Skills

Vc Docs Seeker

Search library/framework documentation via llms.txt (context7.com).

Install

npx skills add withkynam/vibecode-pro-max-kit --skill vc-docs-seeker -g -a claude-code -y
Category
Git and review
Updated
5mo ago
License
MIT
Context cost
Lightabout 922 tokens
Runs scripts
Yes, review before use

What it does

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

Documentation Discovery

Output style: Follow process/development-protocols/communication-standards.md, answer-first, plain language, no unexplained jargon, TL;DR on long responses.

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:

# 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 distribution (1 agent, 3 agents, 7 agents, phased)
  • Returns JSON with strategy
  • Zero-token execution

Workflow References

Topic-Specific Search - Fastest path (10-15s)

General Library Search - Comprehensive coverage (30-60s)

Read the whole SKILL.md on GitHub

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