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Found 13,237 Skills
Use when the user asks to "improve my agent", "self-improving agent", "auto-tune my agent", "iterate on my agent prompt", "fix my agent based on test results", "close the loop on agent quality", "auto-improve agent prompt", "use eval results to improve agent", "optimize my prompt based on failures", "rewrite my prompt", or describes agent self-improvement, prompt iteration from run results, or automated agent quality loops. Covers the full diagnose → propose → apply → re-validate loop for VAPI agents (squads + tool definitions) and for self-hosted agents (custom websocket servers, including the offline / pasted-prompt degenerate variant).
AI-powered social media agent with real browser automation for autonomous account operation
Adaptive multi-agent framework for automated data science tasks with planning, execution, and validation
Build and deploy autonomous AI agents with CowAgent - planning, memory, knowledge base, skills, and multi-channel support
Use when the user needs to perform multi-step operations with the MetaMask Agentic CLI such as onboarding, login, swapping tokens, bridging across chains, opening/closing/modifying perpetual positions, prediction market trading, or troubleshooting CLI issues.
Generate a CLAUDE.md or AGENT.md configuration file for Sui projects. Use when setting up a new Sui project, when user mentions "CLAUDE.md", "AGENT.md", "agent config", or when working on a Sui project that does not already have a CLAUDE.md or AGENT.md in the project root.
agentmemory configuration, environment variables, ports, and feature flags. Use when enabling a feature, changing ports, setting an API key, configuring auth, or explaining why a feature is off by default.
Used when executing implementation plans containing independent tasks in the current session
Declared architecture snapshot for one Agentforce agent: planner, topics, actions, flows, Apex, prompt templates, and NGA plugins. Renders a human-readable architecture document and Mermaid invocation graph from design-time metadata (not runtime audit rows). TRIGGER when user asks to describe, diagram, inventory, audit, document, or diff (e.g. v3 vs v5) the architecture / action tree / topic structure / tool inventory of a specific agent by agent API name in a specific org. DO NOT TRIGGER for runtime session traces, conversation transcripts, generation timings, or gateway audit chains — this skill reads design-time metadata only (use agentforce-d360-analyze for session traces).
Use this skill when the user asks to add, embed, integrate, configure, style, or remove an agent, chatbot, chat widget, conversation client, or AI assistant in a UI Bundle project. TRIGGER when: project contains a uiBundles/*/src/ directory and the task involves adding or modifying a chat widget, chatbot, or conversational AI; files under uiBundles/*/src/ import AgentforceConversationClient; user asks to add any chat or agent functionality to a page. DO NOT TRIGGER when: user wants to create a custom agent, chatbot, or chat widget component from scratch; the project has no uiBundles directory.
Guides agents to interactively discover customer requirements for live, bidirectional multi-agent AI systems that process continuous streams of multimodal data for real-time technical guidance and safety monitoring. Generates a custom Google Cloud solution that uses opinionated best practices and architecture guidance. Use when users need agentic assistance to design and create a multi-product solution in the cloud for live bidirectional multimodal streaming workloads.
Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.