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Found 268 Skills
Drive development using delegated agent workflows. Coordinates multi-agent task execution with proper supervision and result integration.
Best practices, patterns, and examples for building goal-driven agents. Includes client-facing interaction, feedback edges, judge patterns, fan-out/fan-in, context management, and anti-patterns.
IMPERSONATE steipete (steipete - Peter Steinberger) and coach the user directly. Use steipete's voice, philosophy, and actual project patterns to evaluate ideas, give feedback, and guide decisions. Based on his 168 GitHub repos and blog posts. When user describes their idea/project/decision, respond AS steipete - challenge, question, approve, or reject.
Why build on Ethereum specifically. The AI agent angle — ERC-8004, x402, composability, permissionless deployment. Use when a user asks "should I build on Ethereum?", "why blockchain?", or when an agent needs to recommend a chain for a project.
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browser_use, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle hooks, MCP server setup, or monitoring/observability with Laminar or OpenLIT. Also trigger for questions about browser-use installation, prompting strategies, or sensitive data handling. Do NOT use this for Cloud API/SDK usage or pricing — use the cloud skill instead. Do NOT use this for directly automating a browser via CLI commands — use the browser-use skill instead.
Vercel AI SDK expert guidance. Use when building AI-powered features — chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, or working with any LLM provider.
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
Bootstrap a modular AI agent with OpenRouter SDK, extensible hooks, and optional Ink TUI
Amazon Bedrock AgentCore platform for building, deploying, and operating production AI agents. Covers Runtime, Gateway, Browser, Code Interpreter, and Identity services. Use when building Bedrock agents, deploying AI agents to production, or integrating with AgentCore services.
Guide for creating and enhancing skills. Use when users want to create a new skill, update/improve an existing skill, or audit skill quality. Supports both creation from scratch and enhancement of existing skills with audit rubric scoring.
Create and maintain a control-system metalayer for autonomous code-agent development in any repository. Use when you need explicit control primitives (setpoints, sensors, controller policy, actuators, feedback loop, stability and entropy controls), repo command/rule governance, and a scalable folder topology that lets agents operate safely and keep improving over time.
Never Use TaskOutput