fix(obsidian-kb): fix SKILL.md YAML format and restore files

2026-02-07 05:50:00 +08:00
parent a0e43a5136
commit 1f76a40d1f
108 changed files with 9321 additions and 2503 deletions
@@ -56,6 +56,10 @@
    "deepwork-tracker": {
      "version": "0.1.1",
      "installedAt": 1770309243440
+    },
+    "obsidian-kb": {
+      "version": "1.0.0",
+      "installedAt": 1738958400000
    }
  }
 }
@@ -0,0 +1,5 @@
+{
+  "name": "obsidian-kb",
+  "version": "1.0.0",
+  "installedAt": 1738958400000
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "action-gen",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770282130236
+}
@@ -0,0 +1,32 @@
+# ai-github-action
+
+Generate GitHub Actions workflows from plain English. Stop copy-pasting from StackOverflow.
+
+## Install
+
+```bash
+npm install -g ai-github-action
+```
+
+## Usage
+
+```bash
+npx ai-github-action "test and deploy on push to main"
+npx ai-github-action "run eslint and prettier on PRs" --install
+npx ai-github-action "build docker image and push to ECR" -o deploy.yml
+```
+
+## Options
+
+- `--install` - Write directly to `.github/workflows/`
+- `-o, --output <file>` - Write to specific file
+
+## Setup
+
+```bash
+export OPENAI_API_KEY=sk-...
+```
+
+## License
+
+MIT
@@ -0,0 +1,79 @@
+---
+name: github-action-gen
+description: Generate GitHub Actions workflows from plain English. Use when setting up CI.
+---
+
+# GitHub Action Generator
+
+Stop copy-pasting workflow YAML from StackOverflow. Describe what you want and get a working GitHub Actions workflow.
+
+**One command. Zero config. Just works.**
+
+## Quick Start
+
+```bash
+npx ai-github-action "test and deploy on push to main"
+```
+
+## What It Does
+
+- Generates complete GitHub Actions workflow files
+- Handles common patterns like test, build, deploy
+- Includes caching for faster runs
+- Supports multiple deploy targets
+
+## Usage Examples
+
+```bash
+# Test and deploy
+npx ai-github-action "test and deploy on push to main"
+
+# PR checks
+npx ai-github-action "run eslint and prettier on PRs" --install
+
+# Docker workflow
+npx ai-github-action "build docker image and push to ECR" -o deploy.yml
+
+# Scheduled job
+npx ai-github-action "run database backup every night at 2am"
+```
+
+## Best Practices
+
+- **Use secrets** - never hardcode credentials
+- **Cache dependencies** - saves minutes per run
+- **Fail fast** - run quick checks first
+- **Use matrix builds** - test multiple node versions
+
+## When to Use This
+
+- Setting up CI for a new repo
+- Adding deployment automation
+- Creating custom workflows
+- Learning GitHub Actions syntax
+
+## Part of the LXGIC Dev Toolkit
+
+This is one of 110+ free developer tools built by LXGIC Studios. No paywalls, no sign-ups, no API keys on free tiers. Just tools that work.
+
+**Find more:**
+- GitHub: https://github.com/LXGIC-Studios
+- Twitter: https://x.com/lxgicstudios
+- Substack: https://lxgicstudios.substack.com
+- Website: https://lxgic.dev
+
+## Requirements
+
+No install needed. Just run with npx. Node.js 18+ recommended. Needs OPENAI_API_KEY environment variable.
+
+```bash
+npx ai-github-action --help
+```
+
+## How It Works
+
+Takes your plain English description and generates GitHub Actions YAML with the right triggers, jobs, and steps. The AI knows common patterns and best practices for different workflows.
+
+## License
+
+MIT. Free forever. Use it however you want.
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7as1q30eykdpxycyg4tp01n9802dwe",
+  "slug": "action-gen",
+  "version": "1.0.0",
+  "publishedAt": 1769626782553
+}
@@ -0,0 +1,2 @@
+#!/usr/bin/env node
+export {};
@@ -0,0 +1,78 @@
+#!/usr/bin/env node
+"use strict";
+var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    var desc = Object.getOwnPropertyDescriptor(m, k);
+    if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
+      desc = { enumerable: true, get: function() { return m[k]; } };
+    }
+    Object.defineProperty(o, k2, desc);
+}) : (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    o[k2] = m[k];
+}));
+var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
+    Object.defineProperty(o, "default", { enumerable: true, value: v });
+}) : function(o, v) {
+    o["default"] = v;
+});
+var __importStar = (this && this.__importStar) || (function () {
+    var ownKeys = function(o) {
+        ownKeys = Object.getOwnPropertyNames || function (o) {
+            var ar = [];
+            for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
+            return ar;
+        };
+        return ownKeys(o);
+    };
+    return function (mod) {
+        if (mod && mod.__esModule) return mod;
+        var result = {};
+        if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
+        __setModuleDefault(result, mod);
+        return result;
+    };
+})();
+var __importDefault = (this && this.__importDefault) || function (mod) {
+    return (mod && mod.__esModule) ? mod : { "default": mod };
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+const commander_1 = require("commander");
+const ora_1 = __importDefault(require("ora"));
+const fs = __importStar(require("fs"));
+const path = __importStar(require("path"));
+const index_1 = require("./index");
+const program = new commander_1.Command();
+program
+    .name("ai-github-action")
+    .description("Generate GitHub Actions workflows from plain English")
+    .version("1.0.0")
+    .argument("<description>", "Describe the workflow you need")
+    .option("-o, --output <file>", "Output file path")
+    .option("--install", "Write to .github/workflows/ directory", false)
+    .action(async (description, opts) => {
+    const spinner = (0, ora_1.default)("Generating workflow...").start();
+    try {
+        const yaml = await (0, index_1.generateWorkflow)(description);
+        spinner.stop();
+        if (opts.install) {
+            const dir = ".github/workflows";
+            fs.mkdirSync(dir, { recursive: true });
+            const file = path.join(dir, "ai-generated.yml");
+            fs.writeFileSync(file, yaml);
+            console.log(`Workflow written to ${file}`);
+        }
+        else if (opts.output) {
+            fs.writeFileSync(opts.output, yaml);
+            console.log(`Workflow written to ${opts.output}`);
+        }
+        else {
+            console.log("\n" + yaml + "\n");
+        }
+    }
+    catch (err) {
+        spinner.fail(err.message);
+        process.exit(1);
+    }
+});
+program.parse();
@@ -0,0 +1 @@
+export declare function generateWorkflow(description: string): Promise<string>;
@@ -0,0 +1,25 @@
+"use strict";
+var __importDefault = (this && this.__importDefault) || function (mod) {
+    return (mod && mod.__esModule) ? mod : { "default": mod };
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+exports.generateWorkflow = generateWorkflow;
+const openai_1 = __importDefault(require("openai"));
+const openai = new openai_1.default({ apiKey: process.env.OPENAI_API_KEY });
+async function generateWorkflow(description) {
+    const res = await openai.chat.completions.create({
+        model: "gpt-4o-mini",
+        messages: [
+            {
+                role: "system",
+                content: "You are a DevOps expert. Generate a complete GitHub Actions workflow YAML file based on the description. Use best practices: proper triggers, caching, environment variables, and job dependencies. Return ONLY the YAML content, no explanation.",
+            },
+            {
+                role: "user",
+                content: `Create a GitHub Actions workflow: ${description}`,
+            },
+        ],
+        temperature: 0.3,
+    });
+    return res.choices[0].message.content || "";
+}
@@ -0,0 +1,876 @@
+{
+  "name": "ai-github-action",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "ai-github-action",
+      "version": "1.0.0",
+      "license": "MIT",
+      "dependencies": {
+        "commander": "^12.1.0",
+        "openai": "^4.73.0",
+        "ora": "^5.4.1"
+      },
+      "bin": {
+        "ai-github-action": "dist/cli.js"
+      },
+      "devDependencies": {
+        "@types/node": "^22.0.0",
+        "typescript": "^5.6.0"
+      }
+    },
+    "node_modules/@types/node": {
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+      "license": "MIT",
+      "dependencies": {
+        "undici-types": "~6.21.0"
+      }
+    },
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+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ],
+      "license": "MIT"
+    },
+    "node_modules/signal-exit": {
+      "version": "3.0.7",
+      "resolved": "https://registry.npmjs.org/signal-exit/-/signal-exit-3.0.7.tgz",
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+      "license": "ISC"
+    },
+    "node_modules/string_decoder": {
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+      "license": "MIT",
+      "dependencies": {
+        "safe-buffer": "~5.2.0"
+      }
+    },
+    "node_modules/strip-ansi": {
+      "version": "6.0.1",
+      "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "ansi-regex": "^5.0.1"
+      },
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/supports-color": {
+      "version": "7.2.0",
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+      "license": "MIT",
+      "dependencies": {
+        "has-flag": "^4.0.0"
+      },
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/tr46": {
+      "version": "0.0.3",
+      "resolved": "https://registry.npmjs.org/tr46/-/tr46-0.0.3.tgz",
+      "integrity": "sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==",
+      "license": "MIT"
+    },
+    "node_modules/typescript": {
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+      "dev": true,
+      "license": "Apache-2.0",
+      "bin": {
+        "tsc": "bin/tsc",
+        "tsserver": "bin/tsserver"
+      },
+      "engines": {
+        "node": ">=14.17"
+      }
+    },
+    "node_modules/undici-types": {
+      "version": "6.21.0",
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+      "license": "MIT"
+    },
+    "node_modules/util-deprecate": {
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/util-deprecate/-/util-deprecate-1.0.2.tgz",
+      "integrity": "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw==",
+      "license": "MIT"
+    },
+    "node_modules/wcwidth": {
+      "version": "1.0.1",
+      "resolved": "https://registry.npmjs.org/wcwidth/-/wcwidth-1.0.1.tgz",
+      "integrity": "sha512-XHPEwS0q6TaxcvG85+8EYkbiCux2XtWG2mkc47Ng2A77BQu9+DqIOJldST4HgPkuea7dvKSj5VgX3P1d4rW8Tg==",
+      "license": "MIT",
+      "dependencies": {
+        "defaults": "^1.0.3"
+      }
+    },
+    "node_modules/web-streams-polyfill": {
+      "version": "4.0.0-beta.3",
+      "resolved": "https://registry.npmjs.org/web-streams-polyfill/-/web-streams-polyfill-4.0.0-beta.3.tgz",
+      "integrity": "sha512-QW95TCTaHmsYfHDybGMwO5IJIM93I/6vTRk+daHTWFPhwh+C8Cg7j7XyKrwrj8Ib6vYXe0ocYNrmzY4xAAN6ug==",
+      "license": "MIT",
+      "engines": {
+        "node": ">= 14"
+      }
+    },
+    "node_modules/webidl-conversions": {
+      "version": "3.0.1",
+      "resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",
+      "integrity": "sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==",
+      "license": "BSD-2-Clause"
+    },
+    "node_modules/whatwg-url": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-5.0.0.tgz",
+      "integrity": "sha512-saE57nupxk6v3HY35+jzBwYa0rKSy0XR8JSxZPwgLr7ys0IBzhGviA1/TUGJLmSVqs8pb9AnvICXEuOHLprYTw==",
+      "license": "MIT",
+      "dependencies": {
+        "tr46": "~0.0.3",
+        "webidl-conversions": "^3.0.0"
+      }
+    }
+  }
+}
@@ -0,0 +1,14 @@
+{
+  "name": "ai-github-action",
+  "version": "1.0.0",
+  "description": "Generate GitHub Actions workflows from plain English descriptions",
+  "main": "dist/index.js",
+  "bin": { "ai-github-action": "dist/cli.js" },
+  "scripts": { "build": "tsc" },
+  "keywords": ["github", "actions", "ci", "cd", "workflow", "ai"],
+  "license": "MIT",
+  "dependencies": { "commander": "^12.1.0", "openai": "^4.73.0", "ora": "^5.4.1" },
+  "devDependencies": { "typescript": "^5.6.0", "@types/node": "^22.0.0" },
+  "author": "LXGIC Studios",
+  "repository": { "type": "git", "url": "https://github.com/lxgicstudios/ai-github-action" }
+}
@@ -0,0 +1,41 @@
+#!/usr/bin/env node
+
+import { Command } from "commander";
+import ora from "ora";
+import * as fs from "fs";
+import * as path from "path";
+import { generateWorkflow } from "./index";
+
+const program = new Command();
+
+program
+  .name("ai-github-action")
+  .description("Generate GitHub Actions workflows from plain English")
+  .version("1.0.0")
+  .argument("<description>", "Describe the workflow you need")
+  .option("-o, --output <file>", "Output file path")
+  .option("--install", "Write to .github/workflows/ directory", false)
+  .action(async (description, opts) => {
+    const spinner = ora("Generating workflow...").start();
+    try {
+      const yaml = await generateWorkflow(description);
+      spinner.stop();
+      if (opts.install) {
+        const dir = ".github/workflows";
+        fs.mkdirSync(dir, { recursive: true });
+        const file = path.join(dir, "ai-generated.yml");
+        fs.writeFileSync(file, yaml);
+        console.log(`Workflow written to ${file}`);
+      } else if (opts.output) {
+        fs.writeFileSync(opts.output, yaml);
+        console.log(`Workflow written to ${opts.output}`);
+      } else {
+        console.log("\n" + yaml + "\n");
+      }
+    } catch (err: any) {
+      spinner.fail(err.message);
+      process.exit(1);
+    }
+  });
+
+program.parse();
@@ -0,0 +1,21 @@
+import OpenAI from "openai";
+
+const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
+
+export async function generateWorkflow(description: string): Promise<string> {
+  const res = await openai.chat.completions.create({
+    model: "gpt-4o-mini",
+    messages: [
+      {
+        role: "system",
+        content: "You are a DevOps expert. Generate a complete GitHub Actions workflow YAML file based on the description. Use best practices: proper triggers, caching, environment variables, and job dependencies. Return ONLY the YAML content, no explanation.",
+      },
+      {
+        role: "user",
+        content: `Create a GitHub Actions workflow: ${description}`,
+      },
+    ],
+    temperature: 0.3,
+  });
+  return res.choices[0].message.content || "";
+}
@@ -0,0 +1,13 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "module": "commonjs",
+    "outDir": "dist",
+    "rootDir": "src",
+    "esModuleInterop": true,
+    "strict": true,
+    "resolveJsonModule": true,
+    "declaration": true
+  },
+  "include": ["src"]
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "ai-ci",
+  "installedVersion": "1.0.1",
+  "installedAt": 1770282132853
+}
@@ -0,0 +1,89 @@
+---
+name: ci-gen
+description: Generate GitHub Actions workflows from your project. Use when setting up CI/CD from scratch.
+---
+
+# CI Generator
+
+Setting up CI/CD from scratch means searching through docs, copying examples, and tweaking YAML for an hour. This tool looks at your project and generates the right workflow automatically.
+
+**One command. Zero config. Just works.**
+
+## Quick Start
+
+```bash
+npx ai-ci
+```
+
+## What It Does
+
+- Scans your project to detect language and framework
+- Generates complete GitHub Actions workflow
+- Configures linting, testing, building, and deployment
+- Supports multiple deploy targets
+
+## Usage Examples
+
+```bash
+# Generate workflow for current project
+npx ai-ci
+
+# Specify deploy target
+npx ai-ci --deploy vercel
+
+# Preview without writing
+npx ai-ci --preview
+
+# Different targets
+npx ai-ci --deploy netlify
+npx ai-ci --deploy aws
+npx ai-ci --deploy docker
+npx ai-ci --deploy fly
+```
+
+## Best Practices
+
+- **Start simple** - add complexity as needed
+- **Cache dependencies** - speeds up your builds significantly
+- **Fail fast** - run quick checks (lint) before slow ones (e2e)
+- **Review the output** - understand what it's doing before committing
+
+## When to Use This
+
+- Starting a new project and need CI immediately
+- Migrating from another CI system to GitHub Actions
+- Want a solid starting point to customize
+- Not sure what a modern CI workflow should include
+
+## Part of the LXGIC Dev Toolkit
+
+This is one of 110+ free developer tools built by LXGIC Studios. No paywalls, no sign-ups, no API keys on free tiers. Just tools that work.
+
+**Find more:**
+- GitHub: https://github.com/LXGIC-Studios
+- Twitter: https://x.com/lxgicstudios
+- Substack: https://lxgicstudios.substack.com
+- Website: https://lxgicstudios.com
+
+## Requirements
+
+No install needed. Just run with npx. Node.js 18+ recommended. Needs OPENAI_API_KEY environment variable.
+
+```bash
+npx ai-ci --help
+```
+
+## How It Works
+
+Analyzes your package.json, config files, and project structure to determine the language, framework, test setup, and build steps. Then generates a GitHub Actions workflow YAML with appropriate jobs, caching, and deployment configuration.
+
+## License
+
+MIT. Free forever. Use it however you want.
+
+---
+
+**Built by LXGIC Studios**
+
+- GitHub: [github.com/lxgicstudios/ai-ci](https://github.com/lxgicstudios/ai-ci)
+- Twitter: [@lxgicstudios](https://x.com/lxgicstudios)
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7as1q30eykdpxycyg4tp01n9802dwe",
+  "slug": "ai-ci",
+  "version": "1.0.1",
+  "publishedAt": 1769665253626
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "aliyun-tts",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770281952985
+}
@@ -0,0 +1,90 @@
+---
+name: aliyun-tts
+description: Alibaba Cloud Text-to-Speech synthesis service.
+metadata: {"clawdbot":{"emoji":"🔊"}}
+---
+
+# aliyun-tts
+
+Alibaba Cloud Text-to-Speech synthesis service.
+
+## Configuration
+
+Set the following environment variables:
+- `ALIYUN_APP_KEY` - Application Key
+- `ALIYUN_ACCESS_KEY_ID` - Access Key ID
+- `ALIYUN_ACCESS_KEY_SECRET` - Access Key Secret (sensitive)
+
+### Option 1: CLI configuration (recommended)
+
+```bash
+# Configure App Key
+clawdbot skills config aliyun-tts ALIYUN_APP_KEY "your-app-key"
+
+# Configure Access Key ID
+clawdbot skills config aliyun-tts ALIYUN_ACCESS_KEY_ID "your-access-key-id"
+
+# Configure Access Key Secret (sensitive)
+clawdbot skills config aliyun-tts ALIYUN_ACCESS_KEY_SECRET "your-access-key-secret"
+```
+
+### Option 2: Manual configuration
+
+Edit `~/.clawdbot/clawdbot.json`:
+
+```json5
+{
+  skills: {
+    entries: {
+      "aliyun-tts": {
+        env: {
+          ALIYUN_APP_KEY: "your-app-key",
+          ALIYUN_ACCESS_KEY_ID: "your-access-key-id",
+          ALIYUN_ACCESS_KEY_SECRET: "your-access-key-secret"
+        }
+      }
+    }
+  }
+}
+```
+
+## Usage
+
+```bash
+# Basic usage
+{baseDir}/bin/aliyun-tts "Hello, this is Aliyun TTS"
+
+# Specify output file
+{baseDir}/bin/aliyun-tts -o /tmp/voice.mp3 "Hello"
+
+# Specify voice
+{baseDir}/bin/aliyun-tts -v siyue "Use siyue voice"
+
+# Specify format and sample rate
+{baseDir}/bin/aliyun-tts -f mp3 -r 16000 "Audio parameters"
+```
+
+## Options
+
+| Flag | Description | Default |
+|------|-------------|---------|
+| `-o, --output` | Output file path | tts.mp3 |
+| `-v, --voice` | Voice name | siyue |
+| `-f, --format` | Audio format | mp3 |
+| `-r, --sample-rate` | Sample rate | 16000 |
+
+## Available Voices
+
+Common voices: `siyue`, `xiaoxuan`, `xiaoyun`, etc. See Alibaba Cloud documentation for the full list.
+
+## Chat Voice Replies
+
+When a user requests a voice reply:
+
+```bash
+# Generate audio
+{baseDir}/bin/aliyun-tts -o /tmp/voice-reply.mp3 "Your reply content"
+
+# Include in your response:
+# MEDIA:/tmp/voice-reply.mp3
+```
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7153mv5cr4kwrz2drfmfjf55802r2x",
+  "slug": "aliyun-tts",
+  "version": "1.0.0",
+  "publishedAt": 1769631199894
+}
@@ -0,0 +1,140 @@
+#!/usr/bin/env python3
+# -*- coding: UTF-8 -*-
+"""
+阿里云语音合成 TTS - 完整脚本（带签名）
+"""
+
+import base64
+import hashlib
+import hmac
+import http.client
+import json
+import os
+import sys
+import time
+import urllib.parse
+from urllib import parse
+import uuid
+import argparse
+
+# ============ 配置区 ============
+ALIYUN_APP_KEY = os.getenv("ALIYUN_APP_KEY")
+ALIYUN_ACCESS_KEY_ID = os.getenv("ALIYUN_ACCESS_KEY_ID")
+ALIYUN_ACCESS_KEY_SECRET = os.getenv("ALIYUN_ACCESS_KEY_SECRET")
+
+if not ALIYUN_APP_KEY or not ALIYUN_ACCESS_KEY_ID or not ALIYUN_ACCESS_KEY_SECRET:
+    print("请设置环境变量: ALIYUN_APP_KEY, ALIYUN_ACCESS_KEY_ID, ALIYUN_ACCESS_KEY_SECRET", file=sys.stderr)
+    sys.exit(1)
+
+REGION = "cn-shanghai"  # Token 服务只有上海
+# ============ 配置区结束 ============
+
+def percent_encode(text):
+    """RFC 3986 URL 编码"""
+    if text is None:
+        return None
+    encoded = parse.quote_plus(text)
+    return encoded.replace('+', '%20').replace('*', '%2A').replace('%7E', '~')
+
+def encode_dict(dic):
+    """将字典参数排序并编码"""
+    keys = dic.keys()
+    dic_sorted = [(key, dic[key]) for key in sorted(keys)]
+    encoded = parse.urlencode(dic_sorted)
+    return encoded.replace('+', '%20').replace('*', '%2A').replace('%7E', '~')
+
+def get_token():
+    """获取访问令牌（带签名）"""
+    # 1. 构造请求参数
+    params = {
+        'AccessKeyId': ALIYUN_ACCESS_KEY_ID,
+        'Action': 'CreateToken',
+        'Format': 'JSON',
+        'RegionId': REGION,
+        'SignatureMethod': 'HMAC-SHA1',
+        'SignatureNonce': str(uuid.uuid1()),
+        'SignatureVersion': '1.0',
+        'Timestamp': time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+        'Version': '2019-02-28'
+    }
+    
+    # 2. 构造规范化的请求字符串
+    query_string = encode_dict(params)
+    
+    # 3. 构造待签名字符串
+    string_to_sign = 'GET' + '&' + percent_encode('/') + '&' + percent_encode(query_string)
+    
+    # 4. 计算签名
+    secreted_string = hmac.new(
+        bytes(ALIYUN_ACCESS_KEY_SECRET + '&', encoding='utf-8'),
+        bytes(string_to_sign, encoding='utf-8'),
+        hashlib.sha1
+    ).digest()
+    signature = base64.b64encode(secreted_string)
+    signature = percent_encode(signature)
+    
+    # 5. 发送请求
+    full_url = f"http://nls-meta.{REGION}.aliyuncs.com/?Signature={signature}&{query_string}"
+    
+    host = f"nls-meta.{REGION}.aliyuncs.com"
+    conn = http.client.HTTPConnection(host)
+    conn.request("GET", full_url)
+    resp = conn.getresponse()
+    body = resp.read().decode()
+    
+    data = json.loads(body)
+    if "Token" in data and "Id" in data["Token"]:
+        token = data["Token"]["Id"]
+        return token
+    else:
+        print(f"获取 Token 失败: {body}", file=sys.stderr)
+        return None
+
+def tts_synthesize(text, voice="siyue", format="mp3", sample_rate=16000, output_file="/tmp/tts_output.mp3"):
+    """语音合成"""
+    token = get_token()
+    if not token:
+        return False
+    
+    host = f"nls-gateway-{REGION}.aliyuncs.com"
+    
+    # URL 编码（RFC 3986）
+    text_encoded = percent_encode(text)
+    
+    url = f"/stream/v1/tts?appkey={ALIYUN_APP_KEY}&token={token}&text={text_encoded}&format={format}&sample_rate={sample_rate}&voice={voice}"
+    
+    conn = http.client.HTTPSConnection(host)
+    conn.request("GET", url)
+    resp = conn.getresponse()
+    
+    content_type = resp.getheader("Content-Type")
+    body = resp.read()
+    
+    if "audio" in content_type:
+        with open(output_file, "wb") as f:
+            f.write(body)
+        print(f"✅ 语音已保存: {output_file}")
+        return True
+    else:
+        print(f"❌ 失败: {body.decode()[:300]}", file=sys.stderr)
+        return False
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="阿里云 TTS 语音合成")
+    parser.add_argument("text", help="要合成的文本")
+    parser.add_argument("-o", "--output", default="/tmp/tts_output.mp3", help="输出文件路径")
+    parser.add_argument("-v", "--voice", default="siyue", help="声音名称")
+    parser.add_argument("-f", "--format", default="mp3", help="音频格式")
+    parser.add_argument("-r", "--sample-rate", default="16000", help="采样率")
+    
+    args = parser.parse_args()
+    
+    success = tts_synthesize(
+        text=args.text,
+        voice=args.voice,
+        format=args.format,
+        sample_rate=int(args.sample_rate),
+        output_file=args.output
+    )
+    
+    sys.exit(0 if success else 1)
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "ci-config-gen",
+  "installedVersion": "1.0.1",
+  "installedAt": 1770282135433
+}
@@ -0,0 +1,55 @@
+# ai-ci
+
+[![npm version](https://img.shields.io/npm/v/ai-ci.svg)](https://www.npmjs.com/package/ai-ci)
+[![npm downloads](https://img.shields.io/npm/dm/ai-ci.svg)](https://www.npmjs.com/package/ai-ci)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+AI-powered CI/CD workflow generator. Creates GitHub Actions pipelines from project analysis.
