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congdon1207/agents.md5 installs

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

How do I install this agent skill?

npx skills add https://github.com/congdon1207/agents.md --skill docs-seeker
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubfail

    The skill executes local Node.js scripts to fetch and analyze documentation from an external domain (context7.com). It creates a significant Indirect Prompt Injection surface by processing untrusted web content to determine agent strategies and explicitly accesses sensitive configuration files (.env) across multiple directory levels.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · No issues

  • Runlayerwarn

    1/17 files flagged

What does this agent skill do?

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:

# 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)

Repository Analysis - Fallback strategy

References

context7-patterns.md - URL patterns, known repositories

errors.md - Error handling, fallback strategies

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?"

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"

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 > .codex/skills/docs-seeker/.env > .codex/skills/.env > .codex/.env

See .env.example for configuration options.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/congdon1207/agents.md/docs-seeker">View docs-seeker on skillZs</a>