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mk-docs-seeker

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

معلومات المصدر

المستودع
phuc-nt/kiro-agent-kit
آخر نشاط في المصدر
٦ سبتمبر ٢٠٢٦ في ١٠:٠١
لغة SKILL.md المكتشفة
الإنجليزية
النجوم
٠
التفرعات
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خيارات التثبيت

يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.

مراجعة ملفات المصدر

اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.

مستكشف الملفات
13 ملفات

عرض SKILL.md

SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
mk-docs-seeker
description
Search library/framework documentation via llms.txt (context7.com). Use for API docs, GitHub repository analysis, technical documentation lookup, latest library features.
category
dev-tools
keywords
["docs","llms-txt","api","library","context7"]
argument-hint
[library-name] [topic]
metadata
{"author":"my-kit","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.
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