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Found 11,838 Skills
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.
Invoke when the user asks to review, check, audit, or look over Qt6 C++ code — or suggest before committing. Runs deterministic linting (60+ rules) then six parallel deep- analysis agents covering model contracts, ownership, threading, API correctness, error handling, and performance. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only — never modifies code.
ELFA AI — real-time crypto social intelligence and automated condition-engine skills for AI agents. Track trending tokens, surface narratives, search mentions, run market analysis, and build automated trigger-based workflows.
Run team-based orchestration for agent squads using work items, ownership, agent Kanban, merge gates, and control pane handoffs.
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).
Build, modify, debug, and deploy agents with Agentforce Agent Script. TRIGGER when: user creates, modifies, or asks about .agent files or aiAuthoringBundle metadata; changes agent behavior, responses, or conversation logic; designs agent actions, tools, subagents, or flow control; writes or reviews an Agent Spec; previews, debugs, deploys, publishes, or tests agents; uses Agent Script CLI commands (sf agent generate/preview/publish/test). DO NOT TRIGGER when: Apex development, Flow building, Prompt Template authoring, Experience Cloud configuration, or general Salesforce CLI tasks unrelated to Agent Script.
Generate AgentforcePlatformTracingSettings metadata to enable or disable Agentforce agent execution trace spans flowing to Data Cloud. Use this skill for any AgentforcePlatformTracingSettings metadata work. TRIGGER when: user mentions Agentforce tracing, agent trace spans, Data Cloud tracing, AgentforcePlatformTracingSettings, platform observability tracing, enable agent tracing, wants agent execution spans in Data Cloud, mentions .settings-meta.xml for AgentforcePlatformTracing, or asks about enabling observability for Agentforce agents. DO NOT TRIGGER when: user wants Platform Tracing for TraceSpanEvent (use platform-tracing-configure), wants to query or analyze existing agent trace data in Data Cloud (use agentforce-observe), wants Event Log Files or ELF configuration, wants Change Data Capture (use integration-eventing-cdc-configure), or wants ManagedEventSubscription (use integration-eventing-subscription-configure).
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
AI agent with retrieval tool for document Q&A using RAG and LangGraph.
Guides the agent through building LLM-powered applications with LangChain and stateful agent workflows with LangGraph. Triggered when the user asks to "create an AI agent", "build a LangChain chain", "create a LangGraph workflow", "implement tool calling", "build RAG pipeline", "create a multi-agent system", "define agent state", "add human-in-the-loop", "implement streaming", or mentions LangChain, LangGraph, chains, agents, tools, retrieval augmented generation, state graphs, or LLM orchestration.
Generate project-level AGENTS.md guides that capture conventions, workflows, and required follow-up tasks. Use when a repository needs clear agent onboarding covering structure, tooling, testing, task flow, README expectations, and conventional commit summaries.
Recovery protocols when agent is stuck—escalate to new agent, migrate context to new session, or reset mid-conversation.