# Vc Docs Seeker

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

- Repository: https://github.com/withkynam/vibecode-pro-max-kit (1164 stars)
- Category: Git and review
- License: MIT
- Last updated: 2026-06-21
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add withkynam/vibecode-pro-max-kit --skill vc-docs-seeker -g -a claude-code -y`
Codex: `npx skills add withkynam/vibecode-pro-max-kit --skill vc-docs-seeker -g -a codex -y`
Cursor: `npx skills add withkynam/vibecode-pro-max-kit --skill vc-docs-seeker -g -a cursor -y`
Gemini CLI: `npx skills add withkynam/vibecode-pro-max-kit --skill vc-docs-seeker -g -a gemini-cli -y`

## Description

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

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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:**

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

## Workflow References

**[Topic-Specific Search](./workflows/topic-search.md)** - Fastest path (10-15s)

**[General Library Search](./workflows/library-search.md)** - Comprehensive coverage (30-60s)

The rest: https://github.com/withkynam/vibecode-pro-max-kit/blob/HEAD/.claude/skills/vc-docs-seeker/SKILL.md