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docs-seeker

Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features/components/concepts), (2) Library/framework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
0
Hot score
74
Updated
March 20, 2026
Overall rating
C2.8
Composite score
2.8
Best-practice grade
S96.0

Install command

npx @skill-hub/cli install namdfang-claudfang-engineer-docs-seeker

Repository

namdfang/claudfang-engineer

Skill path: .claude/skills/docs-seeker

Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features/components/concepts), (2) Library/framework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy

Open repository

Best for

Primary workflow: Grow & Distribute.

Technical facets: Full Stack, Tech Writer.

Target audience: everyone.

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: namdfang.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install docs-seeker into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/namdfang/claudfang-engineer before adding docs-seeker to shared team environments
  • Use docs-seeker for development workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: docs-seeker
description: "Search technical documentation using executable scripts to detect query type, fetch from llms.txt sources (context7.com), and analyze results. Use when user needs: (1) Topic-specific documentation (features/components/concepts), (2) Library/framework documentation, (3) GitHub repository analysis, (4) Documentation discovery with automated agent distribution strategy"
version: 3.1.0
---

# Documentation Discovery via Scripts

## Overview

**Script-first** documentation discovery using llms.txt standard.

Execute scripts to handle entire workflow - no manual URL construction needed.

## Primary Workflow

**ALWAYS execute scripts in this order:**

```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)

**[Repository Analysis](./workflows/repo-analysis.md)** - Fallback strategy

## References

**[context7-patterns.md](./references/context7-patterns.md)** - URL patterns, known repositories

**[errors.md](./references/errors.md)** - Error handling, fallback strategies

**[advanced.md](./references/advanced.md)** - Edge cases, versioning, multi-language

## Execution Principles

1. **Scripts first** - Execute scripts instead of manual URL construction
2. **Zero-token overhead** - Scripts run without context loading
3. **Automatic fallback** - Scripts handle topic → general → error chains
4. **Progressive disclosure** - Load workflows/references only when needed
5. **Agent distribution** - Scripts recommend parallel agent strategy

## Quick Start

**Topic query:** "How do I use date picker in shadcn?"
```bash
node scripts/detect-topic.js "<query>"  # → {topic, library, isTopicSpecific}
node scripts/fetch-docs.js "<query>"    # → 2-3 URLs
# Read URLs with WebFetch
```

**General query:** "Documentation for Next.js"
```bash
node scripts/detect-topic.js "<query>"         # → {isTopicSpecific: false}
node scripts/fetch-docs.js "<query>"           # → 8+ URLs
cat llms.txt | node scripts/analyze-llms-txt.js -  # → {totalUrls, distribution}
# Deploy agents per recommendation
```

## Environment

Scripts load `.env`: `process.env` > `.claude/skills/docs-seeker/.env` > `.claude/skills/.env` > `.claude/.env`

See `.env.example` for configuration options.
docs-seeker | SkillHub