+
+Setting up CI/CD from scratch is a pain. This tool looks at your project and generates the right GitHub Actions workflow for it.
+
+## Install
+
+```bash
+npm install -g ai-ci
+```
+
+## Usage
+
+```bash
+# Generate a GitHub Actions workflow
+npx ai-ci
+
+# Specify provider and deploy target
+npx ai-ci --provider github --deploy vercel
+
+# Preview without writing
+npx ai-ci --preview
+
+# Different deploy targets
+npx ai-ci --deploy netlify
+npx ai-ci --deploy aws
+npx ai-ci --deploy docker
+```
+
+## What it does
+
+Scans your project to figure out the language, framework, test setup, and build steps. Then generates a proper CI/CD workflow with linting, testing, building, and deployment configured.
+
+## Supported
+
+- **Providers**: GitHub Actions (more coming)
+- **Deploy targets**: Vercel, Netlify, AWS, Docker, Fly.io, Railway
+- **Languages**: Node.js, Python, Go, Rust, Ruby, Java
+
+## Requirements
+
+Set your `OPENAI_API_KEY` environment variable.
+
+```bash
+export OPENAI_API_KEY=sk-...
+```
+
+## License
+
+MIT
@@ -0,0 +1,82 @@
+---
+name: ci-gen
+description: Generate GitHub Actions workflows from your project. Use when setting up CI/CD from scratch.
+---
+
+# CI Generator
+
+Setting up CI/CD from scratch means searching through docs, copying examples, and tweaking YAML for an hour. This tool looks at your project and generates the right workflow automatically.
+
+**One command. Zero config. Just works.**
+
+## Quick Start
+
+```bash
+npx ai-ci
+```
+
+## What It Does
+
+- Scans your project to detect language and framework
+- Generates complete GitHub Actions workflow
+- Configures linting, testing, building, and deployment
+- Supports multiple deploy targets
+
+## Usage Examples
+
+```bash
+# Generate workflow for current project
+npx ai-ci
+
+# Specify deploy target
+npx ai-ci --deploy vercel
+
+# Preview without writing
+npx ai-ci --preview
+
+# Different targets
+npx ai-ci --deploy netlify
+npx ai-ci --deploy aws
+npx ai-ci --deploy docker
+npx ai-ci --deploy fly
+```
+
+## Best Practices
+
+- **Start simple** - add complexity as needed
+- **Cache dependencies** - speeds up your builds significantly
+- **Fail fast** - run quick checks (lint) before slow ones (e2e)
+- **Review the output** - understand what it's doing before committing
+
+## When to Use This
+
+- Starting a new project and need CI immediately
+- Migrating from another CI system to GitHub Actions
+- Want a solid starting point to customize
+- Not sure what a modern CI workflow should include
+
+## Part of the LXGIC Dev Toolkit
+
+This is one of 110+ free developer tools built by LXGIC Studios. No paywalls, no sign-ups, no API keys on free tiers. Just tools that work.
+
+**Find more:**
+- GitHub: https://github.com/LXGIC-Studios
+- Twitter: https://x.com/lxgicstudios
+- Substack: https://lxgicstudios.substack.com
+- Website: https://lxgicstudios.com
+
+## Requirements
+
+No install needed. Just run with npx. Node.js 18+ recommended. Needs OPENAI_API_KEY environment variable.
+
+```bash
+npx ai-ci --help
+```
+
+## How It Works
+
+Analyzes your package.json, config files, and project structure to determine the language, framework, test setup, and build steps. Then generates a GitHub Actions workflow YAML with appropriate jobs, caching, and deployment configuration.
+
+## License
+
+MIT. Free forever. Use it however you want.
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7as1q30eykdpxycyg4tp01n9802dwe",
+  "slug": "ci-config-gen",
+  "version": "1.0.1",
+  "publishedAt": 1769632242691
+}
@@ -0,0 +1,45 @@
+{
+  "name": "ai-ci",
+  "version": "1.0.0",
+  "description": "Generates GitHub Actions CI/CD workflows from project analysis",
+  "main": "dist/index.js",
+  "bin": {
+    "ai-ci": "dist/cli.js"
+  },
+  "scripts": {
+    "build": "tsc"
+  },
+  "keywords": [
+    "ai",
+    "openai",
+    "gpt",
+    "ci",
+    "cd",
+    "github-actions",
+    "continuous-integration",
+    "devops",
+    "workflow",
+    "automation",
+    "developer-tools",
+    "cli",
+    "typescript",
+    "nodejs",
+    "yaml"
+  ],
+  "license": "MIT",
+  "dependencies": {
+    "commander": "^12.1.0",
+    "glob": "^10.3.10",
+    "openai": "^4.52.0",
+    "ora": "^5.4.1"
+  },
+  "devDependencies": {
+    "typescript": "^5.5.0",
+    "@types/node": "^20.14.0"
+  },
+  "author": "LXGIC Studios",
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/lxgicstudios/ai-ci"
+  }
+}
@@ -0,0 +1,60 @@
+#!/usr/bin/env node
+
+import { Command } from "commander";
+import ora from "ora";
+import * as fs from "fs";
+import * as path from "path";
+import { scanProject, generateWorkflow } from "./index";
+
+const program = new Command();
+
+program
+  .name("ai-ci")
+  .description("Generates CI/CD workflows from project analysis")
+  .version("1.0.0")
+  .option("-p, --preview", "Preview without writing")
+  .option("--provider <provider>", "CI provider", "github")
+  .option("--deploy <target>", "Deploy target (vercel, netlify, aws, docker)")
+  .option("-d, --dir <path>", "Project directory", ".")
+  .option("-o, --output <path>", "Output path")
+  .action(async (opts) => {
+    const spinner = ora("Scanning project...").start();
+
+    try {
+      const dir = path.resolve(opts.dir);
+      const info = await scanProject(dir);
+
+      if (info.files.length === 0) {
+        spinner.warn("No project files found. Are you in the right directory?");
+        process.exit(1);
+      }
+
+      spinner.text = `Found ${info.files.length} config files. Generating workflow...`;
+
+      const workflow = await generateWorkflow(info, opts.provider, opts.deploy);
+
+      const defaultOutput = opts.provider === "github"
+        ? ".github/workflows/ci.yml"
+        : "ci-workflow.yml";
+      const outPath = path.resolve(opts.output || defaultOutput);
+
+      if (opts.preview) {
+        spinner.stop();
+        console.log(`\n--- Generated ${opts.provider} workflow ---\n`);
+        console.log(workflow);
+        console.log("\n-----------------------------------------\n");
+      } else {
+        const outDir = path.dirname(outPath);
+        if (!fs.existsSync(outDir)) {
+          fs.mkdirSync(outDir, { recursive: true });
+        }
+        fs.writeFileSync(outPath, workflow + "\n");
+        spinner.succeed(`Workflow written to ${outPath}`);
+      }
+    } catch (err: any) {
+      spinner.fail(err.message);
+      process.exit(1);
+    }
+  });
+
+program.parse();
@@ -0,0 +1,65 @@
+import OpenAI from "openai";
+import { glob } from "glob";
+import * as fs from "fs";
+import * as path from "path";
+
+const CONFIG_FILES = [
+  "package.json", "tsconfig.json", "next.config.js", "next.config.mjs",
+  "vite.config.ts", "nuxt.config.ts", "Cargo.toml", "go.mod",
+  "pyproject.toml", "requirements.txt", "Gemfile", "build.gradle", "pom.xml",
+  "jest.config.js", "jest.config.ts", "vitest.config.ts", ".eslintrc.js",
+  ".eslintrc.json", "prettier.config.js", "Makefile",
+  "docker-compose.yml", "Dockerfile", "vercel.json", "netlify.toml",
+  "fly.toml", "railway.json",
+];
+
+export async function scanProject(dir: string): Promise<{ files: string[]; contents: Record<string, string> }> {
+  const found: string[] = [];
+  const contents: Record<string, string> = {};
+
+  for (const f of CONFIG_FILES) {
+    const full = path.join(dir, f);
+    if (fs.existsSync(full)) {
+      found.push(f);
+      const stat = fs.statSync(full);
+      if (stat.size < 5000) {
+        contents[f] = fs.readFileSync(full, "utf-8");
+      }
+    }
+  }
+
+  return { files: found, contents };
+}
+
+export async function generateWorkflow(
+  projectInfo: { files: string[]; contents: Record<string, string> },
+  provider: string,
+  deployTarget?: string
+): Promise<string> {
+  if (!process.env.OPENAI_API_KEY) {
+    throw new Error("Missing OPENAI_API_KEY environment variable. Set it with: export OPENAI_API_KEY=sk-...");
+  }
+
+  const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
+
+  const deployInstruction = deployTarget
+    ? `Include a deployment step for ${deployTarget}. Use the standard ${deployTarget} GitHub Action or deployment method.`
+    : "Don't include deployment steps, just CI (lint, test, build).";
+
+  const response = await openai.chat.completions.create({
+    model: "gpt-4o-mini",
+    messages: [
+      {
+        role: "system",
+        content: `You are a CI/CD expert. Generate a ${provider === "github" ? "GitHub Actions" : provider} workflow YAML file. Output ONLY the YAML contents. No markdown code fences. Include proper caching, matrix testing if appropriate, and best practices. ${deployInstruction}`
+      },
+      {
+        role: "user",
+        content: `Project files: ${projectInfo.files.join(", ")}\n\nKey file contents:\n${Object.entries(projectInfo.contents).map(([k, v]) => `--- ${k} ---\n${v}`).join("\n\n")}`
+      }
+    ],
+    temperature: 0.3,
+  });
+
+  return response.choices[0]?.message?.content?.trim() || "";
+}
@@ -0,0 +1,13 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "module": "commonjs",
+    "outDir": "dist",
+    "rootDir": "src",
+    "esModuleInterop": true,
+    "strict": true,
+    "resolveJsonModule": true,
+    "declaration": true
+  },
+  "include": ["src"]
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "ci-gen",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770282141006
+}
@@ -0,0 +1,49 @@
+# ai-ci
+
+Setting up CI/CD from scratch is a pain. This tool looks at your project and generates the right GitHub Actions workflow for it.
+
+## Install
+
+```bash
+npm install -g ai-ci
+```
+
+## Usage
+
+```bash
+# Generate a GitHub Actions workflow
+npx ai-ci
+
+# Specify provider and deploy target
+npx ai-ci --provider github --deploy vercel
+
+# Preview without writing
+npx ai-ci --preview
+
+# Different deploy targets
+npx ai-ci --deploy netlify
+npx ai-ci --deploy aws
+npx ai-ci --deploy docker
+```
+
+## What it does
+
+Scans your project to figure out the language, framework, test setup, and build steps. Then generates a proper CI/CD workflow with linting, testing, building, and deployment configured.
+
+## Supported
+
+- **Providers**: GitHub Actions (more coming)
+- **Deploy targets**: Vercel, Netlify, AWS, Docker, Fly.io, Railway
+- **Languages**: Node.js, Python, Go, Rust, Ruby, Java
+
+## Requirements
+
+Set your `OPENAI_API_KEY` environment variable.
+
+```bash
+export OPENAI_API_KEY=sk-...
+```
+
+## License
+
+MIT
@@ -0,0 +1,77 @@
+---
+name: ci-gen
+description: Generate GitHub Actions CI/CD workflows from project analysis. Use when setting up automated pipelines.
+---
+
+# CI/CD Workflow Generator
+
+Point this at any project and get a working GitHub Actions workflow. It scans your codebase, detects the stack, and generates a pipeline that actually makes sense for your setup.
+
+**One command. Zero config. Just works.**
+
+## Quick Start
+
+```bash
+npx ai-ci ./my-project
+```
+
+## What It Does
+
+- Scans your project to detect framework, language, and dependencies
+- Generates GitHub Actions workflow with proper build and test steps
+- Includes caching for faster CI runs
+- Sets up deployment steps based on common platforms
+- Creates separate workflows for PRs vs main branch pushes
+
+## Usage Examples
+
+```bash
+# Analyze current directory
+npx ai-ci .
+
+# Generate for a specific project
+npx ai-ci ./apps/frontend
+
+# Include deployment to Vercel
+npx ai-ci . --deploy vercel
+```
+
+## Best Practices
+
+- **Review the output** - AI generates good defaults but tweak for your exact needs
+- **Start with tests only** - Get CI green first, add deployment later
+- **Use secrets properly** - The workflow references secrets, make sure to add them in GitHub
+- **Keep it simple** - Don't overcomplicate your first pipeline
+
+## When to Use This
+
+- Starting a new project and need CI fast
+- Migrating from another CI system to GitHub Actions
+- Learning GitHub Actions syntax through real examples
+- Standardizing CI across multiple repos
+
+## Part of the LXGIC Dev Toolkit
+
+This is one of 110+ free developer tools built by LXGIC Studios. No paywalls, no sign-ups, no API keys on free tiers. Just tools that work.
+
+**Find more:**
+- GitHub: https://github.com/LXGIC-Studios
+- Twitter: https://x.com/lxgicstudios
+- Substack: https://lxgicstudios.substack.com
+- Website: https://lxgic.dev
+
+## Requirements
+
+No install needed. Just run with npx. Node.js 18+ recommended.
+
+```bash
+npx ai-ci --help
+```
+
+## How It Works
+
+The tool uses glob patterns to scan your project structure. It identifies package.json, requirements.txt, Dockerfile, and other config files to understand your stack. Then it generates a workflow YAML tailored to what it found.
+
+## License
+
+MIT. Free forever. Use it however you want.
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7as1q30eykdpxycyg4tp01n9802dwe",
+  "slug": "ci-gen",
+  "version": "1.0.0",
+  "publishedAt": 1769626080933
+}
@@ -0,0 +1,35 @@
+{
+  "name": "ai-ci",
+  "version": "1.0.0",
+  "description": "Generates GitHub Actions CI/CD workflows from project analysis",
+  "main": "dist/index.js",
+  "bin": {
+    "ai-ci": "dist/cli.js"
+  },
+  "scripts": {
+    "build": "tsc"
+  },
+  "keywords": [
+    "ci",
+    "cd",
+    "github-actions",
+    "ai",
+    "cli"
+  ],
+  "license": "MIT",
+  "dependencies": {
+    "commander": "^12.1.0",
+    "glob": "^10.3.10",
+    "openai": "^4.52.0",
+    "ora": "^5.4.1"
+  },
+  "devDependencies": {
+    "typescript": "^5.5.0",
+    "@types/node": "^20.14.0"
+  },
+  "author": "LXGIC Studios",
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/lxgicstudios/ai-ci"
+  }
+}
@@ -0,0 +1,60 @@
+#!/usr/bin/env node
+
+import { Command } from "commander";
+import ora from "ora";
+import * as fs from "fs";
+import * as path from "path";
+import { scanProject, generateWorkflow } from "./index";
+
+const program = new Command();
+
+program
+  .name("ai-ci")
+  .description("Generates CI/CD workflows from project analysis")
+  .version("1.0.0")
+  .option("-p, --preview", "Preview without writing")
+  .option("--provider <provider>", "CI provider", "github")
+  .option("--deploy <target>", "Deploy target (vercel, netlify, aws, docker)")
+  .option("-d, --dir <path>", "Project directory", ".")
+  .option("-o, --output <path>", "Output path")
+  .action(async (opts) => {
+    const spinner = ora("Scanning project...").start();
+
+    try {
+      const dir = path.resolve(opts.dir);
+      const info = await scanProject(dir);
+
+      if (info.files.length === 0) {
+        spinner.warn("No project files found. Are you in the right directory?");
+        process.exit(1);
+      }
+
+      spinner.text = `Found ${info.files.length} config files. Generating workflow...`;
+
+      const workflow = await generateWorkflow(info, opts.provider, opts.deploy);
+
+      const defaultOutput = opts.provider === "github"
+        ? ".github/workflows/ci.yml"
+        : "ci-workflow.yml";
+      const outPath = path.resolve(opts.output || defaultOutput);
+
+      if (opts.preview) {
+        spinner.stop();
+        console.log(`\n--- Generated ${opts.provider} workflow ---\n`);
+        console.log(workflow);
+        console.log("\n-----------------------------------------\n");
+      } else {
+        const outDir = path.dirname(outPath);
+        if (!fs.existsSync(outDir)) {
+          fs.mkdirSync(outDir, { recursive: true });
+        }
+        fs.writeFileSync(outPath, workflow + "\n");
+        spinner.succeed(`Workflow written to ${outPath}`);
+      }
+    } catch (err: any) {
+      spinner.fail(err.message);
+      process.exit(1);
+    }
+  });
+
+program.parse();
@@ -0,0 +1,65 @@
+import OpenAI from "openai";
+import { glob } from "glob";
+import * as fs from "fs";
+import * as path from "path";
+
+const CONFIG_FILES = [
+  "package.json", "tsconfig.json", "next.config.js", "next.config.mjs",
+  "vite.config.ts", "nuxt.config.ts", "Cargo.toml", "go.mod",
+  "pyproject.toml", "requirements.txt", "Gemfile", "build.gradle", "pom.xml",
+  "jest.config.js", "jest.config.ts", "vitest.config.ts", ".eslintrc.js",
+  ".eslintrc.json", "prettier.config.js", "Makefile",
+  "docker-compose.yml", "Dockerfile", "vercel.json", "netlify.toml",
+  "fly.toml", "railway.json",
+];
+
+export async function scanProject(dir: string): Promise<{ files: string[]; contents: Record<string, string> }> {
+  const found: string[] = [];
+  const contents: Record<string, string> = {};
+
+  for (const f of CONFIG_FILES) {
+    const full = path.join(dir, f);
+    if (fs.existsSync(full)) {
+      found.push(f);
+      const stat = fs.statSync(full);
+      if (stat.size < 5000) {
+        contents[f] = fs.readFileSync(full, "utf-8");
+      }
+    }
+  }
+
+  return { files: found, contents };
+}
+
+export async function generateWorkflow(
+  projectInfo: { files: string[]; contents: Record<string, string> },
+  provider: string,
+  deployTarget?: string
+): Promise<string> {
+  if (!process.env.OPENAI_API_KEY) {
+    throw new Error("Missing OPENAI_API_KEY environment variable. Set it with: export OPENAI_API_KEY=sk-...");
+  }
+
+  const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
+
+  const deployInstruction = deployTarget
+    ? `Include a deployment step for ${deployTarget}. Use the standard ${deployTarget} GitHub Action or deployment method.`
+    : "Don't include deployment steps, just CI (lint, test, build).";
+
+  const response = await openai.chat.completions.create({
+    model: "gpt-4o-mini",
+    messages: [
+      {
+        role: "system",
+        content: `You are a CI/CD expert. Generate a ${provider === "github" ? "GitHub Actions" : provider} workflow YAML file. Output ONLY the YAML contents. No markdown code fences. Include proper caching, matrix testing if appropriate, and best practices. ${deployInstruction}`
+      },
+      {
+        role: "user",
+        content: `Project files: ${projectInfo.files.join(", ")}\n\nKey file contents:\n${Object.entries(projectInfo.contents).map(([k, v]) => `--- ${k} ---\n${v}`).join("\n\n")}`
+      }
+    ],
+    temperature: 0.3,
+  });
+
+  return response.choices[0]?.message?.content?.trim() || "";
+}
@@ -0,0 +1,13 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "module": "commonjs",
+    "outDir": "dist",
+    "rootDir": "src",
+    "esModuleInterop": true,
+    "strict": true,
+    "resolveJsonModule": true,
+    "declaration": true
+  },
+  "include": ["src"]
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "clawlist",
+  "installedVersion": "0.0.1",
+  "installedAt": 1770309239752
+}
@@ -0,0 +1,89 @@
+---
+name: clawlist
+description: "MUST use for any multi-step project, long-running task, or infinite monitoring workflow. Plan, execute, track, and verify tasks with checkpoint validation. For projects, automation, and ongoing operations."
+---
+
+# Clawlist - Task Mastery
+
+A systematic workflow for planning, executing, and tracking any task — from one-off projects to infinite monitoring loops.
+
+## When to Use This Skill
+
+**ALWAYS use clawlist when:**
+- Starting any new project or initiative
+- Setting up long-running monitoring
+- Breaking down complex goals
+- You need to track progress across sessions
+- Managing infinite tasks (research, monitoring, engagement)
+
+## Long-Running & Infinite Task Examples
+
+### Example: Moltbook Engagement (Infinite)
+- **Type:** Infinite loop
+- **Schedule:** Every 30 minutes
+- **Goal:** Engage with community, build presence
+- **Checkpoints:** Check feed, check DMs, create content
+
+### Example: GitHub Monitoring (Long-Running)
+- **Type:** Continuous
+- **Schedule:** Every 4 hours
+- **Goal:** Monitor repos, triage issues, implement
+- **Checkpoints:** Inbox zero, PR review, implementation
+
+## The Clawlist Workflow
+
+Uses standalone skills in sequence:
+
+1. **brainstorming** → Clarify intent, explore approaches
+2. **write-plan** → Create detailed plan with checkpoints  
+3. **doing-tasks** → Execute with skill discipline
+4. **verify-task** → Confirm completion
+
+For parallel work, insert **dispatch-multiple-agents** between write-plan and doing-tasks.
+
+## Ongoing Tasks File
+
+**Location:** `memory/tasks/ongoing-tasks.md`
+
+Tracks all long-running and infinite tasks. Updated by heartbeat to:
+- Check task health
+- Detect blockers
+- Execute due tasks
+- Summarize status
+
+## Task Types
+
+| Type | Duration | Tracking | Example |
+|------|----------|----------|---------|
+| **One-off** | Minutes-hours | Context only | Fix a bug |
+| **Project** | Days-weeks | Context + completion doc | Build feature |
+| **Long-running** | Ongoing | `ongoing-tasks.md` | GitHub monitoring |
+| **Infinite** | Forever | `ongoing-tasks.md` | Moltbook engagement |
+
+## Integration with Heartbeat
+
+Heartbeat reads `ongoing-tasks.md` every check to:
+- Execute due infinite tasks
+- Detect and report blockers
+- Update health status (🟢🟡🔴)
+- Ping user if intervention needed
+
+## Quick Reference
+
+```
+New Task
+   ↓
+brainstorming → write-plan → doing-tasks → verify-task
+                      ↓
+            dispatch-multiple-agents (if parallel)
+                      ↓
+            update ongoing-tasks.md (if long-running)
+```
+
+## Sub-Skills
+
+- **brainstorming** - Phase 1: Clarify
+- **write-plan** - Phase 2: Plan
+- **doing-tasks** - Phase 3: Execute
+- **dispatch-multiple-agents** - Parallel execution
+- **verify-task** - Phase 4: Verify
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7fmmgtxega8e1rmvf65w1cxh808cgb",
+  "slug": "clawlist",
+  "version": "0.0.1",
+  "publishedAt": 1769828137423
+}
@@ -0,0 +1,46 @@
+---
+name: brainstorming
+description: "MUST use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation."
+---
+
+# Brainstorming Ideas Into Designs
+
+## Overview
+
+Help turn ideas into fully formed designs and specs through natural collaborative dialogue.
+
+Start by understanding the current project context, then ask questions one at a time to refine the idea. Once you understand what you're building, present the design in small sections (200-300 words), checking after each section whether it looks right so far.
+
+## The Process
+
+**Understanding the idea:**
+- Check out the current project state first (files, docs, recent commits)
+- Ask questions one at a time to refine the idea
+- Prefer multiple choice questions when possible, but open-ended is fine too
+- Only one question per message - if a topic needs more exploration, break it into multiple questions
+- Focus on understanding: purpose, constraints, success criteria
+
+**Exploring approaches:**
+- Propose 2-3 different approaches with trade-offs
+- Present options conversationally with your recommendation and reasoning
+- Lead with your recommended option and explain why
+
+**Presenting the design:**
+- Once you believe you understand what you're building, present the design
+- Break it into sections of 200-300 words
+- Ask after each section whether it looks right so far
+- Cover: architecture, components, data flow, error handling, testing
+- Be ready to go back and clarify if something doesn't make sense
+
+## After Brainstorming
+
+Once design is validated, proceed to **write-plan** skill to create the implementation plan.
+
+## Key Principles
+
+- **One question at a time** - Don't overwhelm with multiple questions
+- **Multiple choice preferred** - Easier to answer than open-ended when possible
+- **YAGNI ruthlessly** - Remove unnecessary features from all designs
+- **Explore alternatives** - Always propose 2-3 approaches before settling
+- **Incremental validation** - Present design in sections, validate each
+- **Be flexible** - Go back and clarify when something doesn't make sense
@@ -0,0 +1,76 @@
+---
+name: dispatch-multiple-agents
+description: "Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies. Dispatch subagents to work concurrently."
+---
+
+# Dispatch Multiple Agents
+
+When you have multiple independent tasks, don't do them sequentially. Dispatch agents to work in parallel.
+
+## When to Use
+
+**Use when:**
+- 3+ independent tasks need attention
+- Tasks don't share state or resources
+- No dependencies between tasks
+- Speed matters
+
+**Don't use when:**
+- Tasks are related (fixing one might fix others)
+- Tasks share files/resources (would conflict)
+- You need full system context for all tasks
+- Tasks must happen in specific order
+
+## The Pattern
+
+### 1. Identify Independent Domains
+
+Group work by what's needed:
+- Task A: Research competitor A
+- Task B: Research competitor B  
+- Task C: Research competitor C
+
+Each is independent.
