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Found 11,863 Skills
Use to navigate and structure Markdown context with clear hierarchy and progressive disclosure. Follow explicit links to read only what’s needed and avoid scanning unrelated content.
Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: "build an agent", "create an agent", "get started", "new project", "agentcore create", "which framework", "Strands vs LangGraph", "hello world agent", "first agent", "create MCP server", "host MCP server", "agentcore dev", "dev server", "what port", "local development". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.
View spending policy on a Circle agent wallet — per-transaction, daily, weekly, and monthly USDC caps via the `circle` CLI. Use when the user wants to inspect current limits. Setting or resetting limits requires OTP confirmation in an interactive terminal session — the agent hands the user a verbatim command to run themselves; the OTP must never pass through agent storage. Mainnet-only — testnet chains are rejected. Triggers on: spending limit, spending policy, wallet limit, per-tx cap, daily cap, weekly cap, monthly cap, set spending limit, reset spending limit, wallet rules, spending cap, OTP confirmation.
Analyze production Agentforce agent behavior using session traces and Data Cloud. TRIGGER when: user queries STDM session data or Data Cloud trace records; investigates production agent failures, regressions, or performance issues; asks about session traces, conversation logs, or agent metrics; wants to reproduce a reported production issue in preview; runs findSessions or trace analysis queries. DO NOT TRIGGER when: user creates, modifies, or debugs .agent files during development (use developing-agentforce); writes or runs test specs (use testing-agentforce); uses sf agent preview for local development iteration; deploys or publishes agents.
Configure AI agents via the imperative SDK / REST API — for no-code dashboard setups, webhook-based tools, and knowledge bases.
Meta-skill: helps create an AGENTS.md for a new project by guiding the user through selecting the right profile from the agentic library and running the compose command. Also helps create a custom AGENTS.md from scratch when no profile fits. Invoked when the user asks to set up agent instructions, create AGENTS.md, or configure agents for a project.
Code Review Expert: Perform in-depth code reviews using context-isolated subagents, covering security vulnerabilities, performance optimizations, and production reliability
Track, optimize, and control token consumption across multi-agent systems. Covers budget allocation, real-time monitoring, cost attribution, per-agent limits, and proactive cost optimization for production LLM deployments.
Browser automation CLI for AI agents - fast native Rust tool for controlling Chrome with accessibility-first commands
Build RAG pipelines with Exa.ai for real-time web retrieval. Use when building retrieval-augmented generation, integrating Exa with LangChain, LlamaIndex, Vercel AI SDK, or implementing AI agents with web search capabilities. Triggers on: RAG pipeline, retrieval augmented generation, Exa LangChain, Exa LlamaIndex, ExaSearchRetriever, ExaSearchResults, Exa MCP, Exa tool calling, Claude tool use, AI agent web search, grounded generation, citation generation, fact checking, hallucination detection, OpenAI compatibility, chat completions.
Deep architectural knowledge of AI Agent Harness design patterns, implementation strategies, and Claude Code internals for building production-grade AI agents
Self-evolving autonomous agent framework with skill tree growth, browser/desktop/mobile control, and hierarchical memory system