How do I install the Ck:docs Seeker skill?

Run npx skillmds@latest add binjuhor/ck-docs-seeker in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Ck:docs Seeker safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Ck:docs Seeker?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Ck:docs Seeker free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Ck:docs Seeker?

binjuhor (@binjuhor) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Ck:docs Seeker by binjuhor — Agent Skill

Name: Ck:docs Seeker
Rating: 4.2 (5 reviews)
Author: binjuhor

File contents

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

Scripts first - Execute scripts instead of manual URL construction
Zero-token overhead - Scripts run without context loading
Automatic fallback - Scripts handle topic → general → error chains
Progressive disclosure - Load workflows/references only when needed
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 > .claude/skills/docs-seeker/.env > .claude/skills/.env > .claude/.env

See .env.example for configuration options.

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

Frequently asked questions

Ck:docs Seeker