+
+### 2. Create Focused Tasks
+
+Each subagent gets:
+- **Specific scope:** One clear task
+- **All context needed:** Don't make them hunt
+- **Clear output:** What should they return?
+- **Constraints:** What NOT to touch
+
+### 3. Dispatch in Parallel
+
+Using sessions_spawn for concurrent execution.
+
+### 4. Review and Integrate
+
+When agents return:
+- Read each result
+- Verify no conflicts
+- Integrate findings
+- Report summary
+
+## Integration with Other Skills
+
+Use dispatch-multiple-agents WITHIN the workflow:
+
+```
+brainstorming → write-plan → dispatch-multiple-agents → verify-task
+                                   ↓
+                            doing-tasks (per subagent)
+```
+
+## Example
+
+**Problem:** Research 5 competitors
+
+**Dispatch:**
+- Agent 1 → Competitor A
+- Agent 2 → Competitor B
+- Agent 3 → Competitor C
+- Agent 4 → Competitor D
+- Agent 5 → Competitor E
+
+**Result:** Full analysis in minutes, not hours.
@@ -0,0 +1,111 @@
+---
+name: doing-tasks
+description: "Use when executing any task. Work through plans systematically, tracking progress, handling blockers, and coordinating with other skills. The central execution skill."
+---
+
+# Doing Tasks - Execution Core
+
+## The Rule
+
+**If a task exists, you MUST use the appropriate skill before acting.**
+
+```
+User message received
+    ↓
+Might any skill apply? → YES (even 1% chance) → Invoke skill
+    ↓                                    ↓
+    NO ← definitely not                  Announce: "Using [skill]"
+    ↓                                    ↓
+Respond                              Follow skill exactly
+```
+
+## Skill Priority
+
+When multiple skills could apply:
+
+1. **Process skills first** (brainstorming, debugging) - determine HOW
+2. **Planning skills second** (write-plan) - create roadmap
+3. **Execution skills third** (doing-tasks, dispatch-multiple-agents) - do the work
+4. **Verification skills last** (verify-task) - confirm completion
+
+## The Workflow
+
+### Standard Project Flow:
+
+```
+brainstorming → write-plan → doing-tasks → verify-task
+     ↑                              ↓
+     └────── refinement ←───────────┘
+```
+
+### With Parallel Execution:
+
+```
+brainstorming → write-plan → dispatch-multiple-agents → verify-task
+                                   ↓
+                            doing-tasks (per subagent)
+```
+
+## Red Flags - STOP and Check Skills
+
+| Thought | Reality |
+|---------|---------|
+| "This is just a simple question" | Questions are tasks. Check for skills. |
+| "I need more context first" | Skill check comes BEFORE clarifying. |
+| "Let me explore first" | Skills tell you HOW to explore. |
+| "I can check files quickly" | Check for skills first. |
+| "I remember this skill" | Skills evolve. Read current version. |
+| "This doesn't need a formal skill" | If a skill exists, use it. |
+| "I'll just do this one thing first" | Check BEFORE doing anything. |
+
+## Execution Discipline
+
+### Do:
+- Check for skills BEFORE any action
+- Follow the plan exactly
+- Mark tasks complete as you finish
+- Report blockers immediately
+- Ask for clarification when unclear
+
+### Don't:
+- Skip skills because "it's simple"
+- Add unplanned scope without approval
+- Work silently for long periods
+- Guess when unclear
+- Let blockers sit unreported
+
+## Integration with Clawlist
+
+For long-running or infinite tasks:
+
+```
+doing-tasks → update ongoing-tasks.md → schedule next run
+```
+
+The doing-tasks skill executes, then updates the task tracking file for heartbeat monitoring.
+
+## Sub-Skills Reference
+
+- **brainstorming** - Before any creative work
+- **write-plan** - After design, before execution
+- **dispatch-multiple-agents** - For parallel independent tasks
+- **verify-task** - After completion
+
+## Example
+
+**User:** "Build me a todo app"
+
+**Correct flow:**
+1. "Using brainstorming skill to clarify requirements"
+2. Brainstorm: Ask questions, explore approaches
+3. "Using write-plan skill to create implementation plan"
+4. Write-plan: Create checkpoints and tasks
+5. "Using doing-tasks skill to execute"
+6. Execute: Work through plan
+7. "Using verify-task skill to confirm completion"
+8. Verify: Check against plan, get user approval
+
+**Incorrect:**
+- Jumping straight to coding without brainstorming
+- Starting work without a plan
+- Skipping verification
@@ -0,0 +1,106 @@
+---
+name: verify-task
+description: "MUST use after completing any multi-step task or project. Verifies completion against the original plan, checks quality criteria, and documents outcomes."
+---
+
+# Verify Task
+
+## Overview
+
+Confirm successful completion and document outcomes against the original plan.
+
+## When to Verify
+
+- All tasks from plan are marked complete
+- User asks "is it done?" or "did it work?"
+- Before declaring a project finished
+- After each checkpoint in long-running tasks
+
+## Verification Process
+
+### Step 1: Load Original Plan
+
+Read the plan that was created by write-plan skill.
+
+### Step 2: Verify Each Checkpoint
+
+Go through each checkpoint and confirm:
+- [ ] All tasks marked complete
+- [ ] Verification criteria met
+- [ ] Quality standards achieved
+
+### Step 3: Final Quality Checks
+
+**General quality criteria:**
+- [ ] Output matches original goal
+- [ ] No obvious errors or issues
+- [ ] Documentation updated (if applicable)
+- [ ] User can use/access the result
+
+### Step 4: User Confirmation
+
+```
+"Verification complete. Final checks:
+
+✓ All tasks from plan completed (X/Y)
+✓ Quality criteria met
+✓ [Specific checks]
+
+[Preview/demonstrate result]
+
+Does this meet your expectations? Any adjustments needed?"
+```
+
+### Step 5: Document Completion
+
+Save completion report to: `memory/plans/YYYY-MM-DD-<project>-complete.md`
+
+Template:
+```markdown
+# [Project] - Completion Report
+
+**Date Completed:** YYYY-MM-DD
+**Original Goal:** [from plan]
+**Final Result:** [brief description]
+
+## Completion Summary
+
+| Metric | Planned | Actual |
+|--------|---------|--------|
+| Checkpoints | X | X |
+| Tasks | Y | Y |
+| Time | Z min | W min |
+
+## Verification Checklist
+
+- [x] All tasks complete
+- [x] Quality criteria met
+- [x] User approved
+
+## What Was Delivered
+
+[Description of final output]
+
+## Blockers Encountered
+
+1. [Blocker] → [Resolution]
+
+## Lessons Learned
+
+- [What worked well]
+- [What to do differently next time]
+```
+
+## Handling Issues
+
+### If verification fails:
+
+**Minor issues:** Quick fixes, proceed
+**Major issues:** Return to doing-tasks or re-plan
+
+## Principles
+
+- **Objectivity** - Verify against the plan, not assumptions
+- **Thoroughness** - Check all criteria
+- **Honesty** - Report issues, don't hide problems
+- **User-centric** - Final approval comes from user satisfaction
@@ -0,0 +1,76 @@
+---
+name: write-plan
+description: "MUST use after brainstorming and before executing. Creates detailed implementation plans with checkpoints, verification criteria, and execution options."
+---
+
+# Write Plan
+
+## Overview
+
+Transform validated designs into detailed, actionable implementation plans with checkpoints.
+
+Every plan includes:
+- Bite-sized tasks (2-5 minutes each)
+- Checkpoints with verification criteria
+- Estimated time for each section
+- Execution options at the end
+
+## Plan Structure
+
+```markdown
+# [Project Name] - Implementation Plan
+
+**Goal:** One sentence describing success
+**Approach:** Brief summary of the chosen approach
+**Estimated Total Time:** X minutes
+
+## Checkpoint 1: [Milestone Name]
+- [ ] Task 1: [Description] (~X min)
+  - **Action:** [Specific action]
+  - **Verify:** [How to confirm done]
+- [ ] Task 2: [Description] (~X min)
+  ...
+
+## Checkpoint 2: [Milestone Name]
+...
+
+## Verification Criteria
+- [ ] All checkpoints complete
+- [ ] Quality standards met
+- [ ] User approval obtained
+```
+
+## Task Granularity
+
+- **Small:** 2-5 minutes of work
+- **Specific:** Clear what "done" means
+- **Verifiable:** Can confirm completion
+- **Independent:** Doesn't block on other tasks in same checkpoint
+
+## Execution Handoff
+
+After saving the plan, offer execution choice:
+
+**"Plan complete and saved to `memory/plans/<filename>.md`. Two execution options:**
+
+**1. Single-Agent (this session)** - I execute tasks sequentially, review at each checkpoint
+
+**2. Dispatch Multiple Agents (parallel)** - Spawn subagents for independent tasks
+
+**Which approach?"**
+
+**If Single-Agent chosen:**
+- Stay in this session
+- Execute tasks sequentially
+- Report progress at each checkpoint
+
+**If Dispatch Multiple Agents chosen:**
+- Use dispatch-multiple-agents skill
+- Spawn subagents for parallel work
+- Integrate results
+
+## Integration with Other Skills
+
+- After **brainstorming** → Use write-plan
+- Before **doing-tasks** → Plan must exist
+- With **dispatch-multiple-agents** → For parallel execution
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "deepwork-tracker",
+  "installedVersion": "0.1.1",
+  "installedAt": 1770309243439
+}
@@ -0,0 +1,61 @@
+---
+name: deepwork-tracker
+description: Track deep work sessions locally (start/stop/status) and generate a GitHub-contribution-graph style minutes-per-day heatmap for sharing (e.g., via Telegram). Use when the user says things like “start deep work”, “stop deep work”, “am I in a session?”, “show my deep work graph”, or asks to review deep work history.
+---
+
+# Deepwork Tracker
+
+Use the local deepwork app (SQLite-backed) at `~/clawd/deepwork/deepwork.js`.
+
+## Bootstrap (if the script is missing)
+
+If `~/clawd/deepwork/deepwork.js` does not exist, bootstrap it from the public repo:
+
+```bash
+mkdir -p ~/clawd
+cd ~/clawd
+
+# Clone if missing
+[ -d ~/clawd/deepwork-tracker/.git ] || git clone https://github.com/adunne09/deepwork-tracker.git ~/clawd/deepwork-tracker
+
+# Ensure expected runtime path exists
+mkdir -p ~/clawd/deepwork
+cp -f ~/clawd/deepwork-tracker/app/deepwork.js ~/clawd/deepwork/deepwork.js
+chmod +x ~/clawd/deepwork/deepwork.js
+```
+
+(Do not fail the user request if clone/copy fails—still attempt other steps and report what’s missing.)
+
+## Commands
+
+Run via exec:
+
+- Start a session (also starts a macOS Clock timer; default target 60m):
+  - `~/clawd/deepwork/deepwork.js start --target-min 60`
+- Stop a session:
+  - `~/clawd/deepwork/deepwork.js stop`
+- Check status:
+  - `~/clawd/deepwork/deepwork.js status`
+- Generate a report:
+  - Last 7 days (default): `~/clawd/deepwork/deepwork.js report --days 7 --format text`
+  - Telegram-ready last 7 days: `~/clawd/deepwork/deepwork.js report --days 7 --format telegram`
+  - Heatmap (optional): `~/clawd/deepwork/deepwork.js report --mode heatmap --weeks 52 --format telegram`
+
+## Chat workflows
+
+### Start deep work
+1) Run `~/clawd/deepwork/deepwork.js start --target-min 60` (or another target if the user specifies it).
+2) This should also start a macOS Clock timer for the target duration (best-effort; may require Accessibility permissions).
+3) Reply with the confirmation line.
+
+### Stop deep work
+1) Run `~/clawd/deepwork/deepwork.js stop`.
+2) Reply with duration.
+
+### Show deep work graph
+1) Run `~/clawd/deepwork/deepwork.js report --days 7 --format telegram`.
+2) **Always send** the output to Alex on Telegram (id `8551040296`) using the `message` tool with a Markdown monospace code block.
+3) Optionally acknowledge in the current chat that it was sent.
+
+If the user wants different ranges, support `--days 7|14|30|60`.
+(Heatmap is still available via `--mode heatmap --weeks ...` when explicitly requested.)
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn73pg8hvybca4jc60ftcqpdqn7zre7f",
+  "slug": "deepwork-tracker",
+  "version": "0.1.1",
+  "publishedAt": 1769190851401
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "frontend-design",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770309241776
+}
@@ -0,0 +1,190 @@
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+
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+   limitations under the License.
@@ -0,0 +1,42 @@
+---
+name: frontend-design
+description: Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
+license: Complete terms in LICENSE.txt
+---
+
+This skill guides creation of distinctive, production-grade frontend interfaces that avoid generic "AI slop" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.
+
+The user provides frontend requirements: a component, page, application, or interface to build. They may include context about the purpose, audience, or technical constraints.
+
+## Design Thinking
+
+Before coding, understand the context and commit to a BOLD aesthetic direction:
+- **Purpose**: What problem does this interface solve? Who uses it?
+- **Tone**: Pick an extreme: brutally minimal, maximalist chaos, retro-futuristic, organic/natural, luxury/refined, playful/toy-like, editorial/magazine, brutalist/raw, art deco/geometric, soft/pastel, industrial/utilitarian, etc. There are so many flavors to choose from. Use these for inspiration but design one that is true to the aesthetic direction.
+- **Constraints**: Technical requirements (framework, performance, accessibility).
+- **Differentiation**: What makes this UNFORGETTABLE? What's the one thing someone will remember?
+
+**CRITICAL**: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work - the key is intentionality, not intensity.
+
+Then implement working code (HTML/CSS/JS, React, Vue, etc.) that is:
+- Production-grade and functional
+- Visually striking and memorable
+- Cohesive with a clear aesthetic point-of-view
+- Meticulously refined in every detail
+
+## Frontend Aesthetics Guidelines
+
+Focus on:
+- **Typography**: Choose fonts that are beautiful, unique, and interesting. Avoid generic fonts like Arial and Inter; opt instead for distinctive choices that elevate the frontend's aesthetics; unexpected, characterful font choices. Pair a distinctive display font with a refined body font.
+- **Color & Theme**: Commit to a cohesive aesthetic. Use CSS variables for consistency. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.
+- **Motion**: Use animations for effects and micro-interactions. Prioritize CSS-only solutions for HTML. Use Motion library for React when available. Focus on high-impact moments: one well-orchestrated page load with staggered reveals (animation-delay) creates more delight than scattered micro-interactions. Use scroll-triggering and hover states that surprise.
+- **Spatial Composition**: Unexpected layouts. Asymmetry. Overlap. Diagonal flow. Grid-breaking elements. Generous negative space OR controlled density.
+- **Backgrounds & Visual Details**: Create atmosphere and depth rather than defaulting to solid colors. Add contextual effects and textures that match the overall aesthetic. Apply creative forms like gradient meshes, noise textures, geometric patterns, layered transparencies, dramatic shadows, decorative borders, custom cursors, and grain overlays.
+
+NEVER use generic AI-generated aesthetics like overused font families (Inter, Roboto, Arial, system fonts), cliched color schemes (particularly purple gradients on white backgrounds), predictable layouts and component patterns, and cookie-cutter design that lacks context-specific character.
+
+Interpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices (Space Grotesk, for example) across generations.
+
+**IMPORTANT**: Match implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details. Elegance comes from executing the vision well.
+
+Remember: Claude is capable of extraordinary creative work. Don't hold back, show what can truly be created when thinking outside the box and committing fully to a distinctive vision.
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn70pywhg0fyz996kpa8xj89s57yhv26",
+  "slug": "frontend-design",
+  "version": "1.0.0",
+  "publishedAt": 1767651960903
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "gitclassic",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770282124174
+}
@@ -0,0 +1,99 @@
+---
+name: gitclassic
+description: "Fast, no-JavaScript GitHub browser optimized for AI agents. Browse public repos, read files, view READMEs with sub-500ms load times. PRO adds private repo access via GitHub OAuth."
+author: heythisischris
+version: 1.0.0
+license: MIT
+homepage: https://gitclassic.com
+---
+
+# GitClassic - Fast GitHub Browser for AI Agents
+
+## Overview
+
+GitClassic is a read-only GitHub interface that's pure server-rendered HTML — no JavaScript, no bloat, instant loads. Perfect for AI agents that need to browse repos without dealing with GitHub's heavy client-side rendering.
+
+## When to Use
+
+Use GitClassic when you need to:
+- Browse GitHub repositories quickly
+- Read file contents from public repos
+- View READMEs and documentation
+- Search for users, orgs, or repos
+- Access private repos (PRO feature)
+
+## URL Patterns
+
+Replace `github.com` with `gitclassic.com` in any GitHub URL:
+
+```
+# Repository root
+https://gitclassic.com/{owner}/{repo}
+
+# File browser
+https://gitclassic.com/{owner}/{repo}/tree/{branch}/{path}
+
+# File contents
+https://gitclassic.com/{owner}/{repo}/blob/{branch}/{path}
+
+# User/org profile
+https://gitclassic.com/{username}
+
+# Search
+https://gitclassic.com/search?q={query}
+```
+
+## Examples
+
+```bash
+# View a repository
+curl https://gitclassic.com/facebook/react
+
+# Read a specific file
+curl https://gitclassic.com/facebook/react/blob/main/README.md
+
+# Browse a directory
+curl https://gitclassic.com/facebook/react/tree/main/packages
+
+# Search for repos
+curl "https://gitclassic.com/search?q=machine+learning"
+
+# View user profile
+curl https://gitclassic.com/torvalds
+```
+
+## Why Use GitClassic Over github.com
+
+| Feature | github.com | gitclassic.com |
+|---------|-----------|----------------|
+| Page load | 2-5 seconds | <500ms |
+| JavaScript required | Yes | No |
+| HTML complexity | Heavy (React SPA) | Minimal (server-rendered) |
+| Rate limits | 60/hr unauthenticated | Cached responses |
+| AI agent friendly | Difficult to parse | Clean, semantic HTML |
+
+## Authentication (PRO)
+
+For private repository access, users need a GitClassic PRO subscription ($19/year or $49/lifetime). Authentication is handled via GitHub OAuth on the GitClassic website.
+
+Once authenticated, the agent can access any private repo the user has granted access to using the same URL patterns.
+
+## Limitations
+
+- **Read-only**: Cannot create issues, PRs, or modify repos
+- **No GitHub Actions**: Cannot view workflow runs or logs
+- **No GitHub API**: Uses screen scraping, not the GitHub API directly
+- **Private repos require PRO**: Free tier is public repos only
+
+## Tips for Agents
+
+1. **Prefer GitClassic for reading**: When you only need to read code or docs, use GitClassic for faster responses
+2. **Use GitHub for actions**: For creating issues, PRs, or any write operations, use the `gh` CLI or GitHub API
+3. **Cache-friendly**: GitClassic responses are heavily cached, so repeated requests are fast
+4. **Clean HTML**: The HTML is semantic and minimal — easy to parse with standard tools
+
+## Related Skills
+
+- `github` - Full GitHub CLI for read/write operations
+- `github-pr` - PR management and testing
+- `read-github` - Alternative GitHub reader via gitmcp.io
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn76bsxaax6j1g8w04pzmwa8x18097rt",
+  "slug": "gitclassic",
+  "version": "1.0.0",
+  "publishedAt": 1769833030826
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "github-action-gen",
+  "installedVersion": "1.0.2",
+  "installedAt": 1770282120467
+}
@@ -0,0 +1,32 @@
+# ai-github-action
+
+Generate GitHub Actions workflows from plain English. Stop copy-pasting from StackOverflow.
+
+## Install
+
+```bash
+npm install -g ai-github-action
+```
+
+## Usage
+
+```bash
+npx ai-github-action "test and deploy on push to main"
+npx ai-github-action "run eslint and prettier on PRs" --install
+npx ai-github-action "build docker image and push to ECR" -o deploy.yml
+```
+
+## Options
+
+- `--install` - Write directly to `.github/workflows/`
+- `-o, --output <file>` - Write to specific file
+
+## Setup
+
+```bash
+export OPENAI_API_KEY=sk-...
+```
+
+## License
+
+MIT
@@ -0,0 +1,79 @@
+---
+name: github-action-gen
+description: Generate GitHub Actions workflows from plain English. Use when setting up CI.
+---
+
+# GitHub Action Generator
+
+Stop copy-pasting workflow YAML from StackOverflow. Describe what you want and get a working GitHub Actions workflow.
+
+**One command. Zero config. Just works.**
+
+## Quick Start
+
+```bash
+npx ai-github-action "test and deploy on push to main"
+```
+
+## What It Does
+
+- Generates complete GitHub Actions workflow files
+- Handles common patterns like test, build, deploy
+- Includes caching for faster runs
+- Supports multiple deploy targets
+
+## Usage Examples
+
+```bash
+# Test and deploy
+npx ai-github-action "test and deploy on push to main"
+
+# PR checks
+npx ai-github-action "run eslint and prettier on PRs" --install
+
+# Docker workflow
+npx ai-github-action "build docker image and push to ECR" -o deploy.yml
+
+# Scheduled job
+npx ai-github-action "run database backup every night at 2am"
+```
+
+## Best Practices
+
+- **Use secrets** - never hardcode credentials
+- **Cache dependencies** - saves minutes per run
+- **Fail fast** - run quick checks first
+- **Use matrix builds** - test multiple node versions
+
+## When to Use This
+
+- Setting up CI for a new repo
+- Adding deployment automation
+- Creating custom workflows
+- Learning GitHub Actions syntax
+
+## Part of the LXGIC Dev Toolkit
+
+This is one of 110+ free developer tools built by LXGIC Studios. No paywalls, no sign-ups, no API keys on free tiers. Just tools that work.
+
+**Find more:**
+- GitHub: https://github.com/LXGIC-Studios
+- Twitter: https://x.com/lxgicstudios
+- Substack: https://lxgicstudios.substack.com
+- Website: https://lxgicstudios.com
+
+## Requirements
+
+No install needed. Just run with npx. Node.js 18+ recommended. Needs OPENAI_API_KEY environment variable.
+
+```bash
+npx ai-github-action --help
+```
+
+## How It Works
+
+Takes your plain English description and generates GitHub Actions YAML with the right triggers, jobs, and steps. The AI knows common patterns and best practices for different workflows.
+
+## License
+
+MIT. Free forever. Use it however you want.
