Loading...
Loading...
Found 10,013 Skills
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
Design and coordinate multi-agent systems where specialized agents work together to solve complex problems. Covers agent communication, task delegation, workflow orchestration, and result aggregation. Use when building coordinated agent teams, complex workflows, or systems requiring specialized expertise across domains.
Jeffrey Emanuel's comprehensive markdown planning methodology for software projects. The 85%+ time-on-planning approach that makes agentic coding work at scale. Includes exact prompts used.
Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configuration and usage mistakes.
Plan-spec-implement workflow for structured development. Only use when explicitly directed by user or when mentioned in project AGENTS.md file. Generates ephemeral plans in ~/.dot-agent/, applies specs to project docs, then implements test-first.
Develop AI agents, tools, and workflows with Mastra v1 Beta and Hono servers. This skill should be used when creating Mastra agents, defining tools with Zod schemas, building workflows with step data flow, setting up Hono API servers with Mastra adapters, or implementing agent networks. Keywords: mastra, hono, agent, tool, workflow, AI, LLM, typescript, API, MCP.
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)
Create and refine OpenCode agents via guided Q&A. Use proactively for agent creation, performance improvement, or configuration design. Examples: - user: "Create an agent for code reviews" → ask about scope, permissions, tools, model preferences, generate AGENTS.md frontmatter - user: "My agent ignores context" → analyze description clarity, allowed-tools, permissions, suggest improvements - user: "Add a database expert agent" → gather requirements, set convex-database-expert in subagent_type, configure permissions - user: "Make my agent faster" → suggest smaller models, reduce allowed-tools, tighten permissions
Dynamic tool selection, composition, and error handling patterns for AI agents. Use when you need to efficiently leverage available tools and handle failures gracefully.
Task decomposition, goal-oriented planning, and adaptive execution strategies for AI agents. Use when facing complex multi-step tasks that require structured approach.
Full-featured Agent Skills management: Search 35+ skills, install locally, star favorites, update from sources. Use when looking for skills, installing new skills, or managing your skill collection.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.