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skills/ck-docs-seeker/SKILL.md
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skills/ck-docs-seeker/SKILL.md
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---
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name: ck-docs-seeker
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description: Search library and framework documentation via llms.txt standard. Use for API docs lookup, GitHub repository analysis, technical documentation discovery, latest library features, context7 integration.
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---
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# ck-docs-seeker
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Script-first documentation discovery using the llms.txt standard via context7.com. Fetch documentation for any library or framework without manual URL construction.
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## When to Use
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- Looking up API documentation for a specific library
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- Finding the latest features or syntax for a framework
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- Analyzing a GitHub repository's documentation
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- Before implementing with an unfamiliar library
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- When the local codebase docs are insufficient
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## Don't Use When
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- Searching local project files — use `ck-scout` instead
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- General web research on a broad topic — use `ck-research`
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- The documentation is already loaded in context
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## Primary Workflow
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Always execute scripts in this order from the `ck-docs-seeker` skill directory:
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```bash
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# 1. Detect query type (topic-specific vs general)
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node scripts/detect-topic.js "<user query>"
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# 2. Fetch documentation using script output
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node scripts/fetch-docs.js "<user query>"
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# 3. Analyze results (if multiple URLs returned)
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cat llms.txt | node scripts/analyze-llms-txt.js -
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```
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Scripts handle URL construction, fallback chains, and error handling automatically.
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## Scripts
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**`detect-topic.js`** — Classify query type
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- Identifies topic-specific vs general queries
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- Extracts library name + topic keyword
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- Returns JSON: `{topic, library, isTopicSpecific}`
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**`fetch-docs.js`** — Retrieve documentation
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- Constructs context7.com URLs automatically
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- Handles fallback: topic → general → error
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- Outputs llms.txt content or error message
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**`analyze-llms-txt.js`** — Process llms.txt
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- Categorizes URLs (critical/important/supplementary)
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- Recommends agent distribution strategy
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- Returns JSON with strategy
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## Examples
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**Topic-specific query:** "How do I use date picker in shadcn?"
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```bash
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node scripts/detect-topic.js "<query>" # → {topic, library, isTopicSpecific: true}
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node scripts/fetch-docs.js "<query>" # → 2-3 URLs
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# Fetch URLs with web fetch tool
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```
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**General query:** "Documentation for Next.js"
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```bash
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node scripts/detect-topic.js "<query>" # → {isTopicSpecific: false}
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node scripts/fetch-docs.js "<query>" # → 8+ URLs
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cat llms.txt | node scripts/analyze-llms-txt.js - # → distribution strategy
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# Deploy parallel agents per recommendation
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```
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## Execution Principles
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1. **Scripts first** — run scripts instead of manual URL construction
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2. **Zero-token overhead** — scripts run as commands without loading content
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3. **Automatic fallback** — scripts handle topic → general → error chains
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4. **Progressive disclosure** — load only what's needed
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5. **Agent distribution** — scripts recommend parallel agent strategy for large docs
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## Don't Use When
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- The skill directory or scripts are not available in the environment
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- Simple, single-page documentation is already at a known URL — fetch directly
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