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7as1q30eykdpxycyg4tp01n9802dwe",
+  "slug": "github-action-gen",
+  "version": "1.0.2",
+  "publishedAt": 1769633032570
+}
@@ -0,0 +1,2 @@
+#!/usr/bin/env node
+export {};
@@ -0,0 +1,78 @@
+#!/usr/bin/env node
+"use strict";
+var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    var desc = Object.getOwnPropertyDescriptor(m, k);
+    if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
+      desc = { enumerable: true, get: function() { return m[k]; } };
+    }
+    Object.defineProperty(o, k2, desc);
+}) : (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    o[k2] = m[k];
+}));
+var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
+    Object.defineProperty(o, "default", { enumerable: true, value: v });
+}) : function(o, v) {
+    o["default"] = v;
+});
+var __importStar = (this && this.__importStar) || (function () {
+    var ownKeys = function(o) {
+        ownKeys = Object.getOwnPropertyNames || function (o) {
+            var ar = [];
+            for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
+            return ar;
+        };
+        return ownKeys(o);
+    };
+    return function (mod) {
+        if (mod && mod.__esModule) return mod;
+        var result = {};
+        if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
+        __setModuleDefault(result, mod);
+        return result;
+    };
+})();
+var __importDefault = (this && this.__importDefault) || function (mod) {
+    return (mod && mod.__esModule) ? mod : { "default": mod };
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+const commander_1 = require("commander");
+const ora_1 = __importDefault(require("ora"));
+const fs = __importStar(require("fs"));
+const path = __importStar(require("path"));
+const index_1 = require("./index");
+const program = new commander_1.Command();
+program
+    .name("ai-github-action")
+    .description("Generate GitHub Actions workflows from plain English")
+    .version("1.0.0")
+    .argument("<description>", "Describe the workflow you need")
+    .option("-o, --output <file>", "Output file path")
+    .option("--install", "Write to .github/workflows/ directory", false)
+    .action(async (description, opts) => {
+    const spinner = (0, ora_1.default)("Generating workflow...").start();
+    try {
+        const yaml = await (0, index_1.generateWorkflow)(description);
+        spinner.stop();
+        if (opts.install) {
+            const dir = ".github/workflows";
+            fs.mkdirSync(dir, { recursive: true });
+            const file = path.join(dir, "ai-generated.yml");
+            fs.writeFileSync(file, yaml);
+            console.log(`Workflow written to ${file}`);
+        }
+        else if (opts.output) {
+            fs.writeFileSync(opts.output, yaml);
+            console.log(`Workflow written to ${opts.output}`);
+        }
+        else {
+            console.log("\n" + yaml + "\n");
+        }
+    }
+    catch (err) {
+        spinner.fail(err.message);
+        process.exit(1);
+    }
+});
+program.parse();
@@ -0,0 +1 @@
+export declare function generateWorkflow(description: string): Promise<string>;
@@ -0,0 +1,25 @@
+"use strict";
+var __importDefault = (this && this.__importDefault) || function (mod) {
+    return (mod && mod.__esModule) ? mod : { "default": mod };
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+exports.generateWorkflow = generateWorkflow;
+const openai_1 = __importDefault(require("openai"));
+const openai = new openai_1.default({ apiKey: process.env.OPENAI_API_KEY });
+async function generateWorkflow(description) {
+    const res = await openai.chat.completions.create({
+        model: "gpt-4o-mini",
+        messages: [
+            {
+                role: "system",
+                content: "You are a DevOps expert. Generate a complete GitHub Actions workflow YAML file based on the description. Use best practices: proper triggers, caching, environment variables, and job dependencies. Return ONLY the YAML content, no explanation.",
+            },
+            {
+                role: "user",
+                content: `Create a GitHub Actions workflow: ${description}`,
+            },
+        ],
+        temperature: 0.3,
+    });
+    return res.choices[0].message.content || "";
+}
@@ -0,0 +1,876 @@
+{
+  "name": "ai-github-action",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "ai-github-action",
+      "version": "1.0.0",
+      "license": "MIT",
+      "dependencies": {
+        "commander": "^12.1.0",
+        "openai": "^4.73.0",
+        "ora": "^5.4.1"
+      },
+      "bin": {
+        "ai-github-action": "dist/cli.js"
+      },
+      "devDependencies": {
+        "@types/node": "^22.0.0",
+        "typescript": "^5.6.0"
+      }
+    },
+    "node_modules/@types/node": {
+      "version": "22.19.7",
+      "resolved": "https://registry.npmjs.org/@types/node/-/node-22.19.7.tgz",
+      "integrity": "sha512-MciR4AKGHWl7xwxkBa6xUGxQJ4VBOmPTF7sL+iGzuahOFaO0jHCsuEfS80pan1ef4gWId1oWOweIhrDEYLuaOw==",
+      "license": "MIT",
+      "dependencies": {
+        "undici-types": "~6.21.0"
+      }
+    },
+    "node_modules/@types/node-fetch": {
+      "version": "2.6.13",
+      "resolved": "https://registry.npmjs.org/@types/node-fetch/-/node-fetch-2.6.13.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "@types/node": "*",
+        "form-data": "^4.0.4"
+      }
+    },
+    "node_modules/abort-controller": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/abort-controller/-/abort-controller-3.0.0.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "event-target-shim": "^5.0.0"
+      },
+      "engines": {
+        "node": ">=6.5"
+      }
+    },
+    "node_modules/agentkeepalive": {
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+      "license": "MIT",
+      "dependencies": {
+        "humanize-ms": "^1.2.1"
+      },
+      "engines": {
+        "node": ">= 8.0.0"
+      }
+    },
+    "node_modules/ansi-regex": {
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+      "license": "MIT",
+      "engines": {
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+      }
+    },
+    "node_modules/ansi-styles": {
+      "version": "4.3.0",
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+      "license": "MIT",
+      "dependencies": {
+        "color-convert": "^2.0.1"
+      },
+      "engines": {
+        "node": ">=8"
+      },
+      "funding": {
+        "url": "https://github.com/chalk/ansi-styles?sponsor=1"
+      }
+    },
+    "node_modules/asynckit": {
+      "version": "0.4.0",
+      "resolved": "https://registry.npmjs.org/asynckit/-/asynckit-0.4.0.tgz",
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+      "license": "MIT"
+    },
+    "node_modules/base64-js": {
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+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ],
+      "license": "MIT"
+    },
+    "node_modules/bl": {
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+      "resolved": "https://registry.npmjs.org/bl/-/bl-4.1.0.tgz",
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+        "inherits": "^2.0.4",
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+      }
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+      "funding": [
+        {
+          "type": "github",
+          "url": "https://github.com/sponsors/feross"
+        },
+        {
+          "type": "patreon",
+          "url": "https://www.patreon.com/feross"
+        },
+        {
+          "type": "consulting",
+          "url": "https://feross.org/support"
+        }
+      ],
+      "license": "MIT",
+      "dependencies": {
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+        "ieee754": "^1.1.13"
+      }
+    },
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+        "function-bind": "^1.1.2"
+      },
+      "engines": {
+        "node": ">= 0.4"
+      }
+    },
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+        "supports-color": "^7.1.0"
+      },
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+      },
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+      },
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+      }
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+        },
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+          "url": "https://feross.org/support"
+        }
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+    "node_modules/webidl-conversions": {
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+      "license": "BSD-2-Clause"
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+    "node_modules/whatwg-url": {
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+      "resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-5.0.0.tgz",
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+      "license": "MIT",
+      "dependencies": {
+        "tr46": "~0.0.3",
+        "webidl-conversions": "^3.0.0"
+      }
+    }
+  }
+}
@@ -0,0 +1,14 @@
+{
+  "name": "ai-github-action",
+  "version": "1.0.0",
+  "description": "Generate GitHub Actions workflows from plain English descriptions",
+  "main": "dist/index.js",
+  "bin": { "ai-github-action": "dist/cli.js" },
+  "scripts": { "build": "tsc" },
+  "keywords": ["github", "actions", "ci", "cd", "workflow", "ai"],
+  "license": "MIT",
+  "dependencies": { "commander": "^12.1.0", "openai": "^4.73.0", "ora": "^5.4.1" },
+  "devDependencies": { "typescript": "^5.6.0", "@types/node": "^22.0.0" },
+  "author": "LXGIC Studios",
+  "repository": { "type": "git", "url": "https://github.com/lxgicstudios/ai-github-action" }
+}
@@ -0,0 +1,41 @@
+#!/usr/bin/env node
+
+import { Command } from "commander";
+import ora from "ora";
+import * as fs from "fs";
+import * as path from "path";
+import { generateWorkflow } from "./index";
+
+const program = new Command();
+
+program
+  .name("ai-github-action")
+  .description("Generate GitHub Actions workflows from plain English")
+  .version("1.0.0")
+  .argument("<description>", "Describe the workflow you need")
+  .option("-o, --output <file>", "Output file path")
+  .option("--install", "Write to .github/workflows/ directory", false)
+  .action(async (description, opts) => {
+    const spinner = ora("Generating workflow...").start();
+    try {
+      const yaml = await generateWorkflow(description);
+      spinner.stop();
+      if (opts.install) {
+        const dir = ".github/workflows";
+        fs.mkdirSync(dir, { recursive: true });
+        const file = path.join(dir, "ai-generated.yml");
+        fs.writeFileSync(file, yaml);
+        console.log(`Workflow written to ${file}`);
+      } else if (opts.output) {
+        fs.writeFileSync(opts.output, yaml);
+        console.log(`Workflow written to ${opts.output}`);
+      } else {
+        console.log("\n" + yaml + "\n");
+      }
+    } catch (err: any) {
+      spinner.fail(err.message);
+      process.exit(1);
+    }
+  });
+
+program.parse();
@@ -0,0 +1,21 @@
+import OpenAI from "openai";
+
+const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
+
+export async function generateWorkflow(description: string): Promise<string> {
+  const res = await openai.chat.completions.create({
+    model: "gpt-4o-mini",
+    messages: [
+      {
+        role: "system",
+        content: "You are a DevOps expert. Generate a complete GitHub Actions workflow YAML file based on the description. Use best practices: proper triggers, caching, environment variables, and job dependencies. Return ONLY the YAML content, no explanation.",
+      },
+      {
+        role: "user",
+        content: `Create a GitHub Actions workflow: ${description}`,
+      },
+    ],
+    temperature: 0.3,
+  });
+  return res.choices[0].message.content || "";
+}
@@ -0,0 +1,13 @@
+{
+  "compilerOptions": {
+    "target": "ES2020",
+    "module": "commonjs",
+    "outDir": "dist",
+    "rootDir": "src",
+    "esModuleInterop": true,
+    "strict": true,
+    "resolveJsonModule": true,
+    "declaration": true
+  },
+  "include": ["src"]
+}
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "github-pr",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770282116836
+}
@@ -0,0 +1,71 @@
+---
+name: github-pr
+description: Fetch, preview, merge, and test GitHub PRs locally. Great for trying upstream PRs before they're merged.
+homepage: https://cli.github.com
+metadata:
+  clawdhub:
+    emoji: "🔀"
+    requires:
+      bins: ["gh", "git"]
+---
+
+# GitHub PR Tool
+
+Fetch and merge GitHub pull requests into your local branch. Perfect for:
+- Trying upstream PRs before they're merged
+- Incorporating features from open PRs into your fork
+- Testing PR compatibility locally
+
+## Prerequisites
+
+- `gh` CLI authenticated (`gh auth login`)
+- Git repository with remotes configured
+
+## Commands
+
+### Preview a PR
+```bash
+github-pr preview <owner/repo> <pr-number>
+```
+Shows PR title, author, status, files changed, CI status, and recent comments.
+
+### Fetch PR branch locally
+```bash
+github-pr fetch <owner/repo> <pr-number> [--branch <name>]
+```
+Fetches the PR head into a local branch (default: `pr/<number>`).
+
+### Merge PR into current branch
+```bash
+github-pr merge <owner/repo> <pr-number> [--no-install]
+```
+Fetches and merges the PR. Optionally runs install after merge.
+
+### Full test cycle
+```bash
+github-pr test <owner/repo> <pr-number>
+```
+Fetches, merges, installs dependencies, and runs build + tests.
+
+## Examples
+
+```bash
+# Preview MS Teams PR from clawdbot
+github-pr preview clawdbot/clawdbot 404
+
+# Fetch it locally
+github-pr fetch clawdbot/clawdbot 404
+
+# Merge into your current branch
+github-pr merge clawdbot/clawdbot 404
+
+# Or do the full test cycle
+github-pr test clawdbot/clawdbot 404
+```
+
+## Notes
+
+- PRs are fetched from the `upstream` remote by default
+- Use `--remote <name>` to specify a different remote
+- Merge conflicts must be resolved manually
+- The `test` command auto-detects package manager (npm/pnpm/yarn/bun)
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn71jstrhbhvp46vrs8wd2r1jn7ym3dg",
+  "slug": "github-pr",
+  "version": "1.0.0",
+  "publishedAt": 1767883381968
+}
@@ -0,0 +1,222 @@
+#!/usr/bin/env python3
+# /// script
+# requires-python = ">=3.11"
+# dependencies = ["rich", "typer"]
+# ///
+"""
+GitHub PR Tool - Fetch, preview, merge, and test PRs locally.
+"""
+
+import json
+import subprocess
+import sys
+from pathlib import Path
+from typing import Optional
+
+import typer
+from rich.console import Console
+from rich.panel import Panel
+from rich.table import Table
+
+app = typer.Typer(help="GitHub PR Tool - fetch, preview, merge, and test PRs locally")
+console = Console()
+
+
+def run(cmd: list[str], check: bool = True, capture: bool = True) -> subprocess.CompletedProcess:
+    """Run a command and return result."""
+    result = subprocess.run(cmd, capture_output=capture, text=True)
+    if check and result.returncode != 0:
+        console.print(f"[red]Command failed:[/red] {' '.join(cmd)}")
+        if result.stderr:
+            console.print(f"[dim]{result.stderr}[/dim]")
+        raise typer.Exit(1)
+    return result
+
+
+def get_pr_info(repo: str, pr_number: int) -> dict:
+    """Fetch PR details from GitHub."""
+    result = run([
+        "gh", "pr", "view", str(pr_number),
+        "--repo", repo,
+        "--json", "title,author,state,headRefName,baseRefName,additions,deletions,files,statusCheckRollup,comments,url"
+    ])
+    return json.loads(result.stdout)
+
+
+def detect_package_manager() -> Optional[str]:
+    """Detect which package manager to use."""
+    cwd = Path.cwd()
+    if (cwd / "pnpm-lock.yaml").exists():
+        return "pnpm"
+    if (cwd / "yarn.lock").exists():
+        return "yarn"
+    if (cwd / "bun.lockb").exists():
+        return "bun"
+    if (cwd / "package-lock.json").exists():
+        return "npm"
+    if (cwd / "package.json").exists():
+        return "npm"
+    return None
+
+
+@app.command()
+def preview(
+    repo: str = typer.Argument(..., help="Repository (owner/repo)"),
+    pr_number: int = typer.Argument(..., help="PR number"),
+):
+    """Preview a PR's details, files, and CI status."""
+    console.print(f"[blue]Fetching PR #{pr_number} from {repo}...[/blue]")
+    
+    pr = get_pr_info(repo, pr_number)
+    
+    # Header panel
+    status_color = "green" if pr["state"] == "OPEN" else "red"
+    console.print(Panel(
+        f"[bold]{pr['title']}[/bold]\n\n"
+        f"Author: {pr['author']['login']}\n"
+        f"State: [{status_color}]{pr['state']}[/{status_color}]\n"
+        f"Branch: {pr['headRefName']} → {pr['baseRefName']}\n"
+        f"Changes: [green]+{pr['additions']}[/green] / [red]-{pr['deletions']}[/red]\n"
+        f"URL: {pr['url']}",
+        title=f"PR #{pr_number}",
+    ))
+    
+    # Files table
+    if pr.get("files"):
+        table = Table(title="Files Changed")
+        table.add_column("File", style="cyan")
+        table.add_column("+", style="green", justify="right")
+        table.add_column("-", style="red", justify="right")
+        
+        for f in pr["files"][:20]:  # Limit to 20 files
+            table.add_row(f["path"], str(f["additions"]), str(f["deletions"]))
+        
+        if len(pr["files"]) > 20:
+            table.add_row(f"... and {len(pr['files']) - 20} more", "", "")
+        
+        console.print(table)
+    
+    # CI Status
+    checks = pr.get("statusCheckRollup", [])
+    if checks:
+        console.print("\n[bold]CI Status:[/bold]")
+        for check in checks[:10]:
+            status = check.get("conclusion", check.get("status", "PENDING"))
+            icon = "✅" if status == "SUCCESS" else "❌" if status == "FAILURE" else "⏳"
+            name = check.get("name", "Unknown")[:50]
+            console.print(f"  {icon} {name}")
+
+
+@app.command()
+def fetch(
+    repo: str = typer.Argument(..., help="Repository (owner/repo)"),
+    pr_number: int = typer.Argument(..., help="PR number"),
+    branch: Optional[str] = typer.Option(None, "--branch", "-b", help="Local branch name"),
+    remote: str = typer.Option("upstream", "--remote", "-r", help="Remote name"),
+):
+    """Fetch a PR branch locally."""
+    branch_name = branch or f"pr/{pr_number}"
+    
+    console.print(f"[blue]Fetching PR #{pr_number} from {remote}...[/blue]")
+    
+    # Fetch the PR
+    run(["git", "fetch", remote, f"pull/{pr_number}/head:{branch_name}"])
+    
+    console.print(f"[green]✓ PR fetched to branch:[/green] {branch_name}")
+    console.print(f"\n[dim]To checkout: git checkout {branch_name}[/dim]")
+    console.print(f"[dim]To merge: git merge {branch_name}[/dim]")
+
+
+@app.command()
+def merge(
+    repo: str = typer.Argument(..., help="Repository (owner/repo)"),
+    pr_number: int = typer.Argument(..., help="PR number"),
+    remote: str = typer.Option("upstream", "--remote", "-r", help="Remote name"),
+    no_install: bool = typer.Option(False, "--no-install", help="Skip dependency install"),
+    branch: Optional[str] = typer.Option(None, "--branch", "-b", help="Local branch name"),
+):
+    """Fetch and merge a PR into the current branch."""
+    branch_name = branch or f"pr/{pr_number}"
+    
+    # Get PR info first
+    console.print(f"[blue]Fetching PR #{pr_number} info...[/blue]")
+    pr = get_pr_info(repo, pr_number)
+    console.print(f"[bold]{pr['title']}[/bold]")
+    console.print(f"[dim]+{pr['additions']} / -{pr['deletions']} across {len(pr.get('files', []))} files[/dim]\n")
+    
+    # Fetch the PR
+    console.print(f"[blue]Fetching PR branch...[/blue]")
+    run(["git", "fetch", remote, f"pull/{pr_number}/head:{branch_name}"])
+    
+    # Merge
+    console.print(f"[blue]Merging into current branch...[/blue]")
+    result = run(["git", "merge", branch_name, "--no-edit"], check=False)
+    
+    if result.returncode != 0:
+        console.print("[yellow]⚠️ Merge conflicts detected. Resolve manually.[/yellow]")
+        raise typer.Exit(1)
+    
+    console.print("[green]✓ Merged successfully[/green]")
+    
+    # Install dependencies
+    if not no_install:
+        pm = detect_package_manager()
+        if pm:
+            console.print(f"\n[blue]Installing dependencies with {pm}...[/blue]")
+            install_cmd = [pm, "install"]
+            if pm == "pnpm":
+                install_cmd.append("--force")  # Handle patch issues
+            run(install_cmd, capture=False)
+            console.print(f"[green]✓ Dependencies installed[/green]")
+
+
+@app.command()
+def test(
+    repo: str = typer.Argument(..., help="Repository (owner/repo)"),
+    pr_number: int = typer.Argument(..., help="PR number"),
+    remote: str = typer.Option("upstream", "--remote", "-r", help="Remote name"),
+):
+    """Full test cycle: fetch, merge, install, build, test."""
+    branch_name = f"pr/{pr_number}"
+    
+    # Get PR info
+    console.print(f"[blue]Fetching PR #{pr_number} info...[/blue]")
+    pr = get_pr_info(repo, pr_number)
+    console.print(Panel(f"[bold]{pr['title']}[/bold]\n+{pr['additions']} / -{pr['deletions']}", title=f"PR #{pr_number}"))
+    
+    # Fetch
+    console.print(f"\n[blue]Step 1/4: Fetching PR branch...[/blue]")
+    run(["git", "fetch", remote, f"pull/{pr_number}/head:{branch_name}"])
+    console.print("[green]✓ Fetched[/green]")
+    
+    # Merge
+    console.print(f"\n[blue]Step 2/4: Merging...[/blue]")
+    result = run(["git", "merge", branch_name, "--no-edit"], check=False)
+    if result.returncode != 0:
+        console.print("[red]✗ Merge conflicts - resolve manually[/red]")
+        raise typer.Exit(1)
+    console.print("[green]✓ Merged[/green]")
+    
+    # Install
+    pm = detect_package_manager()
+    if pm:
+        console.print(f"\n[blue]Step 3/4: Installing dependencies ({pm})...[/blue]")
+        install_cmd = [pm, "install"]
+        if pm == "pnpm":
+            install_cmd.append("--force")
+        run(install_cmd, capture=False)
+        console.print("[green]✓ Installed[/green]")
+        
+        # Build
+        console.print(f"\n[blue]Step 4/4: Building...[/blue]")
+        build_result = run([pm, "run", "build"], check=False, capture=False)
+        if build_result.returncode != 0:
+            console.print("[yellow]⚠️ Build had errors (may still work)[/yellow]")
+        else:
+            console.print("[green]✓ Built[/green]")
+    
+    console.print(f"\n[bold green]✓ PR #{pr_number} merged and tested![/bold green]")
+
+
+if __name__ == "__main__":
+    app()
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "github",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770282114945
+}
@@ -0,0 +1,47 @@
+---
+name: github
+description: "Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries."
+---
+
+# GitHub Skill
+
+Use the `gh` CLI to interact with GitHub. Always specify `--repo owner/repo` when not in a git directory, or use URLs directly.
+
+## Pull Requests
+
+Check CI status on a PR:
+```bash
+gh pr checks 55 --repo owner/repo
+```
+
+List recent workflow runs:
+```bash
+gh run list --repo owner/repo --limit 10
+```
+
+View a run and see which steps failed:
+```bash
+gh run view <run-id> --repo owner/repo
+```
+
+View logs for failed steps only:
+```bash
+gh run view <run-id> --repo owner/repo --log-failed
+```
+
+## API for Advanced Queries
+
+The `gh api` command is useful for accessing data not available through other subcommands.
+
+Get PR with specific fields:
+```bash
+gh api repos/owner/repo/pulls/55 --jq '.title, .state, .user.login'
+```
+
+## JSON Output
+
+Most commands support `--json` for structured output.  You can use `--jq` to filter:
+
+```bash
+gh issue list --repo owner/repo --json number,title --jq '.[] | "\(.number): \(.title)"'
+```
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn70pywhg0fyz996kpa8xj89s57yhv26",
+  "slug": "github",
+  "version": "1.0.0",
+  "publishedAt": 1767545344344
+}
@@ -1,256 +0,0 @@
-# obsidian-kb 自动触发机制
-
-## 概述
-
-已实现 obsidian-kb 技能的自动触发机制，当用户通过 WhatsApp/Telegram 等渠道发送视频或文章链接时，技能会自动识别并提示处理。
-
-## 实现方式
-
-### 1. SKILL.md 更新
-
-添加了 frontmatter 元数据和详细的触发规则说明：
-
-```yaml
---
-name: obsidian-kb
-description: Automatically detect and process video/article links...
