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Found 268 Skills
Build serverless TypeScript functions on Zavu Cloud — declare agents + tools in code with defineAgent / defineTool, deploy with `zavu deploy`, debug with `zavu agents executions`. Use this skill whenever the user wants code-driven AI agents, custom tool handlers, or event-driven business logic.
CLI and skills for building, evaluating, and deploying AI agents on Google Cloud's Gemini Enterprise Agent Platform using ADK
Structured learning roadmap for AI Agent development from LLM basics to multi-agent systems (bilingual Chinese/English)
Interactive sub-agent creation skill for Claude Code. Use when user wants to create a custom subagent or mentions needing a specialized agent for specific tasks. This skill guides the entire subagent creation process including identifier design, system prompt generation, skill/context selection, and writing properly formatted agent files to .claude/agents.
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Design, audit, and refactor production-safe agentic harnesses with provider-neutral best practices for tools, permissions, planning, context, and observability.
Bootstrap a fresh Ubuntu VPS into a complete multi-agent AI development environment with safety tools and coordination infrastructure in 30 minutes
Onboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle.
Scaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants to quickly build or try a Deep Agent locally.
Drives a disciplined explore → plan → implement → verify loop for changing an AI agent's behavior with confidence — whether fixing a reported failure or introducing a new requirement, business rule, or policy. Grounds the diagnosis in MLflow traces, codifies the desired behavior as a regression test suite (`mlflow.genai.evaluate` assertions in `@mlflow.test` pytest tests), and iterates the agent — not the test — until green, resisting quick system-prompt patches when the real fix is upstream (missing tool, retrieval source, or capability). Use whenever the user wants to fix or change how an agent behaves — e.g. "fix this issue in my agent", "this answer is wrong", "the agent is hallucinating", "improve my agent based on this trace", "make the agent do X instead of Y", "I want the agent to lead with/prioritize/recommend X", "new business rule: the agent should X", "always/never do X", "change the agent's default behavior" — or shares a trace they want addressed.
Build AI agents with Cloudflare Agents SDK on Workers + Durable Objects. Provides WebSockets, state persistence, scheduling, and multi-agent coordination. Prevents 23 documented errors. Use when: building WebSocket agents, RAG with Vectorize, MCP servers, or troubleshooting "Agent class must extend", "new_sqlite_classes", binding errors, WebSocket payload limits.
Guide for defining and using Claude subagents effectively. Use when (1) creating new subagent types, (2) learning how to delegate work to specialized subagents, (3) improving subagent delegation prompts, (4) understanding subagent orchestration patterns, or (5) debugging ineffective subagent usage.