一键导入
docs-seeker
Find documentation using llms.txt standard, context7.com, and repomix. Best practices for library research.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Find documentation using llms.txt standard, context7.com, and repomix. Best practices for library research.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Interview the user relentlessly about a plan or design until branch-level decisions are resolved for execution.
Access Figma designs, extract design systems, and retrieve component specifications. Use when implementing UI from Figma mockups, extracting design tokens, or analyzing design files.
Enforce cost-aware MCP usage. Use when a task might trigger heavy external tools, web search, or broad context expansion. Prevents token burn by ensuring MCPs are only used when local context is insufficient.
Navigate the Warmplane mcp0 facade efficiently. Use when the active config exposes provider capabilities through `mcp0_*` tools and you need to discover or call provider tools without brute-force describing large capability sets. Trigger on requests involving mcp0, Warmplane, or provider work through the facade such as Linear, Notion, Figma, New Relic, Context7, grep.app, or Storybook tools.
Use this when the user needs to control Chrome, navigate to a page, inspect a tab, click or fill elements, take screenshots, or automate a browser flow with aeroxy/chrome-devtools-cli.
Guidelines for creating and managing implementation plans with citations
| name | docs-seeker |
| description | Find documentation using llms.txt standard, context7.com, and repomix. Best practices for library research. |
Load this skill when you need to find documentation for libraries, frameworks, or APIs.
# Use the context7 MCP tool
context7_resolve_library_id(libraryName="next.js")
context7_get_library_docs(libraryId="...", topic="app router")
Supported libraries: Next.js, React, shadcn/ui, Tailwind CSS, Better Auth, Drizzle ORM, and many more.
Why first: Aggregates llms.txt files from official sources, AI-optimized format.
If context7 doesn't have it:
# Use webfetch for official docs
webfetch(url="https://docs.example.com/api/reference")
Best sources:
For understanding library internals:
# Package entire repo for analysis
npx repomix --remote https://github.com/owner/repo --output repo.xml
Use when:
1. context7 → resolve library ID
2. context7 → get docs for specific topic
3. If incomplete → webfetch official docs
4. If still unclear → repomix the source
1. webfetch → API reference page
2. Look for: endpoints, auth, rate limits
3. Find code examples
4. Test with minimal example first
1. grep_app → search GitHub for exact error
2. Look for: issues, discussions, PRs
3. Find the fix or workaround
4. Verify solution applies to your version
Many sites now provide /llms.txt files optimized for AI:
# Check for llms.txt
webfetch(url="https://example.com/llms.txt")
Format: Markdown with structured sections for AI consumption.
Growing adoption: Next.js, Vercel, Anthropic, and more.
| Need | Tool | Example |
|---|---|---|
| Library docs | context7 | context7_get_library_docs("react", "hooks") |
| API reference | webfetch | webfetch("https://api.example.com/docs") |
| GitHub search | grep_app | grep_app("error message") |
| Source analysis | repomix | npx repomix --remote url |
For comprehensive research, fire multiple agents:
task(agent="researcher", prompt="Find Next.js app router docs via context7")
task(agent="researcher", prompt="Find authentication patterns for Next.js")
task(agent="explore", prompt="Find how auth is implemented in this codebase")
Combine external docs with internal patterns for best results.