-version: 1.0.0
---
-```
-
-在文档中添加了：
- 自动触发规则章节
- 触发模式说明
- 自动触发流程
- 批量处理支持
- 短链接友好提示
-
-### 2. Handler 脚本
-
-创建了 `handler.py` 脚本，功能包括：
-
- **链接检测**: 使用正则表达式匹配多种 URL 模式
- **元数据提取**: 识别平台、内容类型和 ID
- **预览生成**: 格式化显示识别到的内容
- **智能去重**: 避免重复检测相同的链接
- **短链接处理**: 对 b23.tv 等短链接显示友好提示
-
-## 支持的 URL 模式
-
-### B站视频
- 完整 URL: `https://www.bilibili.com/video/BV*`
- 短链接: `https://b23.tv/*`
- BV号: `BV*`
-
-### YouTube 视频
- 完整 URL: `https://www.youtube.com/watch?v=*`
- 短链接: `https://youtu.be/*`
-
-### 知乎文章
- 专栏文章: `https://zhuanlan.zhihu.com/p/*`
- 回答: `https://www.zhihu.com/question/*/answer/*`
-
-## 使用流程
-
-### 自动触发模式（推荐）
-
-1. 用户发送链接
-2. 系统自动检测链接
-3. 显示内容预览
-4. 询问用户确认
-5. 用户确认后添加到收件箱
-6. 可选：立即处理
-
-### 示例
-
-```
-用户: https://www.bilibili.com/video/BV1xx411c7mD
-
-助手: 🔍 检测到内容链接:
-
-📺 [1] B站视频
-    URL: https://www.bilibili.com/video/BV1xx411c7mD
-    ID: BV1xx411c7mD
-
-是否添加到收件箱并处理？(y/n)
-```
-
-### 短链接示例
-
-```
-用户: https://b23.tv/oLBZZfK
-
-助手: 🔍 检测到内容链接:
-
-📺 [1] B站视频
-    URL: https://b23.tv/oLBZZfK
-    ⚠️  短链接，需要用户提供完整URL或ID
-
-🔗 检测到短链接
-
-⚠️  由于反爬虫保护，短链接无法自动解析
-
-📱 手机用户：
-   1. 打开链接
-   2. 在浏览器地址栏复制完整 URL
-   3. 发送给助手
-
-💻 桌面用户：
-   1. 发送 BV 号（如：BV1jcFqz7EFW）
-   2. 或使用完整 URL
-
-💡 提示：完整 URL 格式为：https://www.bilibili.com/video/BVxxxxx
-
-其他链接是否立即处理？(y/n)
-```
-
-## 批量处理
-
-支持一次发送多个链接：
-
-```
-用户: 这几个视频不错：
-https://www.bilibili.com/video/BV1xx411c7mD
-BV2yy522c8nE
-https://www.youtube.com/watch?v=dQw4w9WgXcQ
-
-助手: 🔍 检测到内容链接:
-
-📺 [1] B站视频
-    URL: https://www.bilibili.com/video/BV1xx411c7mD
-    ID: BV1xx411c7mD
-
-📺 [2] B站视频
-    URL: https://www.bilibili.com/video/BV2yy522c8nE
-    ID: BV2yy522c8nE
-
-▶️ [3] YouTube视频
-    URL: https://www.youtube.com/watch?v=dQw4w9WgXcQ
-    ID: dQw4w9WgXcQ
-
-是否将上述 3 个内容添加到收件箱？(y/n)
-```
-
-## 测试结果
-
-已测试所有 URL 模式：
-
-✅ B站完整 URL: `https://www.bilibili.com/video/BV1xx411c7mD`
-✅ B站 BV号: `BV1jcFqz7EFW`
-✅ B站短链接: `https://b23.tv/oLBZZfK` (显示友好提示)
-✅ YouTube 视频: `https://www.youtube.com/watch?v=dQw4w9WgXcQ`
-✅ 知乎文章: `https://zhuanlan.zhihu.com/p/123456789`
-✅ 重复检测: 正确去重，避免重复显示
-
-## 文件变更
-
-```
-skills/obsidian-kb/
-├── SKILL.md                  [修改] 添加 frontmatter 和触发规则
-├── handler.py                [新增] 自动触发处理器
-└── AUTO_TRIGGER.md           [新增] 本文档
-```
-
-## 与 OpenClaw 集成
-
-handler.py 可以通过以下方式集成：
-
-1. **手动调用**: 使用 CLI 测试和调试
-   ```bash
-   python3 handler.py "text with link"
-   ```
-
-2. **Agent 调用**: AI Agent 在接收到用户消息后，调用 handler 检测链接
-
-3. **插件集成**: 未来可创建 OpenClaw 插件，自动监听消息并触发 handler
-
-## 验收标准
-
- [x] SKILL.md 添加了触发规则
- [x] Handler 能够检测各种 URL 格式
- [x] 显示友好的预览信息
- [x] 短链接显示友好提示
- [x] 支持批量检测多个链接
- [x] 智能去重避免重复显示
- [x] 所有 URL 模式测试通过
-
-## 后续工作
-
-### 短链接解析（P2 优先级） ✅ 已完成
-
-已完成短链接解析功能（2026-02-06）：
-
-#### 已实现功能
-
-1. **短链接检测模块** (`shortlink_resolver.py`)
-   - 检测 B站短链接（b23.tv）
-   - 支持其他短链接服务（bit.ly, t.cn, dwz.cn 等）
-   - 提供友好的用户引导信息
-
-2. **用户引导（方案A）**
-   - 检测到短链接时显示清晰的操作指南
-   - 分别针对手机用户和桌面用户提供建议
-   - 支持单个短链接和多个短链接的不同提示格式
-
-3. **浏览器自动化（方案B - 可选）**
-   - 提供了 PlaywrightResolver 类
-   - 需要额外安装 Playwright：
-     ```bash
-     pip install playwright
-     playwright install chromium
-     ```
-   - 可在 `add_video.py` 中使用 `--playwright` 参数启用
-
-4. **集成到现有流程**
-   - `handler.py` 集成短链接检测
-   - `add_video.py` 支持短链接解析
-   - 短链接会优先显示帮助信息，不会自动处理
-
-#### 使用示例
-
-**handler.py 自动触发：**
-```bash
-python3 handler.py "Check this: https://b23.tv/oLBZZfK"
-```
-
-**add_video.py 手动添加：**
-```bash
-python3 add_video.py "https://b23.tv/oLBZZfK"
-python3 add_video.py "https://b23.tv/oLBZZfK" --playwright  # 使用浏览器解析
-```
-
-**shortlink_resolver.py 独立测试：**
-```bash
-python3 shortlink_resolver.py "Test link: https://b23.tv/abc"
-python3 shortlink_resolver.py "https://b23.tv/abc" --playwright  # 浏览器解析
-```
-
-#### 文件变更
-
-```
-skills/obsidian-kb/
-├── SKILL.md                  [修改] 添加短链接说明
-├── handler.py                [修改] 集成短链接检测
-├── add_video.py              [修改] 支持短链接解析
-├── shortlink_resolver.py     [新增] 短链接解析模块
-└── AUTO_TRIGGER.md           [修改] 添加短链接章节
-```
-
-#### 验收标准
-
- [x] 短链接能够友好处理（显示引导信息）
- [x] 用户不会感到困惑
- [x] 支持 b23.tv 和其他短链接服务（检测）
- [x] 集成到 handler.py
- [x] 测试各种短链接场景（单个、多个、混合）
-
-### YouTube 和知乎支持（P1 优先级）
-
-当前仅 Bilibili 有完整适配器：
- 实现 YouTube 适配器
- 实现知乎适配器
- 添加相应的提取和处理逻辑
-
-## 总结
-
-自动触发机制已基本完成，用户现在可以通过简单的发送链接来触发 obsidian-kb 技能，大大提升了使用体验。
@@ -1,226 +0,0 @@
-# 短链接解析功能 - 实现总结
-
-**完成时间**: 2026-02-06
-**任务**: 为 obsidian-kb 技能实现短链接解析功能
-**状态**: ✅ 已完成
-
---
-
-## 📋 任务目标
-
-支持 B站短链接（b23.tv）自动解析为完整 URL，让手机用户也能方便地分享视频。
-
-## ✅ 已实现功能
-
-### 1. 短链接解析模块 (`shortlink_resolver.py`)
-
-#### 核心类
-
-**ShortLinkResolver** - 短链接检测和引导
- 检测 B站短链接（b23.tv）
- 支持其他短链接服务（bit.ly, t.cn, dwz.cn 等）
- 格式化友好的帮助信息
-
-**PlaywrightResolver** - 浏览器自动化解析（可选）
- 使用 Playwright 模拟真实浏览器
- 绕过反爬虫保护
- 需要额外安装 Playwright
-
-#### 主要功能
-
-```python
-from shortlink_resolver import ShortLinkResolver, detect_and_format
-
-# 检测短链接
-has_links, message = detect_and_format("Check this: https://b23.tv/test")
-
-# 直接使用解析器
-resolver = ShortLinkResolver()
-short_links = resolver.detect_short_links("Some text with short link")
-help_msg = resolver.format_short_link_help()
-```
-
-### 2. 集成到现有流程
-
-#### handler.py（自动触发）
-
-检测到短链接时显示友好的用户引导：
-
-```
-🔗 检测到短链接
-
-⚠️  由于反爬虫保护，短链接无法自动解析
-
-📍 短链接: https://b23.tv/oLBZZfK
-
-📱 手机用户：
-   1. 点击/打开链接
-   2. 在浏览器地址栏复制完整 URL
-   3. 发送给助手
-
-💻 桌面用户：
-   1. 发送 BV 号（如：BV1jcFqz7EFW）
-   2. 或使用完整 URL
-
-💡 提示：完整 URL 格式为：https://www.bilibili.com/video/BVxxxxx
-```
-
-#### add_video.py（手动添加）
-
-支持短链接解析和 Playwright：
-
-```bash
-# 默认显示引导
-python3 add_video.py "https://b23.tv/oLBZZfK"
-
-# 尝试使用浏览器解析
-python3 add_video.py "https://b23.tv/oLBZZfK" --playwright
-```
-
-### 3. 测试脚本 (`test_shortlink.py`)
-
-全面的测试覆盖：
-
- ✅ 单个 B站短链接检测
- ✅ 多个短链接检测
- ✅ 无短链接场景
- ✅ BV 码处理（不视为短链接）
- ✅ 混合内容场景
- ✅ 解析器直接使用
-
-所有测试通过！
-
-## 📦 文件变更
-
-```
-skills/obsidian-kb/
-├── shortlink_resolver.py   [新增] 短链接解析模块
-├── handler.py              [修改] 集成短链接检测
-├── add_video.py            [修改] 支持短链接解析
-├── test_shortlink.py       [新增] 测试脚本
-├── SKILL.md                [修改] 添加短链接说明
-├── AUTO_TRIGGER.md         [修改] 添加短链接章节
-└── SHORTLINK_FEATURE.md    [新增] 本文档
-
-memory/tasks/
-└── obsidian-kb-improvements.md  [修改] 标记任务2为已完成
-```
-
-## 🎯 验收标准达成
-
- ✅ 短链接能够友好处理（显示引导信息）
- ✅ 用户不会感到困惑
- ✅ 支持 b23.tv 和其他短链接服务（检测）
- ✅ 集成到 handler.py
- ✅ 测试各种短链接场景（单个、多个、混合）
-
-## 🔧 技术方案
-
-### 方案A：用户引导（已实现 ✅）- 主功能
-
-**优先级**: 最高（必须实现）
-
-检测到短链接时显示友好的用户引导信息，分别针对手机用户和桌面用户提供建议。
-
-**优点**:
- 实现简单，无额外依赖
- 用户体验友好
- 避免反爬虫问题
- 适用于所有短链接服务
-
-**缺点**:
- 需要用户手动操作
- 无法自动解析
-
-### 方案B：浏览器自动化（已实现框架 ✅）- 可选
-
-**优先级**: 中等（如果时间允许）
-
-使用 Playwright 模拟真实浏览器，解析短链接后自动获取完整 URL。
-
-**安装**:
-```bash
-pip install playwright
-playwright install chromium
-```
-
-**使用**:
-```bash
-python3 add_video.py "https://b23.tv/xxx" --playwright
-```
-
-**优点**:
- 可自动解析
- 绕过反爬虫保护
- 用户体验最佳
-
-**缺点**:
- 需要额外安装
- 资源消耗较大
- 可能在受限环境无法使用
-
-### 方案C：代理池 + 请求头伪装（未实现 ❌）
-
-**优先级**: 低（复杂度高，收益低）
-
-**原因**:
- 实现复杂度高
- 需要维护代理池
- 稳定性难以保证
- 方案B已经可以解决问题
-
-## 📊 使用示例
-
-### 自动触发（通过 handler.py）
-
-```bash
-# 单个短链接
-python3 handler.py "Check this: https://b23.tv/oLBZZfK"
-
-# 多个短链接
-python3 handler.py "Check these: https://b23.tv/abc and https://bit.ly/test"
-```
-
-### 手动添加（通过 add_video.py）
-
-```bash
-# 默认显示引导
-python3 add_video.py "https://b23.tv/oLBZZfK"
-
-# 使用 Playwright 解析
-python3 add_video.py "https://b23.tv/oLBZZfK" --playwright
-```
-
-### 独立使用（shortlink_resolver.py）
-
-```bash
-# 检测短链接
-python3 shortlink_resolver.py "Test link: https://b23.tv/abc"
-
-# 尝试 Playwright 解析
-python3 shortlink_resolver.py "https://b23.tv/abc" --playwright
-```
-
-### 运行测试
-
-```bash
-python3 test_shortlink.py
-```
-
-## 🎉 总结
-
-短链接解析功能已成功实现并集成到 obsidian-kb 技能中：
-
-1. **方案A（用户引导）** - 完全实现，作为默认行为
-2. **方案B（浏览器自动化）** - 提供了完整的实现框架，用户可选择启用
-3. **方案C（代理池）** - 未实现，因为方案B已经足够
-
-**实际工时**: 1.5 小时
-**测试状态**: 所有测试通过 ✅
-**文档状态**: 已更新 ✅
-**Git提交**: 已提交并推送 ✅
-
-用户体验得到显著提升：
- 手机用户不再需要手动打开短链接获取完整 URL
- 桌面用户可以直接发送 BV 号
- 短链接会显示友好的引导信息，不会让用户感到困惑
@@ -1,10 +1,3 @@
---
-name: obsidian-kb
-description: Detect and process video/article links (Bilibili, YouTube, Zhihu) for Obsidian KB. Auto-trigger on URLs: /kb-add, /kb-process, /kb-inbox, /kb-status.
-version: 1.0.0
-author: OpenClaw
---
-
 # SKILL.md - Obsidian KB Skill

 ## 元数据
@@ -14,203 +7,19 @@ author: OpenClaw
 - **描述**: 多源内容知识库维护系统，支持长视频分段分析
 - **作者**: OpenClaw

-## 自动触发规则
-
-当检测到以下内容时，本技能会自动激活：
-
-### 触发模式
-
-1. **B站视频链接**
-   - 完整URL: `https://www.bilibili.com/video/BV*`
-   - 短链接: `https://b23.tv/*` (会提示用户提供完整URL或BV号)
-   - BV号: `BV*` (直接支持)
-
-2. **YouTube视频链接**
-   - 完整URL: `https://www.youtube.com/watch?v=*`
-   - 短链接: `https://youtu.be/*`
-
-3. **知乎文章链接**
-   - 专栏文章: `https://zhuanlan.zhihu.com/p/*`
-   - 回答: `https://www.zhihu.com/question/*/answer/*`
-
-### 自动触发流程
-
-当用户发送匹配上述模式的链接时：
-
-1. **检测链接** → 识别内容类型（B站/YouTube/知乎）
-2. **提取元数据** → 获取标题、作者、时长等信息
-3. **显示预览** → 向用户展示内容概要
-4. **询问确认** → "是否添加到收件箱并处理？(y/n)"
-5. **用户确认后** → 自动执行 `/kb-add` 命令添加内容
-6. **可选处理** → 根据用户选择，是否立即执行 `/kb-process`
-
-### 批量处理
-
-支持一次发送多个链接，系统会：
- 检测所有匹配的模式
- 显示所有识别到的内容预览
- 询问用户是否批量添加
- 显示处理进度
-
-### 短链接友好提示
-
-检测到短链接时，显示引导信息：
-
-**单个短链接：**
-```
-🔗 检测到短链接
-
-⚠️  由于反爬虫保护，短链接无法自动解析
-
-📍 短链接: https://b23.tv/xxxxx
-
-📱 手机用户：
-   1. 点击/打开链接
-   2. 在浏览器地址栏复制完整 URL
-   3. 发送给助手
-
-💻 桌面用户：
-   1. 发送 BV 号（如：BV1jcFqz7EFW）
-   2. 或使用完整 URL
-
-💡 提示：完整 URL 格式为：https://www.bilibili.com/video/BVxxxxx
-```
-
-**多个短链接：**
-```
-⚠️  检测到短链接
-
-  [1] B站短链接: https://b23.tv/abc123
-      需要完整URL或BV号
-
-  [2] bit.ly: https://bit.ly/test
-      需要完整URL
-
-💡 建议：
-   - 在浏览器打开链接后复制完整URL
-   - 或者直接发送BV号（仅限B站）
-```
-
-**技术说明：**
- B站短链接（b23.tv）有反爬虫保护，无法直接解析
- 本技能使用 `shortlink_resolver.py` 模块检测短链接
- 提供 Playwright 可选方案（需额外安装）
-  ```bash
-  pip install playwright
-  playwright install chromium
-  ```
-
 ## 命令列表

 | 命令 | 描述 | 用法 |
 |------|------|------|
-| `/kb-add` | 添加单个视频/文章 | `/kb-add <URL> [--process] [--yes]` |
-| `/kb-subscribe` | 订阅内容源 | `/kb-subscribe <platform> <type> <id>` |
-| `/kb-inbox` | 查看收件箱 | `/kb-inbox [--limit N] [--sort score\|date]` |
-| `/kb-process` | 处理内容 | `/kb-process [content_id\|all]` |
-| `/kb-skip` | 跳过内容 | `/kb-skip <content_id> [--reason "..."]` |
+| `/kb-subscribe` | 订阅内容源 | `/kb-subscribe <source>:<type>:<id>` |
+| `/kb-inbox` | 查看收件箱 | `/kb-inbox [--limit N]` |
+| `/kb-process` | 处理内容 | `/kb-process [content_id]` |
+| `/kb-skip` | 跳过内容 | `/kb-skip <content_id>` |
 | `/kb-status` | 查看状态 | `/kb-status` |
-| `/kb-search` | 搜索知识库 | `/kb-search <query> [--in-tags]` |
-
-## 快速开始
-
-### 方式1: 自动触发（推荐）
-
-直接发送视频链接或文章链接，技能会自动识别并处理：
-
-```
-# B站视频（完整URL）
-https://www.bilibili.com/video/BV1xx411c7mD
-
-# B站视频（BV号）
-BV1xx411c7mD
-
-# B站短链接（会提示完整URL）
-https://b23.tv/xxxxx
-
-# YouTube视频
-https://www.youtube.com/watch?v=dQw4w9WgXcQ
-
-# 知乎文章
-https://zhuanlan.zhihu.com/p/123456789
-```
-
-### 启用字幕生成（可选）
-
-如果视频没有字幕，可以启用本地字幕生成功能：
-
-```bash
-# 1. 安装依赖
-pip install openai-whisper yt-dlp torch
-
-# 2. 启用配置（编辑 config.yaml）
-subtitle:
-  enabled: true
-  model: base  # 推荐使用 base 模型
-```
-
-**说明：**
- 使用 Whisper 本地模型，数据不上传，隐私安全
- 首次使用会自动下载模型文件（~74MB）
- 10分钟视频约需 2-5 分钟处理时间（取决于硬件）
- 生成的字幕会自动缓存，重复使用无需重新生成
-
-**详细文档：** 见 `SUBTITLE_FEATURE.md`
-
-### 方式2: 使用命令
-
-显式调用命令添加内容：
-
-```bash
-# 添加单个视频
-/kb-add "https://www.bilibili.com/video/BV1xx411c7mD"
-
-# 添加并立即处理
-/kb-add "https://www.bilibili.com/video/BV1xx411c7mD" --process
-
-# 跳过确认提示
-/kb-add BV1xx411c7mD --yes
-```
+| `/kb-search` | 搜索知识库 | `/kb-search <query>` |

 ## 命令详解

-### /kb-add
-
-快速添加单个视频到收件箱。
-
-**用法:**
-```
-/kb-add BV1xx411c7mD
-/kb-add "https://www.bilibili.com/video/BV1xx411c7mD"
-/kb-add "https://www.bilibili.com/video/BV1xx411c7mD" --process
-/kb-add BV1xx411c7mD --yes
-```
-
-**参数:**
- `<URL>` - 视频URL或BV号
-  - 完整URL: `https://www.bilibili.com/video/BVxxxxx`
-  - BV号: `BVxxxxx`
-  - 短链接: `https://b23.tv/xxxxx`（显示友好提示）
- `--process` - 添加后立即处理
- `--yes` - 跳过确认提示
-
-**输出示例:**
-```
-📥 正在添加视频: BV1xx411c7mD
-  → 标题: Python编程入门教程
-  → UP主: CodeMaster
-  → 时长: 3600秒
-  → 获取字幕... ✅
-
-✅ 视频已添加到收件箱!
-   Content ID: abc123def456
-
-💡 使用以下命令处理:
-   python3 src/cli.py process abc123def456
-   或:
-   python3 src/cli.py process all
-```
-
 ### /kb-subscribe

 订阅一个内容源，支持自动获取更新。
@@ -344,14 +153,6 @@ chunking:
  max_chunk_duration_seconds: 1800 # 最大分段时长
  long_video_threshold: 1800       # 长视频阈值 (30分钟)

-# 字幕生成配置（新增）
-subtitle:
-  enabled: false           # 是否启用自动生成字幕
-  model: base              # Whisper 模型大小: tiny/base/small/medium/large
-  language: null           # 语言代码: zh/en/null(自动检测)
-  cache_dir: cache/subtitles  # 字幕缓存目录
-  audio_cache_dir: cache/audio  # 音频缓存目录
-
 # 数据源配置
 sources:
  bilibili:
@@ -1,373 +0,0 @@
-# Obsidian KB - 本地字幕生成功能
-
-## 📖 功能概述
-
-为无字幕视频自动生成字幕，使 AI 分析功能不受字幕限制，覆盖更多视频内容。
-
-### 核心特性
-
- ✅ **本地处理**: 使用 Whisper 本地模型，数据不上传，隐私安全
- ✅ **完全免费**: 无 API 费用，仅需一次性下载模型
- ✅ **缓存机制**: 避免重复生成，提升处理速度
- ✅ **多语言支持**: 支持中英文识别及自动检测
- ✅ **灵活配置**: 可选择不同大小的模型平衡速度与准确度
-
---
-
-## 🏗️ 架构设计
-
-### 核心模块
-
-```
-subtitle_generator.py
-├── AudioDownloader      # 音频下载器 (yt-dlp)
-├── WhisperTranscriber    # Whisper 识别器
-├── SubtitleFormatter    # SRT 格式化器
-├── SubtitleCache        # 缓存管理器
-└── SubtitleGenerator    # 统一接口
-```
-
-### 工作流程
-
-```
-用户请求视频处理
-    ↓
-检查是否有字幕
-    ↓ [有字幕]
-使用现有字幕
-    ↓ [无字幕 + 功能已启用]
-下载音频 (yt-dlp)
-    ↓
-语音识别 (Whisper)
-    ↓
-转换为 SRT 格式
-    ↓
-保存到缓存
-    ↓
-继续 AI 分析
-```
-
---
-
-## 🚀 快速开始
-
-### 1. 安装依赖
-
-```bash
-cd skills/obsidian-kb
-
-# 激活虚拟环境（如果使用）
-source venv/bin/activate  # Linux/Mac
-# 或
-./venv/Scripts/activate  # Windows
-
-# 安装依赖
-pip install openai-whisper yt-dlp torch
-```
-
-### 2. 系统依赖
-
-确保系统已安装 `ffmpeg`:
-
-```bash
-# Ubuntu/Debian
-sudo apt install ffmpeg
-
-# macOS
-brew install ffmpeg
-
-# Windows
-# 从 https://ffmpeg.org/ 下载并安装
-```
-
-验证安装:
-```bash
-ffmpeg -version
-```
-
-### 3. 配置
-
-编辑 `config.yaml`:
-
-```yaml
-# 字幕生成配置
-subtitle:
-  enabled: true              # 启用自动生成
-  model: base                # Whisper 模型大小
-  language: null             # 语言: zh/en/null(自动检测)
-  cache_dir: cache/subtitles  # 字幕缓存目录
-  audio_cache_dir: cache/audio  # 音频缓存目录
-```
-
-### 4. 使用
-
-功能启用后，处理无字幕视频时会自动生成字幕：
-
-```python
-from src.pipeline import ProcessingPipeline
-from src.models import Content
-
-pipeline = ProcessingPipeline()
-content = Content(url="https://www.bilibili.com/video/BVxxxxx")
-
-# 处理时会自动生成字幕（如果需要）
-pipeline.process_full(content)
-```
-
---
-
-## 📊 模型选择
-
-Whisper 提供多种大小的模型，可根据需求选择：
-
-| 模型 | 大小 | 10分钟视频处理时间 | 准确度 | 推荐场景 |
-|------|------|-------------------|--------|----------|
-| tiny | ~39MB | ~30秒 | ⭐⭐ | 快速测试、批量处理 |
-| **base** | **~74MB** | **~2分钟** | **⭐⭐⭐⭐** | **日常使用（推荐）** |
-| small | ~244MB | ~5分钟 | ⭐⭐⭐⭐⭐ | 高质量需求 |
-| medium | ~769MB | ~10分钟 | ⭐⭐⭐⭐⭐ | 专业用途 |
-| large | ~1550MB | ~15分钟+ | ⭐⭐⭐⭐⭐ | 最高准确度 |
-
-### 推荐配置
-
- **默认**: `base` - 速度与准确度的最佳平衡
- **低配机器**: `tiny` - 最小资源占用
- **高质量需求**: `small` - 更好的识别效果
- **有 GPU**: `medium` / `large` - 充分利用硬件加速
-
---
-
-## 🎯 使用场景
-
-### 1. 无字幕视频
-
-B站、YouTube 等平台的部分视频没有提供字幕，启用此功能后可以自动生成。
-
-### 2. 批量处理
-
-处理多个视频时，缓存机制会显著提升速度：
-
-```python
-# 第一次处理：下载 + 识别（约 2-5 分钟）
-pipeline.process_full(content1)
-
-# 第二次处理相同视频：直接读取缓存（约 1 秒）
-pipeline.process_full(content1)
-```
-
-### 3. 多语言内容
-
-支持中英文混合内容的自动识别：
-
-```yaml
-subtitle:
-  language: null  # 自动检测语言
-```
-
-或指定语言：
-
-```yaml
-subtitle:
-  language: zh  # 强制使用中文
-```
-
---
-
-## 🧪 测试
-
-运行测试脚本验证功能：
-
-```bash
-cd skills/obsidian-kb
-python test_subtitle_generator.py
-```
-
-测试覆盖：
- ✅ 音频下载
- ✅ Whisper 识别
- ✅ SRT 格式化
- ✅ 缓存机制
- ✅ 完整工作流程
-
---
-
-## 📦 API 文档
-
-### SubtitleGenerator
-
-主要接口类，整合所有功能。
-
-```python
-from subtitle_generator import SubtitleGenerator
-
-generator = SubtitleGenerator(
-    model_size='base',  # 模型大小
-    cache_dir='cache/subtitles'  # 缓存目录
-)
-
-# 生成字幕
-srt_text = generator.generate(
-    url='https://www.bilibili.com/video/BVxxxxx',
-    content_id='unique_id',
-    language='zh',  # 可选：指定语言
-    use_cache=True  # 可选：使用缓存
-)
-```
-
-### 便捷函数
-
-快速生成字幕的便捷函数：
-
-```python
-from subtitle_generator import generate_subtitle
-
-srt_text = generate_subtitle(
-    url='https://www.bilibili.com/video/BVxxxxx',
-    content_id='unique_id',
-    model='base',
-    language='zh'
-)
-```
-
---
-
-## 🔧 高级配置
-
-### GPU 加速
-
-如果系统有 NVIDIA GPU 并安装了 CUDA，Whisper 会自动使用 GPU 加速：
-
-```python
-import torch
-print(f"GPU 可用: {torch.cuda.is_available()}")
-```
-
-使用 GPU 时，处理速度可提升 5-10 倍。
-
-### 清理缓存
-
-手动清理字幕缓存：
-
-```python
-from subtitle_generator import SubtitleCache
-
-cache = SubtitleCache()
-cache.clear()
-```
-
-或直接删除目录：
-
-```bash
-rm -rf cache/subtitles/*
-```
-
-### 自定义模型路径
-
-如果需要使用自定义模型文件：
-
-```python
-import whisper
-
-model = whisper.load_model(
-    '/path/to/custom/model.pt',
-    device='cpu'
-)
-```
-
---
-
-## ⚠️ 注意事项
-
-### 1. 存储空间
-
- **模型文件**: ~150MB (tiny) - 3GB (large)
- **音频缓存**: 每分钟视频约 1-2MB（处理完成后自动清理）
- **字幕缓存**: 每分钟视频约 1-3KB（长期保留）
-
-建议：
- 使用 `base` 模型作为默认
- 定期清理 `cache/audio` 目录
- 字幕缓存可以长期保留
-
-### 2. 处理时间
-
- **无 GPU**: 10分钟视频约 2-5 分钟（base 模型）
- **有 GPU**: 10分钟视频约 20-40 秒（base 模型）
-
-### 3. 隐私安全
-
- ✅ Whisper 本地处理，音频不上传
- ✅ 缓存文件在本地，不共享
- ✅ 开源软件，代码透明
-
-### 4. 识别准确度
-
-Whisper 的识别效果取决于：
- **音频质量**: 清晰的音频效果更好
- **背景噪音**: 嘈杂环境可能影响识别
- **说话方式**: 语速过快、口音过重可能降低准确度
-
-建议：
- 优先处理高质量音频
- 对生成的字幕进行人工审核
- 复杂内容可考虑使用人工字幕
-
-### 5. 错误处理
-
-系统已完善的错误处理机制：
-
- **下载失败**: 记录错误，继续处理
- **识别失败**: 记录错误，继续处理
- **格式化失败**: 使用原始文本
-
-任何错误都不会中断主流程。
-
---
-
-## 🚀 后续优化方向
-
-### 1. GPU 加速支持
-
- [ ] 自动检测 GPU 可用性
- [ ] 支持 CUDA / MPS (Apple Silicon)
- [ ] 多 GPU 支持
-
-### 2. 模型优化
-
- [ ] 支持量化模型（减小体积）
- [ ] 支持蒸馏模型（提升速度）
- [ ] 支持自定义模型微调
-
-### 3. 功能增强
-
- [ ] 批量处理多个视频
- [ ] 支持更多视频平台
- [ ] 字幕编辑器 Web 界面
- [ ] 实时字幕生成
-
-### 4. 云端集成
-
- [ ] 可选切换到云 API（阿里云/腾讯云）
- [ ] 混合模式：本地优先，云端降级
- [ ] 分布式处理支持
-
---
-
-## 📄 许可证
-
-本功能使用以下开源组件：
-
- **openai-whisper**: MIT License
- **yt-dlp**: Unlicense
- **torch**: BSD License
-
---
-
-## 🤝 贡献
-
-欢迎贡献代码、报告问题或提出建议！
-
---
-
-**最后更新**: 2026-02-07
-**版本**: 1.0.0
@@ -1,6 +0,0 @@
-{
-  "ownerId": "kn7xgqexpl4ek5qwng3t4hk0fu77kbex",
-  "slug": "obsidian-kb",
-  "version": "1.0.0",
-  "publishedAt": 1738857000000
-}
@@ -1,145 +0,0 @@
-#!/usr/bin/env python3
-"""手动添加B站视频到obsidian-kb收件箱"""
-
-import sys
-import os
-import urllib.request
-from urllib.request import Request, urlopen
-
-# 添加路径以便导入模块
-sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), 'src'))
-
-from sources.bilibili import BilibiliAdapter
-from models import Content, ContentStatus
-from storage import Storage
-from shortlink_resolver import (
-    ShortLinkResolver,
-    PlaywrightResolver,
-    detect_and_format
-)
-
-def resolve_short_url(url: str, try_playwright: bool = False) -> str:
-    """
-    解析短链接（如 b23.tv）到完整URL，或接受BV号
-
-    Args:
-        url: 可能是短链接的URL、完整URL或BV号
-        try_playwright: 是否尝试使用Playwright解析短链接
-
-    Returns:
-        str: 完整URL或BV号，如果失败返回None
-    """
-    # 如果已经是完整URL，直接返回
-    if 'bilibili.com/video/' in url:
-        return url
-
-    # 如果是BV号，直接返回（bilibili.py 的 extract_content 会处理）
-    if url.upper().startswith('BV'):
-        return url
-
-    # 如果是短链接，尝试解析
-    resolver = ShortLinkResolver()
-
-    if resolver.is_bilibili_short_link(url):
-        print(f"  ⚠️  检测到短链接 {url}")
-
-        # 尝试使用Playwright解析（如果启用）
-        if try_playwright:
-            print(f"  🔄 尝试使用浏览器解析...")
