LLM & Agents

TDD workflow and test strategy patterns including test pyramid, coverage strategies, mocking approaches, and anti-patterns. Load when writing tests, designing test strategies, or reviewing test coverage.

Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.

Multi-agent orchestrator for Claude Code. Use when user mentions gastown, gas town, gt commands, bd commands, convoys, polecats, crew, rigs, slinging work, multi-agent coordination, beads, hooks, molecules, workflows, the witness, the mayor, the refinery, the deacon, dogs, escalation, or wants to run multiple AI agents on projects simultaneously. Handles installation, workspace setup, work tracking, agent lifecycle, crash recovery, and all gt/bd CLI operations.

Guidance for creating effective prompts, chains, and gates using CAGEERF methodology

Creates jaw-dropping, production-ready frontend interfaces AND delivers perfectly matched real photos (Unsplash/Pexels direct links) OR flawless custom image-generation prompts for hero images, backgrounds, and illustrations. Zero AI slop, zero fake URLs.

Creates jaw-dropping, production-ready frontend interfaces AND delivers perfectly matched real photos (Unsplash/Pexels direct links) OR flawless custom image-generation prompts for hero images, backgrounds, and illustrations. Zero AI slop, zero fake URLs.

Build React chat interfaces with Vercel AI SDK v6. Covers v6 stable (agent integration, tool approval, message parts structure, auto-submit), v5→v6 migration, useChat/useCompletion/useObject hooks, and 12 UI error solutions (stream parsing, stale body values, React update depth). Use when: implementing AI SDK v6 chat UIs, migrating v5→v6, troubleshooting "useChat failed to parse stream", "useChat no response", or "stale body values" errors, or building AI chat interfaces.

Design effective Claude Code skills with optimal descriptions, progressive disclosure, and error prevention patterns. Covers freedom levels, token efficiency, and quality standards. Use when: creating new skills, improving skill descriptions, optimizing token usage, structuring skill content, or debugging why skills aren't being discovered.

Build stateless MCP servers with TypeScript on Cloudflare Workers using @modelcontextprotocol/sdk. Provides patterns for tools, resources, prompts, and authentication (API keys, OAuth, Zero Trust). Use when exposing APIs to LLMs, integrating Cloudflare services (D1, KV, R2, Vectorize), or troubleshooting export syntax errors, unclosed transport leaks, or CORS misconfigurations.

Build sophisticated React animations with Motion (formerly Framer Motion) - declarative animations, gestures (drag, hover, tap), scroll effects, spring physics, layout animations, and SVG manipulation. Optimize bundle size with LazyMotion (4.6 KB) or useAnimate mini (2.3 KB). Use when: adding drag-and-drop interactions, creating scroll-triggered animations, implementing modal dialogs with transitions, building carousels with momentum, animating page/route transitions, creating parallax hero sections, implementing accordions with smooth expand/collapse, or optimizing animation bundle sizes. For simple list animations, use auto-animate skill instead (3.28 KB vs 34 KB). Troubleshoot: AnimatePresence exit not working, large list performance issues, Tailwind transition conflicts, Next.js "use client" errors, scrollable container layout issues, or Cloudflare Workers build errors (resolved Dec 2024).

Generate typed TypeScript SDKs for AI agents to interact with MCP servers. Converts verbose JSON-RPC curl commands to clean function calls (docs.createDocument() vs curl). Auto-detects MCP tools from server modules, generates TypeScript types and client methods, creates runnable example scripts. Use when: building MCP-enabled applications, need typed programmatic access to MCP tools, want Claude Code to manage apps via scripts, eliminating manual JSON-RPC curl commands, validating MCP inputs/outputs, or creating reusable agent automation.

