ts-interface-miner
一个专门用于分析 TypeScript (.ts/.tsx) 文件的智能助手。它能够根据用户提供的关键词（功能描述、函数名、API 路径），精准定位相关接口定义。该技能深度解析代码结构与注释（JSDoc/单行注释），提取请求方法、路径、参数细节、响应结构及状态码，最终生成结构清晰、信息完整的 Markdown 表格文档。
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/9talk/ts-interface-minerWhat This Skill Does
The ts-interface-miner is a specialized AI agent skill designed for TypeScript developers working in complex codebases. It acts as an automated documentation engineer, scanning .ts and .tsx files to extract critical API information. By leveraging intelligent parsing of JSDoc, inline comments, and TypeScript type definitions, it builds structured, human-readable documentation. It effectively bridges the gap between raw, loosely documented code and professional API reference guides, saving developers hours of manual documentation effort.
Installation
You can integrate this skill into your OpenClaw environment using the following command:
clawhub install openclaw/skills/skills/9talk/ts-interface-miner
Use Cases
- Legacy Code Onboarding: Quickly generate documentation for undocumented APIs in large-scale enterprise projects.
- Frontend-Backend Integration: Generate API requirement tables from frontend service files to confirm request parameters and response structures.
- Code Review: Automatically verify if TypeScript interfaces are correctly annotated and aligned with functional descriptions.
Example Prompts
- "Analyze the file at
src/services/auth.tsand generate an API document for theloginfunction." - "Find the interface for
/api/v1/orders/listand list all required body parameters in a table." - "Can you check the
updateUserProfilefunction inuser.service.tsand tell me what the response structure and potential error codes are?"
Tips & Limitations
- Tips: For best results, ensure your project utilizes clear JSDoc comments (
@param,@returns). The skill is optimized to resolve complex, nested TypeScript interfaces automatically. - Limitations: The tool is strictly designed for TypeScript files. While it handles common HTTP client patterns (axios, fetch), highly obfuscated code or non-standard custom network wrappers may require the AI to utilize more context provided by the user. If a type is dynamically generated at runtime without static definitions, the agent will report the inferred type instead.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-9talk-ts-interface-miner": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-read