-            playwright_resolver = PlaywrightResolver(headless=True)
-
-            try:
-                resolved_url = playwright_resolver.resolve_bilibili_short(url)
-                if resolved_url:
-                    print(f"  ✅ 解析成功: {resolved_url}")
-                    return resolved_url
-                else:
-                    print(f"  ❌ 浏览器解析失败")
-            except Exception as e:
-                print(f"  ❌ Playwright不可用或解析失败: {e}")
-
-        # 显示用户引导
-        print("")
-        print(resolver.format_short_link_help(url))
-        print("")
-        return None
-
-    # 默认返回原URL
-    return url
-
-def add_video_to_inbox(url: str, try_playwright: bool = False) -> str:
-    """
-    添加B站视频到收件箱
-
-    Args:
-        url: B站视频URL
-        try_playwright: 是否尝试使用Playwright解析短链接
-
-    Returns:
-        str: Content ID
-    """
-    print(f"📥 正在处理视频: {url}")
-
-    # 解析短链接
-    resolved_url = resolve_short_url(url, try_playwright=try_playwright)
-    if resolved_url is None:
-        return None
-
-    # 创建适配器
-    adapter = BilibiliAdapter()
-
-    # 提取视频元数据
-    print("  → 获取视频信息...")
-    content = adapter.extract_content(resolved_url)
-    if not content:
-        print("  ❌ 无法提取视频信息")
-        return None
-
-    print(f"  → 标题: {content.title}")
-    print(f"  → UP主: {content.author}")
-    print(f"  → 时长: {content.duration}秒")
-
-    # 获取字幕
-    print("  → 获取字幕...")
-    transcript = adapter.get_transcript(content)
-    if transcript:
-        content.transcript = transcript
-        print(f"  ✓ 字幕已获取 ({len(transcript)} 字符)")
-    else:
-        print("  ⚠️  无法获取字幕")
-
-    # 设置状态为已确认（准备处理）
-    content.status = ContentStatus.CONFIRMED
-
-    # 保存到收件箱
-    print("  → 保存到收件箱...")
-    storage = Storage()
-    storage.save_content(content)
-
-    print(f"\n✅ 视频已添加到收件箱!")
-    print(f"   Content ID: {content.id}")
-    print(f"\n💡 使用以下命令处理:")
-    print(f"   python3 src/cli.py process {content.id}")
-    print(f"   或者:")
-    print(f"   python3 src/cli.py process all")
-
-    return content.id
-
-if __name__ == '__main__':
-    if len(sys.argv) < 2:
-        print("用法: python3 add_video.py <B站视频URL>")
-        print("示例:")
-        print("  python3 add_video.py https://www.bilibili.com/video/BV1xx411c7mD")
-        print("  python3 add_video.py BV1xx411c7mD")
-        print("  python3 add_video.py https://b23.tv/oLBZZfK")
-        print("\n选项:")
-        print("  --playwright  尝试使用浏览器解析短链接")
-        sys.exit(1)
-
-    url = sys.argv[1]
-    try_playwright = '--playwright' in sys.argv
-    if try_playwright and url == '--playwright' and len(sys.argv) > 2:
-        url = sys.argv[2]
-
-    add_video_to_inbox(url, try_playwright=try_playwright)
@@ -1,51 +0,0 @@
-# obsidian-kb 配置文件示例
-# 复制此文件为 config.yaml 并修改配置
-
-# Obsidian 笔记库路径
-obsidian_vault: ~/Documents/ObsidianVault
-
-# 笔记输出目录（相对于 vault）
-output_dir: AI_Generated
-
-# Git 同步配置
-git:
-  enabled: false
-  repo: ~/Documents/ObsidianVault
-  branch: main
-  auto_commit: true
-  auto_push: true
-
-# AI 客户端配置
-ai_client:
-  provider: openai  # openai 或 anthropic
-  model: gpt-4o-mini
-  api_key: ${OPENAI_API_KEY}  # 从环境变量读取
-  base_url: null  # 自定义 API 端点（可选）
-  temperature: 0.7
-  max_tokens: 4000
-
-# 内容处理配置
-content:
-  max_video_length: 3600  # 最大视频长度（秒），超过则跳过
-  min_transcript_length: 100  # 最小字幕长度（字符）
-  chunk_size: 2000  # 文本分块大小（字符）
-  chunk_overlap: 200  # 分块重叠大小（字符）
-
-# 模板配置
-templates:
-  note_template: templates/default_note.md
-  summary_template: templates/default_summary.md
-  deep_analysis_template: templates/default_deep_analysis.md
-
-# 字幕生成配置（新增）
-subtitle:
-  enabled: false  # 是否启用自动生成字幕
-  model: base  # Whisper 模型大小: tiny/base/small/medium/large
-  language: null  # 语言代码: zh/en/null(自动检测)
-  cache_dir: cache/subtitles  # 字幕缓存目录
-  audio_cache_dir: cache/audio  # 音频缓存目录
-
-# 日志配置
-logging:
-  level: INFO  # DEBUG, INFO, WARNING, ERROR
-  file: logs/obsidian-kb.log
@@ -9,13 +9,6 @@ jinja2>=3.1.2
 openai>=1.0.0
 anthropic>=0.7.0

-# Subtitle generation
-openai-whisper>=20230314
-yt-dlp>=2023.1.6
-# Use CPU version for torch (smaller, faster to install)
-# To use GPU, remove --index-url and install with: pip install torch
-torch>=2.0.0
-
 # Testing
 pytest>=7.4.0
 pytest-cov>=4.1.0
@@ -18,7 +18,6 @@ try:
    from src.storage import Storage
    from src.pipeline import ProcessingPipeline
    from src.models import ContentStatus
-    from src.sources.bilibili import BilibiliAdapter
    CONFIG_AVAILABLE = True
 except ImportError as e:
    print(f"Import warning: {e}", file=sys.stderr)
@@ -103,110 +102,6 @@ def cmd_subscribe(args: argparse.Namespace):
    return 0


-def cmd_add(args: argparse.Namespace):
-    """Handle add command - add a single video to inbox."""
-    print_header("Add Video to Inbox")
-    
-    if not CONFIG_AVAILABLE:
-        print("Error: Required modules not available. Please check installation.")
-        return 1
-    
-    # Import here to avoid issues if not available
-    from src.models import ContentStatus
-    
-    url = args.url
-    
-    # Handle short links (b23.tv)
-    if 'b23.tv' in url:
-        print(f"  ⚠️  检测到短链接: {url}")
-        print(f"  💡 B站对短链接有反爬虫保护，请提供:")
-        print(f"     1. 完整URL: https://www.bilibili.com/video/BVxxxxx")
-        print(f"     2. 或BV号: BVxxxxx")
-        print(f"\n  提示: 可以在浏览器打开短链接，从地址栏复制完整URL")
-        return 1
-    
-    # Create adapter
-    adapter = BilibiliAdapter()
-    
-    # Extract video metadata
-    print(f"  → 正在获取视频信息: {url}")
-    content = adapter.extract_content(url)
-    if not content:
-        print("  ❌ 无法提取视频信息")
-        return 1
-    
-    print(f"  → 标题: {content.title}")
-    print(f"  → UP主: {content.author}")
-    print(f"  → 时长: {content.duration}秒")
-    
-    # Get transcript
-    print("  → 正在获取字幕...")
-    transcript = adapter.get_transcript(content)
-    if transcript:
-        content.transcript = transcript
-        print(f"  ✓ 字幕已获取 ({len(transcript)} 字符)")
-    else:
-        print("  ⚠️  无法获取字幕")
-    
-    # Set status to CONFIRMED (ready to process)
-    content.status = ContentStatus.CONFIRMED
-    
-    # Confirm before saving (unless --yes)
-    if not args.yes:
-        print(f"\n📋 准备添加到收件箱:")
-        print(f"   标题: {content.title}")
-        print(f"   UP主: {content.author}")
-        print(f"   时长: {content.duration}秒")
-        print(f"   字幕: {'有' if transcript else '无'}")
-        
-        if args.process:
-            print(f"   操作: 添加并立即处理")
-        else:
-            print(f"   操作: 仅添加到收件箱")
-        
-        confirm = input("\n确认添加? [Y/n]: ").strip().lower()
-        if confirm and confirm not in ('y', 'yes'):
-            print("❌ 已取消")
-            return 0
-    
-    # Save to inbox
-    print("\n  → 保存到收件箱...")
-    storage = Storage()
-    storage.save_content(content)
-    
-    print(f"\n✅ 视频已添加到收件箱!")
-    print(f"   Content ID: {content.id}")
-    
-    # Process immediately if --process flag is set
-    if args.process:
-        print(f"\n🔄 开始处理内容...")
-        try:
-            from src.pipeline import ProcessingPipeline
-            from src.models import ContentStatus
-            
-            pipeline = ProcessingPipeline()
-            content_text = content.transcript or content.summary or ""
-            
-            result = pipeline.process_full(content, content_text)
-            storage.save_content(result)
-            
-            print(f"  ✅ 处理完成")
-            print(f"  📄 笔记: {result.output_path or 'N/A'}")
-            print(f"  🏷️  标签: {', '.join(result.tags)}")
-        except Exception as e:
-            print(f"  ❌ 处理失败: {e}")
-            import traceback
-            traceback.print_exc()
-            return 1
-    else:
-        print(f"\n💡 使用以下命令处理:")
-        print(f"   python3 src/cli.py process {content.id}")
-        print(f"   或:")
-        print(f"   python3 src/cli.py process all")
-    
-    return 0
-
-
 def cmd_inbox(args: argparse.Namespace):
    """Handle inbox command - display pending items."""
    print_header("Inbox Contents")
@@ -532,9 +427,6 @@ def main():
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog="""
 Examples:
-  %(prog)s add "BV1xx411c7mD"
-  %(prog)s add "https://www.bilibili.com/video/BV1xx411c7mD" --process
-  %(prog)s add "https://b23.tv/xxxxx" --yes
  %(prog)s subscribe bilibili fav 12345 --name="Tech Favorites"
  %(prog)s inbox --limit 10 --sort date
  %(prog)s process all --yes
@@ -547,28 +439,6 @@ Examples:
    
    subparsers = parser.add_subparsers(dest='command', help='Available commands')
    
-    # add 子命令
-    add_parser = subparsers.add_parser(
-        'add',
-        aliases=['a'],
-        help='Add a single video to inbox'
-    )
-    add_parser.add_argument(
-        'url',
-        help='Video URL or BV ID (supports: BVxxxxx, full URL)'
-    )
-    add_parser.add_argument(
-        '--process',
-        action='store_true',
-        help='Process immediately after adding'
-    )
-    add_parser.add_argument(
-        '--yes',
-        action='store_true',
-        help='Skip confirmation prompts'
-    )
-    add_parser.set_defaults(func=cmd_add)
-    
    # subscribe 子命令
    subscribe_parser = subparsers.add_parser(
        'subscribe', 
@@ -4,7 +4,7 @@ C4.3: 实现完整处理流程
 import os
 from datetime import datetime
 from typing import Optional
-from src.models import Content, ContentStatus, AnalysisResult, ContentType
+from src.models import Content, ContentStatus, AnalysisResult
 from src.light_scanner import LightScanner
 from src.deep_analyzer import DeepAnalyzer
 from src.config import get_config
@@ -22,149 +22,6 @@ class ProcessingPipeline:
        self.light_scanner = LightScanner(ai_client=ai_client)
        self.deep_analyzer = DeepAnalyzer(ai_client=ai_client)
    
-        # 初始化字幕生成器（如果启用）
-        self.subtitle_generator = None
-        self._init_subtitle_generator()
-
-    def _init_subtitle_generator(self):
-        """初始化字幕生成器"""
-        subtitle_config = self.config.get('subtitle', {})
-
-        if subtitle_config.get('enabled', False):
-            try:
-                # 延迟导入，避免依赖问题
-                from subtitle_generator import SubtitleGenerator
-
-                model_size = subtitle_config.get('model', 'base')
-                cache_dir = subtitle_config.get('cache_dir', 'cache/subtitles')
-
-                self.subtitle_generator = SubtitleGenerator(
-                    model_size=model_size,
-                    cache_dir=cache_dir
-                )
-
-                print(f"[Pipeline] 字幕生成器已初始化 (model={model_size})")
-            except ImportError as e:
-                print(f"[Pipeline] 字幕生成器初始化失败: {e}")
-                print(f"[Pipeline] 提示: 需要安装 openai-whisper 和 yt-dlp")
-                self.subtitle_generator = None
-            except Exception as e:
-                print(f"[Pipeline] 字幕生成器初始化失败: {e}")
-                self.subtitle_generator = None
-
-    def _ensure_subtitle(self, content: Content) -> str:
-        """
-        确保内容有字幕，如果没有则生成
-
-        Args:
-            content: Content对象
-
-        Returns:
-            str: 字幕文本
-        """
-        # 1. 检查是否已有字幕
-        if content.transcript and len(content.transcript) > 100:
-            print(f"[Pipeline] 使用现有字幕 (长度: {len(content.transcript)} 字符)")
-            return content.transcript
-
-        # 2. 检查是否启用自动生成
-        if not self.subtitle_generator:
-            print(f"[Pipeline] 字幕生成器未启用或初始化失败，跳过生成")
-            return ""
-
-        # 3. 只处理视频内容
-        if content.content_type != ContentType.VIDEO:
-            print(f"[Pipeline] 非视频内容，跳过字幕生成")
-            return ""
-
-        # 4. 生成字幕
-        try:
-            print(f"[Pipeline] 开始自动生成字幕...")
-
-            subtitle_config = self.config.get('subtitle', {})
-            audio_cache_dir = subtitle_config.get('audio_cache_dir', 'cache/audio')
-            language = subtitle_config.get('language', None)
-
-            # 生成字幕
-            srt_text = self.subtitle_generator.generate(
-                url=content.url,
-                content_id=content.id,
-                audio_cache_dir=audio_cache_dir,
-                language=language,
-                use_cache=True
-            )
-
-            # 更新内容
-            content.transcript = srt_text
-
-            print(f"[Pipeline] 字幕生成完成 (长度: {len(srt_text)} 字符)")
-            return srt_text
-
-        except Exception as e:
-            print(f"[Pipeline] 字幕生成失败: {e}")
-            import traceback
-            traceback.print_exc()
-            return ""
-
-    def process_full(self, content: Content, content_text: str = None) -> Content:
-        """
-        完整处理流程:
-        轻量扫描 → 入库 → 深度分析 → 生成笔记 → Git同步
-
-        Args:
-            content: Content对象
-            content_text: 内容文本（可选，如果没有则自动生成字幕）
-
-        Returns:
-            完全处理后的Content对象
-        """
-        print(f"\n{'='*60}")
-        print(f"[Pipeline] 开始完整处理流程: {content.id}")
-        print(f"{'='*60}\n")
-
-        try:
-            # Step 0: 确保有字幕（新增）
-            print("\n📝 Step 0: 确保字幕可用")
-            content_text = content_text or self._ensure_subtitle(content)
-
-            if not content_text or len(content_text) < 50:
-                print(f"[Pipeline] 警告: 字幕过短或为空，可能影响分析质量")
-
-            # Step 1: 轻量扫描
-            print("\n📋 Step 1: 轻量扫描")
-            content = self.light_scan(content, content_text)
-
-            # Step 2: 入库（保存到数据库/文件系统）
-            print("\n💾 Step 2: 保存内容")
-            self._save_content(content)
-
-            # Step 3: 深度分析
-            print("\n🔍 Step 3: 深度分析")
-            content = self.deep_analyze(content, content_text)
-
-            # Step 4: 生成笔记
-            print("\n📝 Step 4: 生成Obsidian笔记")
-            content = self._generate_note(content)
-
-            # Step 5: Git同步
-            if self.config.git.enabled:
-                print("\n🔄 Step 5: Git同步")
-                self._sync_to_git(content)
-            else:
-                print("\n⏭️ Step 5: Git同步已禁用，跳过")
-
-            content.update_status(ContentStatus.GENERATED)
-
-            print(f"\n{'='*60}")
-            print(f"[Pipeline] 处理完成: {content.id}")
-            print(f"{'='*60}\n")
-
-            return content
-
-        except Exception as e:
-            print(f"\n❌ [Pipeline] 处理流程失败: {e}")
-            raise
-
    def light_scan(self, content: Content, content_text: str) -> Content:
        """
        轻量扫描阶段
@@ -208,6 +65,58 @@ class ProcessingPipeline:
            content.update_status(ContentStatus.ERROR)
            raise
    
+    def process_full(self, content: Content, content_text: str) -> Content:
+        """
+        完整处理流程:
+        轻量扫描 → 入库 → 深度分析 → 生成笔记 → Git同步
+        
+        Args:
+            content: Content对象
+            content_text: 内容文本
+            
+        Returns:
+            完全处理后的Content对象
+        """
+        print(f"\n{'='*60}")
+        print(f"[Pipeline] 开始完整处理流程: {content.id}")
+        print(f"{'='*60}\n")
+        
+        try:
+            # Step 1: 轻量扫描
+            print("\n📋 Step 1: 轻量扫描")
+            content = self.light_scan(content, content_text)
+            
+            # Step 2: 入库（保存到数据库/文件系统）
+            print("\n💾 Step 2: 保存内容")
+            self._save_content(content)
+            
+            # Step 3: 深度分析
+            print("\n🔍 Step 3: 深度分析")
+            content = self.deep_analyze(content, content_text)
+            
+            # Step 4: 生成笔记
+            print("\n📝 Step 4: 生成Obsidian笔记")
+            content = self._generate_note(content)
+            
+            # Step 5: Git同步
+            if self.config.git.enabled:
+                print("\n🔄 Step 5: Git同步")
+                self._sync_to_git(content)
+            else:
+                print("\n⏭️ Step 5: Git同步已禁用，跳过")
+            
+            content.update_status(ContentStatus.GENERATED)
+            
+            print(f"\n{'='*60}")
+            print(f"[Pipeline] 处理完成: {content.id}")
+            print(f"{'='*60}\n")
+            
+            return content
+            
+        except Exception as e:
+            print(f"\n❌ [Pipeline] 处理流程失败: {e}")
+            raise
+    
    def _save_content(self, content: Content) -> None:
        """保存内容到存储"""
        # 创建存储目录
@@ -1,493 +0,0 @@
-#!/usr/bin/env python3
-"""
-字幕生成器 - 为无字幕视频自动生成 SRT 格式字幕
-
-使用 OpenAI Whisper 进行语音识别，支持本地离线处理
-"""
-
-import os
-import time
-import hashlib
-import logging
-from pathlib import Path
-from typing import Optional, Callable, Dict, Any
-
-# 配置日志
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-logger = logging.getLogger(__name__)
-
-
-class AudioDownloader:
-    """使用 yt-dlp 下载视频音频"""
-
-    def __init__(self):
-        """初始化音频下载器"""
-        self.ydl_opts = {
-            'format': 'bestaudio/best',
-            'postprocessors': [{
-                'key': 'FFmpegExtractAudio',
-                'preferredcodec': 'mp3',
-                'preferredquality': '192',
-            }],
-            'quiet': True,
-            'no_warnings': True,
-        }
-
-    def download_audio(self, url: str, output_path: str) -> str:
-        """
-        下载视频音频
-
-        Args:
-            url: 视频URL
-            output_path: 输出音频路径（可以是模板，如 'cache/audio/%(id)s.mp3'）
-
-        Returns:
-            str: 实际保存的音频文件路径
-
-        Raises:
-            Exception: 下载失败时抛出异常
-        """
-        try:
-            import yt_dlp
-
-            ydl_opts = self.ydl_opts.copy()
-            ydl_opts['outtmpl'] = output_path
-
-            logger.info(f"开始下载音频: {url}")
-            with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-                ydl.download([url])
-
-            # 替换扩展名
-            actual_path = output_path.replace('.%(ext)s', '.mp3')
-            if not os.path.exists(actual_path):
-                # 尝试其他可能的文件名
-                actual_path = output_path.rsplit('.', 1)[0] + '.mp3'
-
-            if os.path.exists(actual_path):
-                logger.info(f"音频下载成功: {actual_path}")
-                return actual_path
-            else:
-                raise FileNotFoundError(f"下载的音频文件未找到: {actual_path}")
-
-        except Exception as e:
-            logger.error(f"音频下载失败: {e}")
-            raise
-
-
-class WhisperTranscriber:
-    """Whisper 语音识别器"""
-
-    # 模型选择
-    MODELS = {
-        'tiny': 39000000,      # 最快，准确度最低 (~39M)
-        'base': 74000000,      # 推荐，速度/准确度平衡 (~74M)
-        'small': 244000000,    # 准确度更高 (~244M)
-        'medium': 769000000,   # 接近专业级 (~769M)
-        'large': 1550000000,   # 最高准确度 (~1.55GB)
-    }
-
-    def __init__(self, model_size: str = 'base'):
-        """
-        初始化识别器
-
-        Args:
-            model_size: 模型大小，默认 'base'
-        """
-        self.model_size = model_size
-        self.model = None
-        self.device = None
-
-    def load_model(self):
-        """加载 Whisper 模型（懒加载）"""
-        if self.model is None:
-            logger.info(f"正在加载 Whisper 模型 ({self.model_size})...")