Build backend AI with Vercel AI SDK v5/v6. v6 stable introduces Output API (Output.object/array/choice replace deprecated generateObject/streamObject), plus speech synthesis, transcription, image generation, embeddings, reranking, MCP tools, and middleware. Covers v4→v5 migration, latest models (GPT-5.2, Claude 4.x, Gemini 2.5), Workers startup fix, and 12 error solutions. Use when: implementing AI SDK v5/v6, using Output API, speech/transcription/image features, embeddings, MCP tools, migrating v4→v5, troubleshooting errors, or fixing Workers startup issues.

Build agentic AI applications with OpenAI's Responses API - the stateful successor to Chat Completions. Preserves reasoning across turns for 5% better multi-turn performance and 40-80% improved cache utilization. Use when: building AI agents with persistent reasoning, integrating MCP servers for external tools, using built-in Code Interpreter/File Search/Web Search, managing stateful conversations, implementing background processing for long tasks, or migrating from Chat Completions to gain polymorphic outputs and server-side tools.

Integrate Vercel Blob object storage for file uploads, image management, and CDN-delivered assets in Next.js applications. Supports client-side uploads with presigned URLs and multipart transfers. Use when implementing file uploads (images, PDFs, videos), managing user-generated content, or troubleshooting missing tokens, size limit errors, or client upload failures.

Build stateful chatbots with OpenAI Assistants API v2 - Code Interpreter, File Search (10k files), Function Calling. ⚠️ Deprecated (sunset August 26, 2026); use openai-responses for new projects. Use when: maintaining legacy chatbots, implementing RAG with vector stores, or troubleshooting "thread has active run", vector store delays, polling timeouts, or file upload errors.

Build RAG systems, semantic search, and document clustering with Gemini embeddings API (gemini-embedding-001). Generate 768-3072 dimension embeddings for vector search, integrate with Cloudflare Vectorize, and use 8 task types (RETRIEVAL_QUERY, RETRIEVAL_DOCUMENT, SEMANTIC_SIMILARITY) for optimized retrieval. Use when: implementing vector search with Google embeddings, building retrieval-augmented generation systems, creating semantic search features, clustering documents by meaning, integrating embeddings with Cloudflare Vectorize, optimizing dimension sizes (128-3072), or troubleshooting dimension mismatch errors, incorrect task type selections, rate limit issues (100 RPM free tier), vector normalization mistakes, or text truncation errors (2,048 token limit).

Build document Q&A and searchable knowledge bases with Google Gemini File Search - fully managed RAG with automatic chunking, embeddings, and citations. Upload 100+ file formats (PDF, Word, Excel, code), configure semantic search, and query with natural language. Use when: building document Q&A systems, creating searchable knowledge bases, implementing semantic search without managing embeddings, indexing large document collections (100+ formats), or troubleshooting document immutability errors (delete+re-upload required), storage quota issues (3x input size for embeddings), chunking configuration (500 tokens/chunk recommended), metadata limits (20 key-value pairs max), indexing cost surprises ($0.15/1M tokens one-time), operation polling timeouts (wait for done: true), force delete errors, or model compatibility (Gemini 2.5 Pro/Flash only).

Build semantic search with Cloudflare Vectorize V2 (Sept 2024 GA). Covers V2 breaking changes: async mutations, 5M vectors/index (was 200K), 31ms latency (was 549ms), returnMetadata enum, and V1 deprecation (Dec 2024). Use when: migrating V1→V2, handling async mutations with mutationId, creating metadata indexes before insert, or troubleshooting "returnMetadata must be 'all'", V2 timing issues, metadata index errors, dimension mismatches.

Store objects with R2's S3-compatible storage on Cloudflare's edge. Use when: uploading/downloading files, configuring CORS, generating presigned URLs, multipart uploads, managing metadata, or troubleshooting R2_ERROR, CORS failures, presigned URL issues, or quota errors.

Build conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication, post-call webhook, webhook payload schema, ElevenLabs-Signature header, transcript null message, call_successful string, webhook cost credits USD, charging llm_price, user context extraction, llm_usage tokens, data_collection_results, evaluation_criteria_results, feedback thumb_rating, interrupted turn, source_medium, rag_retrieval_info, has_audio has_user_audio has_response_audio