claudemem-orchestration
Multi-agent code analysis orchestration using claudemem. Share claudemem output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping.
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Multi-agent code analysis orchestration using claudemem. Share claudemem output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping.
This skill should be used when the user mentions "wrangler", "wrangler.toml", "wrangler.jsonc", "wrangler commands", "local development", "wrangler dev", "wrangler deploy", "wrangler publish", "secrets manageme...
This skill should be used when the user asks about "Workers AI", "AI models", "text generation", "embeddings", "semantic search", "RAG", "Retrieval Augmented Generation", "AI inference", "LLaMA", "Llama", "bge...
This skill should be used when the user asks about "R2", "D1", "KV", "Durable Objects", "Queues", "Vectorize", "Hyperdrive", "Workers Analytics", "Email Routing", "Browser Rendering", or discusses Cloudflare pl...
⚡ PRIMARY TOOL for: 'why is X broken', 'find bug source', 'root cause analysis', 'trace error', 'debug issue', 'find where X fails'. Uses claudemem v0.3.0 AST with context command for call chain analysis. GREP...
⚡ PRIMARY TOOL for: 'what's the architecture', 'system design', 'how are layers organized', 'find design patterns', 'audit structure', 'map dependencies'. Uses claudemem v0.3.0 AST structural analysis with Pag...
Common patterns for extracting and combining analytics data from GA4, GSC, and SE Ranking. Includes API patterns, rate limiting, caching, and error handling.
⛔ INTERCEPT TRIGGER: Automatically invoked BEFORE Read 3+ files OR Glob with broad patterns. Validates whether bulk file operations should be replaced with semantic search. Prevents token waste from sequential...
⚡ AUTO-INVOKE when user asks: 'audit', 'investigate', 'how does X work', 'find all', 'where is', 'trace', 'understand', 'map the codebase', 'comprehensive'. MUST run BEFORE Read/Glob when planning to read 3+ f...
⚡ PRIMARY TOOL for: 'how does X work', 'find implementation of', 'trace data flow', 'where is X defined', 'audit integrations', 'find all usages'. Uses claudemem v0.3.0 AST with callers/callees analysis. GREP/...
Interpret GA4, GSC, and SE Ranking data for content optimization. Provides benchmarks, status indicators, and actionable insights.
⚡ PRIMARY TOOL for: 'comprehensive audit', 'deep analysis', 'full codebase review', 'multi-perspective investigation', 'complex questions'. Combines ALL detective perspectives (architect+developer+tester+debug...
Reference guide for using PROXY_MODE with external AI models. Use when running multi-model reviews, understanding which agents support PROXY_MODE, or debugging external model integration issues.
This skill should be used when the user asks about "Workers API", "fetch handler", "Workers runtime", "request handling", "response handling", "Workers bindings", "environment variables in Workers", "Workers co...
Intelligently debug and fix bugs with a repro-first approach. Use when the user reports a bug, unexpected behavior, or asks to fix an issue. Establishes reproducible test cases before fixing.
Read project documentation from ./docs with access logging. Use when you need to consult documentation, understand architecture, or learn about project components. Tracks doc usage and helpfulness.
Provides guidelines and principles for bridging the gap between simulated robotics environments and real-world hardware deployment in Physical AI.
Generate working Python/rclpy code examples for Physical AI & Humanoid Robotics textbook with tier-specific variants (Simulation/Jetson/Robot).
Vision-Language-Action model integration patterns for cognitive robotics with ROS 2.
Structure for creating hands-on exercises in the Physical AI textbook.
Build production-grade UI/UX with React (Next.js, Docusaurus), CSS architecture (Tailwind, Modules, Global), animations, theming, performance optimization, state management, and testing. Use when creating React...
Provides comprehensive guidelines for writing and formatting MDX content, frontmatter, and Docusaurus-specific components for the Physical AI & Humanoid Robotics textbook.
NVIDIA Isaac Sim and Isaac ROS integration patterns for Physical AI applications.
Authoritative guidelines for writing production-grade ROS 2 (Humble) Python 3.11+ code (leveraging 3.12+ features where compatible) for Physical AI applications.
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