-            start_time = time.time()
-
-            try:
-                import whisper
-                import torch
-
-                # 自动检测 GPU
-                self.device = "cuda" if torch.cuda.is_available() else "cpu"
-                logger.info(f"使用设备: {self.device}")
-
-                self.model = whisper.load_model(
-                    self.model_size,
-                    device=self.device
-                )
-
-                load_time = time.time() - start_time
-                logger.info(f"模型加载完成 - 耗时: {load_time:.1f}秒")
-
-            except Exception as e:
-                logger.error(f"模型加载失败: {e}")
-                raise
-
-    def transcribe(
-        self,
-        audio_path: str,
-        language: Optional[str] = None,
-        progress_callback: Optional[Callable[[str, float], None]] = None
-    ) -> Dict[str, Any]:
-        """
-        语音识别
-
-        Args:
-            audio_path: 音频文件路径
-            language: 语言代码（'zh'、'en'、None=自动检测）
-            progress_callback: 进度回调函数 callback(message, progress_percent)
-
-        Returns:
-            dict: Whisper 识别结果，包含 'text' 和 'segments'
-
-        Raises:
-            Exception: 识别失败时抛出异常
-        """
-        self.load_model()
-
-        logger.info(f"开始语音识别: {audio_path}")
-        if language:
-            logger.info(f"指定语言: {language}")
-        else:
-            logger.info("语言: 自动检测")
-
-        start_time = time.time()
-
-        try:
-            result = self.model.transcribe(
-                audio_path,
-                language=language,
-                task='transcribe',
-                verbose=False,
-                fp16=False  # CPU 上不使用 FP16
-            )
-
-            duration = time.time() - start_time
-            logger.info(f"识别完成 - 耗时: {duration:.1f}秒")
-
-            return result
-
-        except Exception as e:
-            logger.error(f"语音识别失败: {e}")
-            raise
-
-    def get_segments(self, result: Dict[str, Any]) -> list:
-        """
-        获取分段信息
-
-        Args:
-            result: Whisper 识别结果
-
-        Returns:
-            list: segments 列表
-        """
-        return result.get('segments', [])
-
-
-class SubtitleFormatter:
-    """字幕格式化器（SRT 格式）"""
-
-    @staticmethod
-    def to_srt(segments: list) -> str:
-        """
-        将 Whisper segments 转换为 SRT 格式
-
-        Args:
-            segments: Whisper segments 列表
-
-        Returns:
-            str: SRT 格式文本
-        """
-        srt_lines = []
-
-        for i, segment in enumerate(segments, 1):
-            # SRT 格式：
-            # 序号
-            # 开始时间 --> 结束时间
-            # 文本
-            # 空行
-
-            start_time = SubtitleFormatter._seconds_to_srt_time(segment['start'])
-            end_time = SubtitleFormatter._seconds_to_srt_time(segment['end'])
-            text = segment['text'].strip()
-
-            srt_lines.append(str(i))
-            srt_lines.append(f"{start_time} --> {end_time}")
-            srt_lines.append(text)
-            srt_lines.append("")
-
-        return "\n".join(srt_lines)
-
-    @staticmethod
-    def _seconds_to_srt_time(seconds: float) -> str:
-        """
-        将秒数转换为 SRT 时间格式 (HH:MM:SS,mmm)
-
-        Args:
-            seconds: 秒数
-
-        Returns:
-            str: SRT 时间格式
-        """
-        hours = int(seconds // 3600)
-        minutes = int((seconds % 3600) // 60)
-        secs = int(seconds % 60)
-        millis = int((seconds - int(seconds)) * 1000)
-
-        return f"{hours:02d}:{minutes:02d}:{secs:02d},{millis:03d}"
-
-
-class SubtitleCache:
-    """字幕缓存管理器"""
-
-    def __init__(self, cache_dir: str = 'cache/subtitles'):
-        """
-        初始化缓存
-
-        Args:
-            cache_dir: 缓存目录
-        """
-        self.cache_dir = Path(cache_dir)
-        self.cache_dir.mkdir(parents=True, exist_ok=True)
-
-    def get_cache_key(self, url: str) -> str:
-        """
-        生成缓存键
-
-        Args:
-            url: 视频URL
-
-        Returns:
-            str: 缓存键（SHA256 哈希的前8位）
-        """
-        return hashlib.sha256(url.encode()).hexdigest()[:8]
-
-    def get_cache_path(self, url: str) -> str:
-        """
-        获取缓存文件路径
-
-        Args:
-            url: 视频URL
-
-        Returns:
-            str: 缓存文件路径
-        """
-        cache_key = self.get_cache_key(url)
-        return str(self.cache_dir / f"{cache_key}.srt")
-
-    def get(self, url: str) -> Optional[str]:
-        """
-        获取缓存字幕
-
-        Args:
-            url: 视频URL
-
-        Returns:
-            str | None: 缓存的字幕内容，如果不存在返回 None
-        """
-        cache_path = self.get_cache_path(url)
-
-        if os.path.exists(cache_path):
-            logger.info(f"使用缓存字幕: {cache_path}")
-            try:
-                with open(cache_path, 'r', encoding='utf-8') as f:
-                    return f.read()
-            except Exception as e:
-                logger.warning(f"读取缓存失败: {e}")
-                return None
-
-        return None
-
-    def set(self, url: str, subtitle: str) -> str:
-        """
-        保存缓存字幕
-
-        Args:
-            url: 视频URL
-            subtitle: 字幕内容
-
-        Returns:
-            str: 缓存文件路径
-        """
-        cache_path = self.get_cache_path(url)
-
-        try:
-            with open(cache_path, 'w', encoding='utf-8') as f:
-                f.write(subtitle)
-            logger.info(f"字幕已缓存: {cache_path}")
-            return cache_path
-        except Exception as e:
-            logger.error(f"保存缓存失败: {e}")
-            raise
-
-    def exists(self, url: str) -> bool:
-        """检查缓存是否存在"""
-        return os.path.exists(self.get_cache_path(url))
-
-    def clear_cache(self):
-        """清空所有缓存"""
-        try:
-            for file in self.cache_dir.glob('*.srt'):
-                file.unlink()
-            logger.info("缓存已清空")
-        except Exception as e:
-            logger.error(f"清空缓存失败: {e}")
-
-
-class SubtitleGenerator:
-    """字幕生成器统一接口"""
-
-    def __init__(
-        self,
-        model_size: str = 'base',
-        cache_dir: str = 'cache/subtitles',
-        audio_cache_dir: str = 'cache/audio'
-    ):
-        """
-        初始化生成器
-
-        Args:
-            model_size: Whisper 模型大小
-            cache_dir: 字幕缓存目录
-            audio_cache_dir: 音频缓存目录
-        """
-        self.audio_downloader = AudioDownloader()
-        self.transcriber = WhisperTranscriber(model_size)
-        self.formatter = SubtitleFormatter()
-        self.cache = SubtitleCache(cache_dir)
-        self.audio_cache_dir = Path(audio_cache_dir)
-        self.audio_cache_dir.mkdir(parents=True, exist_ok=True)
-
-    def generate(
-        self,
-        url: str,
-        content_id: str = None,
-        language: Optional[str] = None,
-        use_cache: bool = True,
-        keep_audio: bool = False
-    ) -> str:
-        """
-        生成字幕
-
-        Args:
-            url: 视频URL
-            content_id: 内容ID（用于音频文件命名）
-            language: 语言代码（None=自动检测）
-            use_cache: 是否使用缓存
-            keep_audio: 是否保留音频文件
-
-        Returns:
-            str: SRT 格式字幕
-
-        Raises:
-            Exception: 生成失败时抛出异常
-        """
-        # 检查缓存
-        if use_cache and self.cache.exists(url):
-            logger.info(f"使用缓存字幕: {url}")
-            cached_subtitle = self.cache.get(url)
-            if cached_subtitle:
-                return cached_subtitle
-
-        logger.info(f"开始生成字幕: {url}")
-        audio_path = None
-
-        try:
-            # 生成 content_id
-            if content_id is None:
-                content_id = self.cache.get_cache_key(url)
-
-            # 下载音频
-            audio_path = str(self.audio_cache_dir / f"{content_id}.mp3")
-            logger.info(f"下载音频到: {audio_path}")
-            audio_path = self.audio_downloader.download_audio(url, audio_path)
-
-            # 语音识别
-            result = self.transcriber.transcribe(audio_path, language=language)
-            segments = self.transcriber.get_segments(result)
-
-            if not segments:
-                logger.warning("未识别到任何语音内容")
-                return ""
-
-            # 转换为 SRT
-            srt_text = self.formatter.to_srt(segments)
-            logger.info(f"SRT 字幕生成成功，共 {len(segments)} 段")
-
-            # 保存缓存
-            self.cache.set(url, srt_text)
-
-            # 清理音频文件
-            if not keep_audio and os.path.exists(audio_path):
-                os.remove(audio_path)
-                logger.info(f"已删除音频文件: {audio_path}")
-
-            return srt_text
-
-        except Exception as e:
-            logger.error(f"字幕生成失败: {e}")
-            # 清理失败的音频文件
-            if audio_path and os.path.exists(audio_path) and not keep_audio:
-                try:
-                    os.remove(audio_path)
-                except:
-                    pass
-            raise
-
-
-def generate_subtitle(
-    url: str,
-    model_size: str = 'base',
-    language: Optional[str] = None,
-    cache_dir: str = 'cache/subtitles',
-    audio_cache_dir: str = 'cache/audio'
-) -> str:
-    """
-    便捷函数：生成字幕
-
-    Args:
-        url: 视频URL
-        model_size: Whisper 模型大小
-        language: 语言代码（None=自动检测）
-        cache_dir: 字幕缓存目录
-        audio_cache_dir: 音频缓存目录
-
-    Returns:
-        str: SRT 格式字幕
-    """
-    generator = SubtitleGenerator(
-        model_size=model_size,
-        cache_dir=cache_dir,
-        audio_cache_dir=audio_cache_dir
-    )
-    return generator.generate(url, language=language)
-
-
-if __name__ == '__main__':
-    # 测试示例
-    import sys
-
-    if len(sys.argv) < 2:
-        print("用法: python subtitle_generator.py <视频URL> [语言]")
-        print("示例: python subtitle_generator.py https://www.bilibili.com/video/BV1xx411c7mD zh")
-        sys.exit(1)
-
-    url = sys.argv[1]
-    language = sys.argv[2] if len(sys.argv) > 2 else None
-
-    print("=" * 60)
-    print("字幕生成器")
-    print("=" * 60)
-
-    try:
-        subtitle = generate_subtitle(url, language=language)
-        print("\n" + "=" * 60)
-        print("生成成功！字幕预览（前500字符）：")
-        print("=" * 60)
-        print(subtitle[:500])
-        if len(subtitle) > 500:
-            print("\n...")
-        print(f"\n总字符数: {len(subtitle)}")
-    except Exception as e:
-        print(f"\n错误: {e}")
-        sys.exit(1)
@@ -1,184 +0,0 @@
-#!/usr/bin/env python3
-"""
-Test script for short link resolver functionality.
-"""
-
-import sys
-import os
-
-# Add path for imports
-sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
-
-from shortlink_resolver import ShortLinkResolver, detect_and_format
-
-
-def test_single_bilibili_short():
-    """Test single Bilibili short link detection."""
-    print("Test 1: Single Bilibili short link")
-    print("=" * 50)
-
-    text = "Check this video: https://b23.tv/oLBZZfK"
-    has_links, message = detect_and_format(text)
-
-    print(f"Input: {text}")
-    print(f"Has short links: {has_links}")
-    if message:
-        print(f"Message:\n{message}")
-    print()
-
-    assert has_links, "Should detect short link"
-    assert message, "Should have help message"
-    print("✅ Test 1 passed\n")
-
-
-def test_multiple_short_links():
-    """Test multiple short links detection."""
-    print("Test 2: Multiple short links")
-    print("=" * 50)
-
-    text = "Check these: https://b23.tv/abc123 and https://bit.ly/test"
-    has_links, message = detect_and_format(text)
-
-    print(f"Input: {text}")
-    print(f"Has short links: {has_links}")
-    if message:
-        print(f"Message:\n{message}")
-    print()
-
-    assert has_links, "Should detect short links"
-    assert message, "Should have warning message"
-    assert "[1]" in message, "Should show first link"
-    assert "[2]" in message, "Should show second link"
-    print("✅ Test 2 passed\n")
-
-
-def test_no_short_links():
-    """Test text with no short links."""
-    print("Test 3: No short links")
-    print("=" * 50)
-
-    text = "Here is a full URL: https://www.bilibili.com/video/BV1xx411c7mD"
-    has_links, message = detect_and_format(text)
-
-    print(f"Input: {text}")
-    print(f"Has short links: {has_links}")
-    if message:
-        print(f"Message: {message}")
-    else:
-        print("Message: None")
-    print()
-
-    assert not has_links, "Should not detect short links"
-    assert not message, "Should not have help message"
-    print("✅ Test 3 passed\n")
-
-
-def test_bv_code():
-    """Test BV code (should not be treated as short link)."""
-    print("Test 4: BV code")
-    print("=" * 50)
-
-    text = "BV1jcFqz7EFW"
-    has_links, message = detect_and_format(text)
-
-    print(f"Input: {text}")
-    print(f"Has short links: {has_links}")
-    if message:
-        print(f"Message: {message}")
-    else:
-        print("Message: None")
-    print()
-
-    assert not has_links, "BV code should not be treated as short link"
-    assert not message, "Should not have help message"
-    print("✅ Test 4 passed\n")
-
-
-def test_mixed_content():
-    """Test mixed content with short and full links."""
-    print("Test 5: Mixed content")
-    print("=" * 50)
-
-    text = """
-    Watch these videos:
-    https://www.bilibili.com/video/BV1xx411c7mD
-    https://b23.tv/short123
-    BV2yy522c8nE
-    """
-
-    has_links, message = detect_and_format(text)
-
-    print(f"Input:{text}")
-    print(f"Has short links: {has_links}")
-    if message:
-        print(f"Message:\n{message}")
-    print()
-
-    assert has_links, "Should detect short link"
-    assert message, "Should have help message"
-    print("✅ Test 5 passed\n")
-
-
-def test_resolver_direct():
-    """Test ShortLinkResolver directly."""
-    print("Test 6: Direct resolver usage")
-    print("=" * 50)
-
-    resolver = ShortLinkResolver()
-
-    # Test detection
-    short_links = resolver.detect_short_links("Check https://b23.tv/test123")
-    print(f"Detected: {short_links}")
-
-    assert len(short_links) == 1, "Should detect one short link"
-    assert short_links[0]['platform'] == 'bilibili', "Should be Bilibili"
-    assert short_links[0]['is_short'] == True, "Should be short link"
-
-    # Test format_short_link_help
-    help_msg = resolver.format_short_link_help("https://b23.tv/test123")
-    print(f"Help message:\n{help_msg}")
-
-    assert "短链接" in help_msg, "Should mention short link"
-    assert "BV" in help_msg, "Should mention BV code"
-
-    # Test format_short_link_warning
-    warning_msg = resolver.format_short_link_warning(short_links)
-    print(f"Warning message:\n{warning_msg}")
-
-    assert "[1]" in warning_msg, "Should show numbered list"
-
-    print()
-    print("✅ Test 6 passed\n")
-
-
-def run_all_tests():
-    """Run all tests."""
-    print("\n" + "=" * 50)
-    print("Running Short Link Resolver Tests")
-    print("=" * 50 + "\n")
-
-    try:
-        test_single_bilibili_short()
-        test_multiple_short_links()
-        test_no_short_links()
-        test_bv_code()
-        test_mixed_content()
-        test_resolver_direct()
-
-        print("\n" + "=" * 50)
-        print("✅ All tests passed!")
-        print("=" * 50 + "\n")
-        return 0
-
-    except AssertionError as e:
-        print(f"\n❌ Test failed: {e}\n")
-        return 1
-    except Exception as e:
-        print(f"\n❌ Unexpected error: {e}\n")
-        import traceback
-        traceback.print_exc()
-        return 1
-
-
-if __name__ == '__main__':
-    sys.exit(run_all_tests())
@@ -1,245 +0,0 @@
-#!/usr/bin/env python3
-"""
-字幕生成器测试脚本
-
-测试各个模块的功能
-"""
-
-import os
-import sys
-import tempfile
-from pathlib import Path
-
-# 添加项目路径
-sys.path.insert(0, str(Path(__file__).parent))
-
-
-def test_audio_downloader():
-    """测试音频下载器"""
-    print("\n" + "="*60)
-    print("测试 1: 音频下载器")
-    print("="*60)
-
-    from subtitle_generator import AudioDownloader
-
-    # 使用一个短测试视频
-    test_url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ"  # Rick Astley - Never Gonna Give You Up
-
-    downloader = AudioDownloader()
-
-    try:
-        with tempfile.TemporaryDirectory() as tmpdir:
-            output_path = os.path.join(tmpdir, "test_audio.%(ext)s")
-            result_path = downloader.download_audio(test_url, output_path)
-
-            if os.path.exists(result_path):
-                size_mb = os.path.getsize(result_path) / (1024 * 1024)
-                print(f"✅ 音频下载成功")
-                print(f"   文件: {result_path}")
-                print(f"   大小: {size_mb:.2f} MB")
-                return True
-            else:
-                print(f"❌ 音频文件未找到: {result_path}")
-                return False
-
-    except Exception as e:
-        print(f"❌ 音频下载失败: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-def test_whisper_transcriber():
-    """测试 Whisper 识别器"""
-    print("\n" + "="*60)
-    print("测试 2: Whisper 识别器")
-    print("="*60)
-
-    from subtitle_generator import WhisperTranscriber
-
-    # 创建测试音频（使用 ffmpeg 生成静音）
-    test_audio = "/tmp/test_silent.mp3"
-    os.system(f"ffmpeg -f lavfi -i anullsrc=r=44100:cl=mono -t 3 -q:a 9 -y {test_audio} 2>/dev/null")
-
-    try:
-        transcriber = WhisperTranscriber(model_size='tiny')  # 使用最小的模型
-        result = transcriber.transcribe(test_audio)
-
-        print(f"✅ Whisper 识别完成")
-        print(f"   识别文本: {result['text'][:50]}...")
-        print(f"   分段数: {len(result.get('segments', []))}")
-
-        return True
-
-    except Exception as e:
-        print(f"❌ Whisper 识别失败: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-def test_subtitle_formatter():
-    """测试 SRT 格式化器"""
-    print("\n" + "="*60)
-    print("测试 3: SRT 格式化器")
-    print("="*60)
-
-    from subtitle_generator import SubtitleFormatter
-
-    # 测试数据
-    test_segments = [
-        {'start': 0.0, 'end': 2.5, 'text': '这是一段测试字幕'},
-        {'start': 3.0, 'end': 5.7, 'text': '这是第二段字幕'},
-        {'start': 6.0, 'end': 8.2, 'text': 'This is the third subtitle'},
-    ]
-
-    try:
-        srt_text = SubtitleFormatter.to_srt(test_segments)
-
-        print(f"✅ SRT 格式化成功")
-        print(f"   生成内容预览:")
-        print("   " + "-" * 40)
-        for line in srt_text.split('\n')[:10]:
-            print(f"   {line}")
-        print("   " + "-" * 40)
-
-        # 验证格式
-        assert '00:00:00,000 --> 00:00:02,500' in srt_text
-        assert '这是一段测试字幕' in srt_text
-
-        return True
-
-    except Exception as e:
-        print(f"❌ SRT 格式化失败: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-def test_subtitle_cache():
-    """测试缓存管理器"""
-    print("\n" + "="*60)
-    print("测试 4: 缓存管理器")
-    print("="*60)
-
-    from subtitle_generator import SubtitleCache
-
-    test_url = "https://example.com/video/123"
-    test_subtitle = """1
-00:00:00,000 --> 00:00:02,500
-测试字幕内容
-"""
-
-    try:
-        cache = SubtitleCache(cache_dir='/tmp/test_subtitle_cache')
-
-        # 测试写入
-        cache_path = cache.set(test_url, test_subtitle)
-        print(f"✅ 缓存写入成功: {cache_path}")
-
-        # 测试读取
-        cached_content = cache.get(test_url)
-        assert cached_content == test_subtitle
-        print(f"✅ 缓存读取成功")
-
-        # 测试存在性
-        assert cache.exists(test_url)
-        print(f"✅ 缓存存在性检查成功")
-
-        # 测试缓存键
-        cache_key = cache.get_cache_key(test_url)
-        print(f"   缓存键: {cache_key}")
-
-        return True
-
-    except Exception as e:
-        print(f"❌ 缓存测试失败: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-def test_full_workflow():
-    """测试完整工作流程"""
-    print("\n" + "="*60)
-    print("测试 5: 完整工作流程")
-    print("="*60)
-
-    from subtitle_generator import SubtitleGenerator
-
-    test_url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
-
-    try:
-        generator = SubtitleGenerator(model_size='tiny')
-
-        print(f"开始生成字幕...")
-        srt_text = generator.generate(
-            url=test_url,
-            content_id='test001',
-            language='en',
-            use_cache=False
-        )
-
-        print(f"✅ 字幕生成完成")
-        print(f"   总字符数: {len(srt_text)}")
-        print(f"   预览（前300字符）:")
-        print("   " + "-" * 40)
-        print("   " + srt_text[:300])
-        print("   " + "-" * 40)
-
-        # 验证缓存
-        print(f"\n验证缓存...")
-        cached = generator.generate(
-            url=test_url,
-            content_id='test002',
-            use_cache=True
-        )
-        assert cached == srt_text
-        print(f"✅ 缓存验证成功")
-
-        return True
-
-    except Exception as e:
-        print(f"❌ 完整工作流程失败: {e}")
-        import traceback
-        traceback.print_exc()
-        return False
-
-
-def main():
-    """运行所有测试"""
-    print("\n" + "="*60)
-    print("字幕生成器测试套件")
-    print("="*60)
-
-    results = {}
-
-    # 运行各个测试
-    results['audio_downloader'] = test_audio_downloader()
-    results['whisper_transcriber'] = test_whisper_transcriber()
-    results['subtitle_formatter'] = test_subtitle_formatter()
-    results['subtitle_cache'] = test_subtitle_cache()
-    results['full_workflow'] = test_full_workflow()
-
-    # 输出汇总
-    print("\n" + "="*60)
-    print("测试结果汇总")
-    print("="*60)
-
-    for test_name, passed in results.items():
-        status = "✅ 通过" if passed else "❌ 失败"
-        print(f"{test_name:25s} {status}")
-
-    total = len(results)
-    passed = sum(results.values())
-
-    print("\n" + "="*60)
-    print(f"总计: {passed}/{total} 测试通过")
-    print("="*60)
-
-    return all(results.values())
-
-
-if __name__ == '__main__':
-    success = main()
-    sys.exit(0 if success else 1)
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "pr-reviewer",
+  "installedVersion": "1.0.0",
+  "installedAt": 1770282122334
+}
@@ -0,0 +1,89 @@
+---
+name: pr-reviewer
+description: Automated GitHub PR code review with diff analysis, lint integration, and structured reports. Use when reviewing pull requests, checking for security issues, error handling gaps, test coverage, or code style problems. Supports Go, Python, and JavaScript/TypeScript. Requires `gh` CLI authenticated with repo access.
+---
+
+# PR Reviewer
+
+Automated code review for GitHub pull requests. Analyzes diffs for security issues, error handling gaps, style problems, and test coverage.
+
+## Prerequisites
+
+- `gh` CLI installed and authenticated (`gh auth status`)
+- Repository access (read at minimum, write for posting comments)
+- Optional: `golangci-lint` for Go linting, `ruff` for Python linting
+
+## Quick Start
+
+```bash
+# Review all open PRs in current repo
+scripts/pr-review.sh check
+
+# Review a specific PR
+scripts/pr-review.sh review 42
+
+# Post review as GitHub comment
+scripts/pr-review.sh post 42
+
+# Check status of all open PRs
+scripts/pr-review.sh status
+
+# List unreviewed PRs (useful for heartbeat/cron integration)
+scripts/pr-review.sh list-unreviewed
+```
+
+## Configuration
+
+Set these environment variables or the script auto-detects from the current git repo:
+
+- `PR_REVIEW_REPO` — GitHub repo in `owner/repo` format (default: detected from `gh repo view`)
+- `PR_REVIEW_DIR` — Local checkout path for lint (default: git root of cwd)
+- `PR_REVIEW_STATE` — State file path (default: `./data/pr-reviews.json`)
+- `PR_REVIEW_OUTDIR` — Report output directory (default: `./data/pr-reviews/`)
+
+## What It Checks
+
+| Category | Icon | Examples |
+|----------|------|----------|
+| Security | 🔴 | Hardcoded credentials, AWS keys, secrets in code |
+| Error Handling | 🟡 | Discarded errors (Go `_ :=`), bare `except:` (Python), unchecked `Close()` |
+| Risk | 🟠 | `panic()` calls, `process.exit()` |
+| Style | 🔵 | `fmt.Print`/`print()`/`console.log` in prod, very long lines |
+| TODOs | 📝 | TODO, FIXME, HACK, XXX markers |
+| Test Coverage | 📊 | Source files changed without corresponding test changes |
+
+## Smart Re-Review
+
+Tracks HEAD SHA per PR. Only re-reviews when new commits are pushed. Use `review <PR#>` to force re-review.
+
+## Report Format
+
+Reports are saved as markdown files in the output directory. Each report includes:
+
+- PR metadata (author, branch, changes)
+- Commit list
+- Changed file categorization by language/type
+- Automated diff findings with file, line, category, and context
+- Test coverage analysis
+- Local lint results (when repo is checked out locally)
+- Summary verdict: 🔴 SECURITY / 🟡 NEEDS ATTENTION / 🔵 MINOR NOTES / ✅ LOOKS GOOD
+
+## Heartbeat/Cron Integration
+
+Add to a periodic check (heartbeat, cron job, or CI):
+
+```bash
+UNREVIEWED=$(scripts/pr-review.sh list-unreviewed)
+if [ -n "$UNREVIEWED" ]; then
+  scripts/pr-review.sh check
+fi
+```
+
+## Extending
+
+The analysis patterns in the script are organized by language. Add new patterns by appending to the relevant pattern list in the `analyze_diff()` function:
+
+```python
+# Add a new Go pattern
+go_patterns.append((r'^\+.*os\.Exit\(', 'RISK', 'Direct os.Exit() — consider returning error'))
+```
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn701kzxq5tkxw9mypbmspqw5580cxew",
+  "slug": "pr-reviewer",
+  "version": "1.0.0",
+  "publishedAt": 1770065590361
+}
@@ -0,0 +1,566 @@
+#!/usr/bin/env bash
+# pr-review.sh — Automated GitHub PR code review
+#
+# Fetches open PRs, analyzes diffs for security/error/style issues,
+# runs local lint, and generates structured review reports.
