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Found 2,231 Skills
Financial Hot Topic Selection Tool that obtains hot news through its built-in data crawling layer, and intelligently filters high-quality topics that can be associated with investment and financial management. Suitable for financial content creation scenarios that need to guide securities account opening and fund investment.
End-of-session reflection. Extracts memories, suggests updates to about-taylor.md and CLAUDE.md. Run before ending a long session or when context is getting full. Triggers on "debrief", "extract memories", "session summary".
Full RPI lifecycle orchestrator. Research → Plan → Pre-mortem → Crank → Vibe → Post-mortem. One command, sequential skill invocations with human gates and hands-free validation. Triggers: "rpi", "full lifecycle", "end to end", "research to production".
Build single-agent and multi-agent systems using Google's Agent Development Kit (ADK) in Python, Java, Go, or TypeScript. Use when creating AI agents with ADK, designing multi-agent architectures, implementing agent tools, configuring agent callbacks, managing agent state, orchestrating sequential/parallel/loop agent workflows, or when the user mentions ADK, google-adk, google agent development kit, agentic AI with Gemini, or agent orchestration with Google tools. Also use when setting up ADK projects, writing agent tests, deploying agents, or integrating MCP tools with ADK.
Activates when the user asks about Agent Skills, wants to find reusable AI capabilities, needs to install skills, or mentions skills for Claude. Use for discovering, retrieving, and installing skills.
Use this agent for audits, debugging nasty bugs, deep research, getting second opinions on approaches, reviewing commits for correctness, or analyzing complex problems. Invoke when you need advanced reasoning about difficult issues. Use PROACTIVELY when encountering complex bugs, architectural decisions, or when a thorough review would prevent future issues.
Guidance for working with the Beltic KYA (Know Your Agent) ecosystem - a credential-based trust framework for AI agents. Use when: (1) Working in any Beltic repository (beltic-spec, beltic-cli, beltic-sdk, fact-python, kya-platform, wizard, nasa), (2) Implementing agent credential signing/verification, (3) Using @belticlabs/kya SDK or beltic-sdk Python, (4) Understanding agent safety certification, (5) Working with verifiable credentials for AI. Triggers on: Beltic CLI commands, agent credentials, HTTP message signatures (RFC 9421), safety scores, KYB tier verification, trust chain validation.
Use this skill to work with Microsoft Foundry (Azure AI Foundry): deploy AI models from catalog, build RAG applications with knowledge indexes, create and evaluate AI agents. USE FOR: Microsoft Foundry, AI Foundry, deploy model, model catalog, RAG, knowledge index, create agent, evaluate agent, agent monitoring. DO NOT USE FOR: Azure Functions (use azure-functions), App Service (use azure-create-app).
Goal-based workflow orchestration - routes tasks to specialist agents based on user goals
Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.
Safe experimentation framework for AI agents. Creates isolated sandbox environments for trying new features, testing approaches, and exploring solutions without polluting the main codebase. USE WHEN: Agent needs to try something uncertain, explore multiple approaches, test a new library, prototype a feature, or run a technical spike before committing to implementation. PRIMARY TRIGGERS: "experiment with" = Setup sandbox + run experiment "try this approach" = Quick experiment in sandbox "spike" / "POC" / "prototype" = Time-boxed technical investigation "tinker" / "tinkering mode" = Enter experimentation workflow "explore options" = Multi-approach comparison in sandbox NOT FOR: Debugging (use debugger), testing (use test runner), or committed feature work (use git branches). DIFFERENTIATOR: Unlike git branches (for committed direction), tinkering is for "I don't know if this will work" exploration. Try 5 things in sandbox before committing to a branch. Faster feedback, zero codebase pollution.
Generates iterable checklist PROMPT files for Ralph Loop from plan files or current context, and provides the /ralph-loop execution command.