docs-seeker
SkillDocs & knowledgeFind documentation for APIs, libraries, and error messages. Looks up official docs, changelog entries, and migration guides.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the docs-seeker skill
What this skill tells your AI
The instructions your AI receives, as published by rune-kit/rune in skills/docs-seeker/SKILL.md and read by ahel’s review.
Purpose
Documentation lookup utility. Receives a library name, API reference, or error message, resolves the correct documentation, and returns API signatures, usage examples, and known issues. Stateless — no memory between calls.
Calls (outbound)
None — pure L3 utility using WebSearch, WebFetch, and Context7 MCP tools directly.
Called By (inbound)
debug(L2): lookup API docs for unclear errorsfix(L2): check correct API usage before applying changesreview(L2): verify API usage is current and correctadversary(L2): verify framework/API assumptions in plan are correct
Execution
Input
target: string — library name, API endpoint, or error message
version: string — (optional) specific version to look up
query: string — specific question about the target (e.g., "how to configure retry")
Step 1 — Identify Target
Parse the input to extract:
- Library or framework name (e.g., "react-query", "fastapi", "prisma")
- Version if specified
- The specific API, method, or error to look up
Step 2 — Try Context7 MCP (fastest)
Attempt Context7 MCP lookup first (faster, higher quality):
- Call
mcp__plugin_context7_context7__resolve-library-idwith the library name and query - Select the best matching library ID from results (prioritize: name match, source reputation, snippet count)
- Call
mcp__plugin_context7_context7__query-docswith the resolved library ID and the specific query - If Context7 returns a satisfactory answer with code examples, proceed to Step 5
Step 3 — Try llms.txt Discovery
If Context7 MCP is unavailable or insufficient, try llms.txt (AI-optimized documentation):
For GitHub repos — pattern: https://context7.com/{org}/{repo}/llms.txt
github.com/vercel/next.js → context7.com/vercel/next.js/llms.txt
github.com/shadcn-ui/ui → context7.com/shadcn-ui/ui/llms.txt
For doc sites — pattern: https://context7.com/websites/{normalized-domain}/llms.txt
docs.imgix.com → context7.com/websites/imgix/llms.txt
ffmpeg.org/doxygen/8.0 → context7.com/websites/ffmpeg_doxygen_8_0/llms.txt
Topic-specific — append ?topic={query} for focused results:
context7.com/shadcn-ui/ui/llms.txt?topic=date-picker
context7.com/vercel/next.js/llms.txt?topic=cache
Traditional llms.txt fallback: WebSearch "[library] llms.txt" → common paths: docs.[lib].com/llms.txt, [lib].dev/llms.txt
Use WebFetch on the resolved llms.txt URL. If it contains multiple section URLs (3+), launch parallel Explorer agents (one per section, max 5).
Step 4 — Fallback to Web Search
If neither Context7 nor llms.txt available:
- Use
WebSearchwith queries:- "[library] [api/method] official documentation"
- "[library] [version] [query]"
- "[error message] [library] fix"
- Identify official documentation URLs (docs.*, official GitHub, npm/pypi pages)
- Call
WebFetchon the top 1-3 official sources
Repository analysis fallback (when docs are sparse but code is available):
npx repomix --output /tmp/repomix-output.xml # in the cloned repo
Read the repomix output to extract API patterns, usage examples, and internal documentation.
Step 5 — Extract Answer
From Context7, llms.txt, or fetched pages, extract:
- Exact API signature with parameter types and return type
- Minimal working code example
- Version-specific notes (deprecated in X, changed in Y)
- Known issues or common pitfalls mentioned in docs
Step 6 — Report
Return structured documentation in the output format below.
Constraints
- Prefer Context7 MCP → llms.txt → WebSearch (in that priority order)
- Only fall back to web if Context7 and llms.txt both lack coverage
- Use
?topic=parameter on llms.txt URLs for targeted results - Always include source URL so callers can verify
- If the API is deprecated, say so explicitly and link to the replacement
- For parallel fetching: 1-3 URLs = single agent, 4-10 = 3-5 Explorer agents, 11+ = 5-7 agents
Output Format
## Documentation: [Library/API]
- **Version**: [detected or "latest"]
- **Source**: [official docs URL or "Context7"]
### API Reference
- **Signature**: `functionName(param1: Type, param2: Type): ReturnType`
- **Parameters**:
- `param1` — description
- `param2` — description
- **Returns**: description
### Usage Example
```[lang]
[minimal working code snippet from official docs]
Known Issues / Deprecations
- [relevant warning, deprecation notice, or common mistake]
## Sharp Edges
Known failure modes for this skill. Check these before declaring done.
| Failure Mode | Severity | Mitigation |
|---|---|---|
| Returning deprecated API without flagging it | HIGH | Must explicitly state "deprecated in X.Y, use Z instead" with replacement link |
| Wrong version docs returned when version specified | HIGH | Verify version match — if version-specific docs unavailable, state that explicitly |
| Skipping Context7 and going directly to web search | MEDIUM | Constraint: Context7 MCP → llms.txt → WebSearch — follow the priority chain |
| Not using ?topic= on llms.txt for focused queries | LOW | Topic parameter dramatically reduces noise — always append when query is specific |
| Returning docs without source URL | MEDIUM | Constraint: always include source URL so callers can verify |
## Done When
- Context7 attempted first (resolve-library-id + query-docs)
- If Context7 insufficient: top 1-3 official doc URLs fetched via WebFetch
- API signature extracted with parameter types and return type
- Minimal working code example included
- Deprecation/version notes included if applicable
- Source URL provided
- Documentation emitted in output format
## Returns
| Artifact | Format | Location |
|----------|--------|----------|
| API reference (signature + params) | Markdown | inline |
| Minimal working code example | Code block | inline |
| Deprecation / version notes | Markdown | inline |
| Source URL | Plain text | inline |
## Cost Profile
~300-600 tokens input, ~200-400 tokens output. Haiku. Fast lookup.
**Scope guardrail:** docs-seeker looks up documentation only — it does not apply changes, write code, or interpret whether the API fits the caller's use case.
Signals
- GitHub stars
- 86
- Forks
- 26
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
docs-seeker-rune-kit- Source
- github.com/rune-kit/rune