Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".
This skill should be used when conducting comprehensive research on any topic using the OpenAI Deep Research API. It automates prompt enhancement through interactive clarifying questions, saves research parameters, and executes deep research with web search capabilities. Use when the user asks for in-depth analysis, investigation, research summaries, or topic exploration.
Review and refine MCP skill descriptions to follow the agent skill specification, and record approved overrides in dev-swarm/mcp_descriptions.yaml. Use when the user asks to update one MCP skill description, all skills from a server, or all MCP skills.
Guide learning and deep understanding through proven methodologies (Socratic, Feynman, Problem-Based). Use when user says "help me understand", "teach me", "explain this", "learn about", "socratic", "feynman", "problem-based", "I don't understand", "confused about", "why does", or wants to truly grasp a concept.
Creates custom CCPM skills from request to deployment with proper templates, safety guardrails, and integration patterns. Auto-activates when user mentions "create skill", "custom workflow", "team specific", "extend CCPM", "codify team practice", or "reusable pattern". Guides through purpose definition (what skill does), activation triggers (when it runs), CCPM integration points, and safety rules. Provides three skill templates: Team Workflow (codify practices), Safety Enforcement (add checks), and Integration Skills (custom tools). Creates directory structure, frontmatter metadata, multi-phase instructions, and supporting docs. Tests skill activation before deployment and suggests improvements.
Design and orchestrate multi-agent systems. Use when building complex AI systems requiring specialization, parallel processing, or collaborative problem-solving. Covers agent coordination, communication patterns, and task delegation strategies.
Moonshot AI Kimi API - Trillion-parameter MoE model with 256K context, tool calling, and agentic capabilities for chat, coding, and autonomous task execution
Edit images with Gemini using the nanobanana CLI. Use when the user asks to transform or retouch images and wants concrete output files.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
Use when wanting to interact with any LLM - Explains available inference endpoints so the agent selects suitable models.
Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network. Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI, configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating with embeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, token limit exceeded, or neurons exceeded errors. Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai, workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers, vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded, neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono, ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai ve
AI-powered coding assistant providing inline suggestions, chat interface, code review, and autonomous coding agent across IDEs and GitHub.com
Explore ideas, validate concepts, and research broadly across technical, business, and market domains. Use when: (1) User has a new idea to explore, (2) Need to research a topic deeply, (3) Validating feasibility - technical, business, or market, (4) Learning and exploration without necessarily building anything, (5) User says 'research this' or 'explore this idea', (6) Brain dumping early thoughts before formal discussion. Creates research documents in docs/workflow/research/ that may feed into discussion or specification.
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
Discover new Runware AI models from documentation and implement providers. Use when: checking for new Runware models, implementing Runware providers, updating providers.md status, or working with Runware API integrations.
AI-driven deployment management using Dokploy MCP server for projects, applications, and databases