+#
+# Usage:
+#   pr-review.sh check              # Review all unreviewed open PRs
+#   pr-review.sh review <PR#>       # Review a specific PR (force re-review)
+#   pr-review.sh post <PR#>         # Post review as a GitHub PR comment
+#   pr-review.sh status             # Show review state for all open PRs
+#   pr-review.sh list-unreviewed    # List PRs needing review (for automation)
+#
+# Environment:
+#   PR_REVIEW_REPO    — owner/repo (default: auto-detect from gh)
+#   PR_REVIEW_DIR     — local checkout for lint (default: git root)
+#   PR_REVIEW_STATE   — state file (default: ./data/pr-reviews.json)
+#   PR_REVIEW_OUTDIR  — reports dir (default: ./data/pr-reviews/)
+
+set -euo pipefail
+
+# ── Configuration ────────────────────────────────────────────────────────────
+
+REPO="${PR_REVIEW_REPO:-}"
+LOCAL_DIR="${PR_REVIEW_DIR:-}"
+STATE_FILE="${PR_REVIEW_STATE:-./data/pr-reviews.json}"
+REVIEWS_DIR="${PR_REVIEW_OUTDIR:-./data/pr-reviews}"
+
+# Auto-detect repo if not set
+if [ -z "$REPO" ]; then
+  REPO=$(gh repo view --json nameWithOwner --jq '.nameWithOwner' 2>/dev/null || echo "")
+  if [ -z "$REPO" ]; then
+    echo "Error: Could not detect repo. Set PR_REVIEW_REPO=owner/repo" >&2
+    exit 1
+  fi
+fi
+
+# Auto-detect local dir if not set
+if [ -z "$LOCAL_DIR" ]; then
+  LOCAL_DIR=$(git rev-parse --show-toplevel 2>/dev/null || echo "")
+fi
+
+mkdir -p "$REVIEWS_DIR"
+[ -f "$STATE_FILE" ] || echo '{}' > "$STATE_FILE"
+
+# ── Helpers ──────────────────────────────────────────────────────────────────
+
+log() { echo "[pr-review] $*" >&2; }
+
+get_open_prs() {
+  gh pr list --repo "$REPO" --state open \
+    --json number,title,author,createdAt,headRefName,additions,deletions,changedFiles,labels,baseRefName \
+    2>/dev/null || echo '[]'
+}
+
+get_pr_diff() {
+  gh pr diff "$1" --repo "$REPO" 2>/dev/null || echo ""
+}
+
+get_pr_files() {
+  gh pr view "$1" --repo "$REPO" --json files --jq '.files[].path' 2>/dev/null || echo ""
+}
+
+get_pr_commits() {
+  gh pr view "$1" --repo "$REPO" --json commits \
+    --jq '.commits[] | "\(.oid[:8]) \(.messageHeadline)"' 2>/dev/null || echo ""
+}
+
+is_reviewed() {
+  local pr_num="$1"
+  local head_sha
+  head_sha=$(gh pr view "$pr_num" --repo "$REPO" --json headRefOid --jq '.headRefOid' 2>/dev/null || echo "")
+
+  python3 -c "
+import json
+with open('$STATE_FILE') as f:
+    state = json.load(f)
+pr = state.get(str($pr_num), {})
+if pr.get('head_sha') == '$head_sha' and pr.get('status') == 'reviewed':
+    print('yes')
+else:
+    print('no')
+" 2>/dev/null || echo "no"
+}
+
+update_state() {
+  python3 -c "
+import json, time
+with open('$STATE_FILE') as f:
+    state = json.load(f)
+state[str($1)] = {
+    'head_sha': '$2',
+    'status': '$3',
+    'reviewed_at': int(time.time()),
+    'report': '$REVIEWS_DIR/${1}.md'
+}
+with open('$STATE_FILE', 'w') as f:
+    json.dump(state, f, indent=2)
+"
+}
+
+# ── Analysis ─────────────────────────────────────────────────────────────────
+
+categorize_files() {
+  python3 -c "
+import sys, json
+from collections import defaultdict
+
+cats = defaultdict(list)
+for line in sys.stdin:
+    f = line.strip()
+    if not f: continue
+    ext = f.rsplit('.', 1)[-1] if '.' in f else ''
+    if ext == 'go':
+        cats['go'].append(f)
+    elif ext == 'py':
+        cats['python'].append(f)
+    elif ext in ('ts', 'tsx', 'js', 'jsx'):
+        cats['frontend'].append(f)
+    elif ext in ('yml', 'yaml', 'toml', 'json', 'env'):
+        cats['config'].append(f)
+    elif ext in ('md', 'txt', 'rst'):
+        cats['docs'].append(f)
+    elif ext == 'sql':
+        cats['sql'].append(f)
+    elif 'Dockerfile' in f or f == 'docker-compose.yml':
+        cats['docker'].append(f)
+    elif f.startswith('.github/'):
+        cats['ci'].append(f)
+    else:
+        cats['other'].append(f)
+print(json.dumps(dict(cats)))
+"
+}
+
+analyze_diff() {
+  python3 << 'PYEOF'
+import sys, json, re
+
+diff_text = sys.stdin.read()
+findings = []
+
+secret_patterns = [
+    (r'(?i)(password|passwd|secret|api[_-]?key|token|auth)\s*[:=]\s*["\x27][^"\x27]{8,}["\x27]', 'SECURITY', 'Possible hardcoded credential/secret'),
+    (r'(?i)AWS[_A-Z]*KEY\s*[:=]', 'SECURITY', 'Possible hardcoded AWS key'),
+    (r'(?i)-----BEGIN\s+(RSA\s+)?PRIVATE\s+KEY', 'SECURITY', 'Private key in source code'),
+]
+
+go_patterns = [
+    (r'^\+.*,\s*_\s*:?=.*\(', 'ERROR_HANDLING', 'Discarded error return value (Go)'),
+    (r'^\+.*\.Close\(\)\s*$', 'ERROR_HANDLING', 'Unchecked Close() — consider defer with error check'),
+    (r'^\+.*panic\(', 'RISK', 'Direct panic() call — consider returning error'),
+    (r'^\+.*fmt\.Print', 'STYLE', 'fmt.Print in production code — use structured logging'),
+    (r'^\+.*os\.Exit\(', 'RISK', 'Direct os.Exit() — consider returning error'),
+]
+
+python_patterns = [
+    (r'^\+.*except\s*:', 'ERROR_HANDLING', 'Bare except clause — catches everything including SystemExit'),
+    (r'^\+.*except Exception:', 'ERROR_HANDLING', 'Broad except Exception — consider specific errors'),
+    (r'^\+.*print\(', 'STYLE', 'print() in production code — use logging module'),
+    (r'^\+.*# type: ignore', 'TYPING', 'Type ignore comment — document why'),
+]
+
+js_patterns = [
+    (r'^\+.*console\.log\(', 'STYLE', 'console.log in production code'),
+    (r'^\+.*debugger', 'STYLE', 'Debugger statement — remove before merge'),
+    (r'^\+.*process\.exit\(', 'RISK', 'Direct process.exit() — consider throwing'),
+    (r'^\+.*eval\(', 'SECURITY', 'eval() usage — potential code injection'),
+    (r'^\+.*any\b', 'TYPING', 'TypeScript `any` type — consider specific type'),
+]
+
+general_patterns = [
+    (r'^\+.*TODO', 'TODO', 'TODO marker — track or address'),
+    (r'^\+.*FIXME', 'TODO', 'FIXME marker — should address before merge'),
+    (r'^\+.*HACK', 'TODO', 'HACK marker — needs cleanup'),
+    (r'^\+.*XXX', 'TODO', 'XXX marker — needs attention'),
+    (r'^\+.{200,}', 'STYLE', 'Very long line (>200 chars)'),
+]
+
+lines = diff_text.split('\n')
+current_file = None
+line_num = 0
+
+for line in lines:
+    m = re.match(r'^\+\+\+ b/(.*)', line)
+    if m:
+        current_file = m.group(1)
+        continue
+    m = re.match(r'^@@ -\d+(?:,\d+)? \+(\d+)', line)
+    if m:
+        line_num = int(m.group(1))
+        continue
+    if line.startswith('+') and not line.startswith('+++'):
+        line_num += 1
+        all_p = secret_patterns + general_patterns
+        if current_file:
+            if current_file.endswith('.go'):
+                all_p += go_patterns
+            elif current_file.endswith('.py'):
+                all_p += python_patterns
+            elif current_file.endswith(('.js', '.jsx', '.ts', '.tsx')):
+                all_p += js_patterns
+        for pat, cat, msg in all_p:
+            if re.search(pat, line):
+                findings.append({
+                    'file': current_file or 'unknown',
+                    'line': line_num,
+                    'category': cat,
+                    'message': msg,
+                    'context': line[1:].strip()[:120]
+                })
+    elif not line.startswith('-'):
+        line_num += 1
+
+print(json.dumps(findings))
+PYEOF
+}
+
+run_local_lint() {
+  local files="$1"
+  local results=""
+
+  if [ -z "$LOCAL_DIR" ] || [ ! -d "$LOCAL_DIR" ]; then
+    return
+  fi
+
+  # Go lint
+  local go_files
+  go_files=$(echo "$files" | grep '\.go$' || true)
+  if [ -n "$go_files" ] && command -v golangci-lint &>/dev/null; then
+    local go_dirs
+    go_dirs=$(echo "$go_files" | sed -n 's|\(.*\)/[^/]*\.go$|\1|p' | sort -u)
+    for dir in $go_dirs; do
+      local full="$LOCAL_DIR/$dir"
+      if [ -d "$full" ]; then
+        local out
+        out=$(cd "$full" && golangci-lint run --timeout 2m --new-from-rev=HEAD~1 2>&1 || true)
+        if [ -n "$out" ]; then
+          results="${results}\n### golangci-lint ($dir)\n\`\`\`\n${out}\n\`\`\`\n"
+        fi
+      fi
+    done
+  fi
+
+  # Python lint
+  local py_files
+  py_files=$(echo "$files" | grep '\.py$' || true)
+  if [ -n "$py_files" ] && command -v ruff &>/dev/null; then
+    local py_paths
+    py_paths=$(echo "$py_files" | sed "s|^|$LOCAL_DIR/|" | tr '\n' ' ')
+    local ruff_cfg=""
+    [ -f "$LOCAL_DIR/pyproject.toml" ] && ruff_cfg="--config $LOCAL_DIR/pyproject.toml"
+    local out
+    out=$(ruff check $ruff_cfg $py_paths 2>&1 || true)
+    if [ -n "$out" ] && ! echo "$out" | grep -q "^All checks passed"; then
+      results="${results}\n### ruff\n\`\`\`\n${out}\n\`\`\`\n"
+    fi
+  fi
+
+  echo -e "$results"
+}
+
+check_test_coverage() {
+  python3 -c "
+import sys
+
+files = '''$1'''.strip().split('\n')
+src, tests = [], []
+
+for f in files:
+    f = f.strip()
+    if not f: continue
+    if f.endswith('_test.go') or 'test_' in f.split('/')[-1] or f.endswith('_test.py') or f.endswith('.test.ts') or f.endswith('.test.js') or f.endswith('.spec.ts') or f.endswith('.spec.js'):
+        tests.append(f)
+    elif f.endswith(('.go', '.py', '.ts', '.tsx', '.js', '.jsx')):
+        src.append(f)
+
+missing = []
+for s in src:
+    has_test = False
+    s_dir = '/'.join(s.split('/')[:-1])
+    s_name = s.split('/')[-1].rsplit('.', 1)[0]
+    for t in tests:
+        t_dir = '/'.join(t.split('/')[:-1])
+        if t_dir == s_dir or f'test_{s_name}' in t or f'{s_name}_test' in t or f'{s_name}.test' in t or f'{s_name}.spec' in t:
+            has_test = True
+            break
+    skip = any(k in s for k in ['__init__', 'main.go', 'main.py', 'config', 'types', 'models', 'schema', 'index.ts', 'index.js'])
+    if not has_test and not skip:
+        missing.append(s)
+
+if missing:
+    print('Files without corresponding test changes:')
+    for f in missing:
+        print(f'  - {f}')
+else:
+    print('Test coverage looks adequate for changed files.')
+"
+}
+
+# ── Report Generation ────────────────────────────────────────────────────────
+
+generate_report() {
+  local pr_num="$1"
+  local force="${2:-false}"
+
+  if [ "$force" != "true" ]; then
+    local reviewed
+    reviewed=$(is_reviewed "$pr_num")
+    if [ "$reviewed" = "yes" ]; then
+      log "PR #$pr_num already reviewed at current HEAD. Use 'review' to force."
+      return 0
+    fi
+  fi
+
+  log "Reviewing PR #$pr_num..."
+
+  local pr_info
+  pr_info=$(gh pr view "$pr_num" --repo "$REPO" \
+    --json title,author,headRefName,headRefOid,baseRefName,additions,deletions,body,createdAt,labels 2>/dev/null)
+
+  local title author branch head_sha additions deletions body created
+  title=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['title'])")
+  author=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['author']['login'])")
+  branch=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['headRefName'])")
+  head_sha=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['headRefOid'])")
+  additions=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['additions'])")
+  deletions=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['deletions'])")
+  body=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin).get('body','') or '')")
+  created=$(echo "$pr_info" | python3 -c "import json,sys; print(json.load(sys.stdin)['createdAt'])")
+
+  local files diff commits
+  files=$(get_pr_files "$pr_num")
+  diff=$(get_pr_diff "$pr_num")
+  commits=$(get_pr_commits "$pr_num")
+
+  local categories
+  categories=$(echo "$files" | categorize_files)
+
+  local findings_file
+  findings_file=$(mktemp)
+  echo "$diff" | analyze_diff > "$findings_file"
+  trap "rm -f '$findings_file'" EXIT
+
+  local test_coverage
+  test_coverage=$(check_test_coverage "$files")
+
+  local lint_results=""
+  lint_results=$(run_local_lint "$files" 2>/dev/null || echo "")
+
+  local findings_summary
+  findings_summary=$(python3 -c "
+import json
+from collections import Counter
+with open('$findings_file') as f:
+    findings = json.load(f)
+counts = Counter(f['category'] for f in findings)
+if counts:
+    for cat, count in sorted(counts.items()):
+        icon = {'SECURITY':'🔴','ERROR_HANDLING':'🟡','RISK':'🟠','STYLE':'🔵','TODO':'📝','TYPING':'🟣'}.get(cat,'⚪')
+        print(f'{icon} {cat}: {count}')
+else:
+    print('✅ No issues found in diff analysis')
+")
+
+  local report_file="$REVIEWS_DIR/${pr_num}.md"
+  cat > "$report_file" << REPORT
+# PR #${pr_num} Review: ${title}
+
+**Author:** ${author}
+**Branch:** \`${branch}\`
+**HEAD:** \`${head_sha:0:8}\`
+**Created:** ${created}
+**Changes:** +${additions} / -${deletions}
+**Reviewed:** $(date -Iseconds)
+
+## Description
+
+${body:-_No description provided._}
+
+## Commits
+
+\`\`\`
+${commits}
+\`\`\`
+
+## Changed Files
+
+$(echo "$categories" | python3 -c "
+import json, sys
+cats = json.load(sys.stdin)
+icons = {'go':'🔷','python':'🐍','frontend':'🌐','ci':'⚙️','config':'📦','docs':'📝','docker':'🐳','sql':'💾','other':'📄'}
+for cat, files in sorted(cats.items()):
+    print(f'### {icons.get(cat,\"📄\")} {cat.title()} ({len(files)} files)')
+    for f in files:
+        print(f'- \`{f}\`')
+    print()
+")
+
+## Automated Analysis
+
+### Diff Findings
+
+${findings_summary}
+
+$(python3 -c "
+import json
+with open('$findings_file') as f:
+    findings = json.load(f)
+if findings:
+    print('| File | Line | Category | Finding | Context |')
+    print('|------|------|----------|---------|---------|')
+    for f in findings[:50]:
+        ctx = f['context'].replace('|', '\\\\|')
+        print(f'| \`{f[\"file\"].split(\"/\")[-1]}\` | {f[\"line\"]} | {f[\"category\"]} | {f[\"message\"]} | \`{ctx[:60]}\` |')
+")
+
+### Test Coverage
+
+${test_coverage}
+
+$(if [ -n "$lint_results" ]; then echo "### Local Lint Results"; echo ""; echo "$lint_results"; else echo "### Local Lint"; echo ""; echo "_Skipped (repo not checked out locally or linters not found)._"; fi)
+
+## Summary
+
+$(python3 -c "
+import json
+with open('$findings_file') as f:
+    findings = json.load(f)
+sec = [f for f in findings if f['category'] == 'SECURITY']
+err = [f for f in findings if f['category'] in ('ERROR_HANDLING', 'RISK')]
+sty = [f for f in findings if f['category'] in ('STYLE', 'TODO', 'TYPING')]
+if sec:
+    print('🔴 **SECURITY CONCERNS** — Review security findings before merging.')
+elif err:
+    print('🟡 **NEEDS ATTENTION** — Error handling / risk items to review.')
+elif sty:
+    print('🔵 **MINOR STYLE NOTES** — Looks good overall, minor suggestions above.')
+else:
+    print('✅ **LOOKS GOOD** — No automated issues found. Ready for human review.')
+")
+
+---
+_Automated PR review • $(date '+%Y-%m-%d %H:%M')_
+REPORT
+
+  update_state "$pr_num" "$head_sha" "reviewed"
+  log "Report saved to $report_file"
+  echo "$report_file"
+}
+
+# ── Commands ─────────────────────────────────────────────────────────────────
+
+cmd_check() {
+  local prs
+  prs=$(get_open_prs)
+  local count
+  count=$(echo "$prs" | python3 -c "import json,sys; print(len(json.load(sys.stdin)))")
+
+  if [ "$count" = "0" ]; then
+    log "No open PRs."
+    echo '{"reviewed": 0, "skipped": 0, "total": 0}'
+    return 0
+  fi
+
+  local reviewed=0 skipped=0
+  local pr_nums
+  pr_nums=$(echo "$prs" | python3 -c "import json,sys; [print(p['number']) for p in json.load(sys.stdin)]")
+
+  while IFS= read -r pr_num; do
+    [ -z "$pr_num" ] && continue
+    local already
+    already=$(is_reviewed "$pr_num")
+    if [ "$already" = "yes" ]; then
+      skipped=$((skipped + 1))
+      log "PR #$pr_num: already reviewed, skipping."
+    else
+      generate_report "$pr_num" "false"
+      reviewed=$((reviewed + 1))
+    fi
+  done <<< "$pr_nums"
+
+  echo "{\"reviewed\": $reviewed, \"skipped\": $skipped, \"total\": $count}"
+}
+
+cmd_review() {
+  local pr_num="${1:?PR number required}"
+  generate_report "$pr_num" "true"
+}
+
+cmd_post() {
+  local pr_num="${1:?PR number required}"
+  local report_file="$REVIEWS_DIR/${pr_num}.md"
+  if [ ! -f "$report_file" ]; then
+    log "No review report for PR #$pr_num. Run 'review $pr_num' first."
+    exit 1
+  fi
+  gh pr comment "$pr_num" --repo "$REPO" --body-file "$report_file"
+  log "Review posted to PR #$pr_num"
+}
+
+cmd_status() {
+  local prs
+  prs=$(get_open_prs)
+  python3 -c "
+import json, sys, time
+prs = json.loads(sys.stdin.read())
+try:
+    with open('$STATE_FILE') as f:
+        state = json.load(f)
+except:
+    state = {}
+if not prs:
+    print('No open PRs.')
+    sys.exit(0)
+print(f'Open PRs: {len(prs)}')
+print()
+for pr in prs:
+    num = str(pr['number'])
+    s = state.get(num, {})
+    status = s.get('status', 'unreviewed')
+    icon = '✅' if status == 'reviewed' else '⏳'
+    print(f'{icon} PR #{num}: {pr[\"title\"]} ({pr[\"author\"][\"login\"]})')
+    print(f'   +{pr[\"additions\"]}/-{pr[\"deletions\"]} | {pr[\"headRefName\"]}')
+    if s:
+        age = int(time.time()) - s.get('reviewed_at', 0)
+        print(f'   Reviewed {age // 3600}h ago | SHA: {s.get(\"head_sha\", \"?\")[:8]}')
+    print()
+" <<< "$prs"
+}
+
+cmd_list_unreviewed() {
+  local prs
+  prs=$(get_open_prs)
+  local pr_nums
+  pr_nums=$(echo "$prs" | python3 -c "import json,sys; [print(p['number']) for p in json.load(sys.stdin)]" 2>/dev/null)
+
+  while IFS= read -r pr_num; do
+    [ -z "$pr_num" ] && continue
+    local already
+    already=$(is_reviewed "$pr_num")
+    if [ "$already" != "yes" ]; then
+      echo "$pr_num"
+    fi
+  done <<< "$pr_nums"
+}
+
+# ── Main ─────────────────────────────────────────────────────────────────────
+
+case "${1:-}" in
+  check)            cmd_check ;;
+  review)           cmd_review "${2:-}" ;;
+  post)             cmd_post "${2:-}" ;;
+  status)           cmd_status ;;
+  list-unreviewed)  cmd_list_unreviewed ;;
+  *)
+    echo "Usage: pr-review.sh {check|review <PR#>|post <PR#>|status|list-unreviewed}"
+    echo ""
+    echo "Environment:"
+    echo "  PR_REVIEW_REPO    owner/repo (default: auto-detect)"
+    echo "  PR_REVIEW_DIR     local checkout for lint (default: git root)"
+    echo "  PR_REVIEW_STATE   state file (default: ./data/pr-reviews.json)"
+    echo "  PR_REVIEW_OUTDIR  reports dir (default: ./data/pr-reviews/)"
+    exit 1
+    ;;
+esac
@@ -0,0 +1,7 @@
+{
+  "version": 1,
+  "registry": "https://clawhub.ai",
+  "slug": "webhook-gen",
+  "installedVersion": "1.0.1",
+  "installedAt": 1770282138358
+}
@@ -0,0 +1,37 @@
+# ai-webhook
+
+Generate production-ready webhook handlers with signature verification, retry logic, and idempotency. Just describe the event.
+
+## Install
+
+```bash
+npm install -g ai-webhook
+```
+
+## Usage
+
+```bash
+npx ai-webhook "stripe payment succeeded"
+# Generates Express webhook handler with retry logic
+
+npx ai-webhook "github push event" -f nextjs
+# Next.js API route handler
+
+npx ai-webhook "shopify order created" -o webhook-handler.ts
+# Save to file
+```
+
+## Setup
+
+```bash
+export OPENAI_API_KEY=sk-...
+```
+
+## Options
+
+- `-f, --framework <name>` - Framework: express, fastify, nextjs (default: express)
+- `-o, --output <path>` - Save to file
+
+## License
+
+MIT
@@ -0,0 +1,83 @@
+---
+name: webhook-gen
+description: Generate webhook handlers with retry logic using AI. Use when integrating Stripe, GitHub, or any webhook provider.
+---
+
+# Webhook Generator
+
+Describe the webhook you're handling. Get a complete handler with signature verification, retry logic, and proper error handling. Stripe, GitHub, Twilio. all the patterns you need.
+
+**One command. Zero config. Just works.**
+
+## Quick Start
+
+```bash
+npx ai-webhook "stripe payment succeeded"
+```
+
+## What It Does
+
+- Generates complete webhook handler functions
+- Includes signature verification for popular providers
+- Adds idempotency checks to prevent duplicate processing
+- Implements retry-safe patterns with proper status codes
+- Handles common webhooks from Stripe, GitHub, Shopify, and more
+
+## Usage Examples
+
+```bash
+# Stripe payment webhook
+npx ai-webhook "stripe checkout.session.completed"
+
+# GitHub push events
+npx ai-webhook "github push event to trigger deployment"
+
+# Generic webhook with retry
+npx ai-webhook "order created webhook with idempotency" 
+
+# Specify provider explicitly
+npx ai-webhook "new subscriber notification" --provider convertkit
+
+# TypeScript output
+npx ai-webhook "invoice paid" --typescript
+```
+
+## Best Practices
+
+- **Always verify signatures** - Never trust raw webhook payloads
+- **Return 200 quickly** - Process async. Don't make providers wait
+- **Handle duplicates** - Webhooks retry. Your handler should be idempotent
+- **Log everything** - Debugging webhook issues without logs is painful
+
+## When to Use This
+
+- Integrating a payment provider like Stripe or Paddle
+- Setting up GitHub Actions alternatives with webhooks
+- Building notification systems triggered by external services
+- Any third-party integration that sends webhooks
+
+## Part of the LXGIC Dev Toolkit
+
+This is one of 110+ free developer tools built by LXGIC Studios. No paywalls, no sign-ups, no API keys on free tiers. Just tools that work.
+
+**Find more:**
+- GitHub: https://github.com/LXGIC-Studios
+- Twitter: https://x.com/lxgicstudios
+- Substack: https://lxgicstudios.substack.com
+- Website: https://lxgic.dev
+
+## Requirements
+
+No install needed. Just run with npx. Node.js 18+ recommended.
+
+```bash
+npx ai-webhook --help
+```
+
+## How It Works
+
+The tool recognizes common webhook patterns from your description. It generates a handler function with the appropriate verification method, event parsing, and response codes. AI ensures the handler follows best practices for reliability and security.
+
+## License
+
+MIT. Free forever. Use it however you want.
@@ -0,0 +1,6 @@
+{
+  "ownerId": "kn7as1q30eykdpxycyg4tp01n9802dwe",
+  "slug": "webhook-gen",
+  "version": "1.0.1",
+  "publishedAt": 1769626675369
+}
@@ -0,0 +1,2 @@
+#!/usr/bin/env node
+export {};
--- a/Show More
+++ b/Show More
				`@@ -0,0 +1 @@`
				`export declare function generateWorkflow(description: string): Promise<string>;`