vcdocs-seeker

Solid

Search library/framework documentation via llms.txt (context7.com). Use for API docs, GitHub repository analysis, technical documentation lookup, latest library features.

AI & Automation 852 stars 197 forks Updated 1 weeks ago MIT

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Quality Score: 94/100

Stars 20%
98
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Documentation Discovery ## Overview Use Context7 MCP as the default path for documentation lookup. The local scripts in this skill are fallback helpers for llms.txt-based discovery when Context7 does not cover the target cleanly. ## Primary Workflow **Default workflow: Context7 first** 1. Resolve the library with Context7. 2. Query the exact API/config/setup question with Context7. 3. Only fall back to the scripts below when Context7 coverage is missing, incomplete, or the user explicitly wants llms.txt/repository-oriented discovery. **Fallback script workflow:** ```bash # 1. DETECT query type (topic-specific vs general) node scripts/detect-topic.js "<user query>" # 2. FETCH documentation using script output node scripts/fetch-docs.js "<user query>" # 3. ANALYZE results (if multiple URLs returned) cat llms.txt | node scripts/analyze-llms-txt.js - ``` Scripts handle URL construction, fallback chains, and error handling automatically. ## Scripts **`detect-topic.js`** - Classify query type - Identifies topic-specific vs general queries - Extracts library name + topic keyword - Returns JSON: `{topic, library, isTopicSpecific}` - Zero-token execution **`fetch-docs.js`** - Retrieve documentation - Constructs context7.com URLs automatically - Handles fallback: topic → general → error - Outputs llms.txt content or error message - Zero-token execution **`analyze-llms-txt.js`** - Process llms.txt - Categorizes URLs (critical/important/supplementary) - Recommends agent d...

Details

Author
withkynam
Repository
withkynam/vibecode-pro-max-kit
Created
2 weeks ago
Last Updated
1 weeks ago
Language
JavaScript
License
MIT

Integrates with

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