القائمة
Search library/framework documentation via llms.txt (context7.com). Use for API docs, GitHub repository analysis, technical documentation lookup, latest library features.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Generate images via Nano Banana with 129 curated prompts. Mandatory validation interview refines style/mood/colors (use --skip to bypass). 3 modes: search, creative, wild. Styles: Ukiyo-e, Bento grid, cyberpunk, cinematic, vintage patent.
Review code quality, receive feedback with technical rigor, verify completion claims. Use before PRs, after implementing features, when claiming task completion. Includes scout-based edge case detection.
Manage MCP servers - discover, analyze, execute tools/prompts/resources. Use for MCP integrations, intelligent tool selection, multi-server management, context-efficient capability discovery.
UI/UX design intelligence. 50 styles, 21 palettes, 50 font pairings, 20 charts, 9 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui). Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check UI/UX code. Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Styles: glassmorphism, claymorphism, minimalism, brutalism, neumorphism, bento grid, dark mode, responsive, skeuomorphism, flat design. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient. Integrations: shadcn/ui MCP for component search and examples.
Generate images via Nano Banana with 129 curated prompts. Mandatory validation interview refines style/mood/colors (use --skip to bypass). 3 modes: search, creative, wild. Styles: Ukiyo-e, Bento grid, cyberpunk, cinematic, vintage patent.
Analyze images/audio/video with Gemini API (better vision than Claude). Generate images (Imagen 4), videos (Veo 3). Use for vision analysis, transcription, OCR, design extraction, multimodal AI.
| name | 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. |
| version | 3.1.0 |
Script-first documentation discovery using llms.txt standard.
Execute scripts to handle entire workflow - no manual URL construction needed.
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.
detect-topic.js - Classify query type
{topic, library, isTopicSpecific}fetch-docs.js - Retrieve documentation
analyze-llms-txt.js - Process llms.txt
Topic-Specific Search - Fastest path (10-15s)
General Library Search - Comprehensive coverage (30-60s)
Repository Analysis - Fallback strategy
context7-patterns.md - URL patterns, known repositories
errors.md - Error handling, fallback strategies
advanced.md - Edge cases, versioning, multi-language
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
Scripts load .env: process.env > .opencode/skills/docs-seeker/.env > .opencode/skills/.env > .opencode/.env
See .env.example for configuration options.