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Found 1,279 Skills
Measure and improve the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For deployment, use agent-platform-deploy.
Test PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.
Web scraping and search CLI returning clean Markdown from any URL (handles JS-rendered pages, SPAs). Use when user requests: (1) "search the web for X", (2) "scrape/fetch URL content", (3) "get content from website", (4) "find recent articles about X", (5) research tasks needing current web data, (6) extract structured data from pages. Outputs LLM-friendly Markdown, handles authentication via firecrawl login, supports parallel scraping for bulk operations. Automatically writes to .firecrawl/ directory. Triggers: web scraping, search web, fetch URL, extract content, Firecrawl, scrape website, get page content, web research, site map, crawl site.
Configure auto-configure Ollama when user needs local LLM deployment, free AI alternatives, or wants to eliminate hosted API costs. Trigger phrases: "install ollama", "local AI", "free LLM", "self-hosted AI", "replace OpenAI", "no API costs". Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Use when adding LangChain-based LLM routes or services in Python or Next.js stacks; pair with architect-stack-selector.
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
Official Firecrawl CLI skill for web scraping, search, crawling, and browser automation. Returns clean LLM-optimized markdown. USE FOR: - Web search and research - Scraping pages, docs, and articles - Site mapping and bulk content extraction - Browser automation for interactive pages Must be pre-installed and authenticated. See rules/install.md for setup, rules/security.md for output handling.
Orchestrate Chinese LLMs (DeepSeek, Qwen, Yi, Moonshot) through OpenRouter API with LangChain. Use when: openrouter, chinese llm, deepseek, qwen, moonshot, yi model, model routing, auto router, llm orchestration.
Route AI coding queries to local LLMs in air-gapped networks. Integrates Serena MCP for semantic code understanding. Use when working offline, with local models (Ollama, LM Studio, Jan, OpenWebUI), or in secure/closed environments. Triggers on local LLM, Ollama, LM Studio, Jan, air-gapped, offline AI, Serena, local inference, closed network, model routing, defense network, secure coding.
Multimodal media authentication and deepfake forensics. PRNU analysis, IGH classification, DQ detection, semantic forensics, and LLM-augmented sensemaking for the post-empirical era. Use when working with deepfake, media forensics, fake detection, synthetic media, prnu, image authentication, video verification, disinformation.
Use this skill when you need to test or evaluate LangGraph/LangChain agents: writing unit or integration tests, generating test scaffolds, mocking LLM/tool behavior, running trajectory evaluation (match or LLM-as-judge), running LangSmith dataset evaluations, and comparing two agent versions with A/B-style offline analysis. Use it for Python and JavaScript/TypeScript workflows, evaluator design, experiment setup, regression gates, and debugging flaky/incorrect evaluation results.
Omniscient APEX Ecosystem development skill. Triggers: apex code, omnihub development, tradeline build, aspiral feature, apex bug, fix apex, apex architecture, omnidash component, triforce guardian, man mode, apex security, apex test, armageddon test, apex deploy, apex optimize, semantic translation, web2 web3 bridge. Produces: zero-drift, first-pass success code for APEX OmniHub, TradeLine 24/7, aSpiral, and all connected applications. Compatible with all LLMs.