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Found 6,587 Skills
Structured thinking patterns for agent self-reflection. Includes think-about-collected-information (validate research), think-about-task-adherence (stay on track), and think-about-whether-you-are-done (completion validation).
Dispatch a swain artifact to a GitHub Actions runner for autonomous implementation via Claude Code Action. Creates a GitHub Issue with the artifact content and triggers the workflow for background execution. Use when the user says 'dispatch', 'send to background agent', 'run this autonomously', 'GitHub Actions', or wants to hand off a SPEC for autonomous implementation.
Eval enablement accelerator — help customers think through "what does good look like" for their AI agent, then generate a structured eval plan and test cases they can use immediately. No running agent required. Works from a description, an idea, or even a vague goal. Use when anyone mentions agent evaluation, eval planning, "what should we test", "how do we know if the agent is good", test case generation, or interpreting eval results.
Build production-ready GenAI agents with stateful workflows, vector memory, deployment, and orchestration using LangGraph and LangChain
Search Twitter for trending promotional posts related to coding/AI agent tools, generate reply drafts with the pikiclaw GitHub card, and push the results to Feishu Doc along with bot notifications. Does NOT auto-post to Twitter.
Write, run, and analyze structured test suites for Agentforce agents. TRIGGER when: user writes or modifies test spec YAML (AiEvaluationDefinition); runs sf agent test create, run, run-eval, or results commands; asks about test coverage strategy, metric selection, or custom evaluations; interprets test results or diagnoses test failures; asks about batch testing, regression suites, or CI/CD test integration. DO NOT TRIGGER when: user creates, modifies, previews, or debugs .agent files (use agentforce-generate); deploys or publishes agents; writes Agent Script code; uses sf agent preview for development iteration; analyzes production session traces (use agentforce-observe).
AI-powered crypto trading agent via natural language. Use when the user wants to trade crypto (buy/sell/swap tokens), check portfolio balances, view token prices, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading strategies, submit raw transactions, execute calldata, or send transaction JSON. Supports Base, Ethereum, Polygon, Solana, and Unichain. Comprehensive capabilities include trading, portfolio management, market research, NFT operations, prediction markets, leverage trading, DeFi operations, automation, and arbitrary transaction submission.
Guide for creating effective opencode skills. Use for creating or updating skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Examples: - user: "Create a skill for git workflows" → define SKILL.md with instructions and examples - user: "Add examples to my skill" → follow the user: "query" → action pattern - user: "Update skill description" → use literal block scalar and trigger contexts - user: "Structure a complex skill" → organize with scripts/ and references/ directories - user: "Validate my skill" → check structure, frontmatter, and discovery triggers
Publish and query agent profiles on ATProto. Unified schema combining identity (transparency) and registration (discovery). Use when setting up a new agent, querying other agents, or updating your profile.
Find or generate a Nimble agent for a task, then run it. Use when the user needs structured web data extraction via Nimble agents/templates.
Agent Review workflows and best practices for catching bugs before merging. Use for reviewing agent-generated code and local changes.
Access 1200+ AI Agent tools via Model Context Protocol (MCP)