Total 55,943 skills, AI & Machine Learning has 9312 skills
Showing 12 of 9312 skills
Implements tracker subtasks tagged `implement`, publishes/updates the PR, and routes review using handoff-first context loading, lazy artifact reads, and rework_mode support.
Instruments Python and TypeScript code with MLflow Tracing for observability. Triggers on questions about adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, or tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen). Examples - "How do I add tracing?", "How to instrument my agent?", "How to trace my LangChain app?", "Getting started with MLflow tracing", "Trace my TypeScript app"
Gemini CLI consultation workflow for coding agents. Use when technical tasks need Gemini consultation for decisions, planning, debugging, problem-solving, or pre-implementation guidance.
Reads invoice images and returns structured data. It can be called by other skills or directly by users.
Reads images of receipts, payment receipts, and Furusato Nozei donation receipts and returns structured data. It can be called from other skills or directly by users.
Build production-ready MCP servers using FastMCP v3. Guides research, scaffolding, tool/resource/prompt implementation, testing, and deployment. Targets FastMCP 3.0.0rc2 with Providers, Transforms, middleware, OAuth, and composition. Use when creating MCP servers, integrating APIs via MCP, converting OpenAPI specs or FastAPI apps, or troubleshooting FastMCP issues. NOT for building REST APIs, CLI tools, or non-MCP integrations.
Craft highly effective prompts for Nano Banana Pro (Gemini image generation). Use when generating images with Nano Banana Pro for any purpose including photorealistic portraits, product photography, creative experiments, e-commerce mockups, social media content, editorial layouts, 3D renders, era-specific aesthetics (Y2K, 2000s, 1990s), miniature/diorama effects, or any advanced image generation task. Provides proven prompt patterns, technical specifications, JSON structuring, identity preservation techniques, and style-specific templates.
Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration. If an experiment ID is available, it should be supplied as input to help determine the use case. Use when the user asks to get started with MLflow, set up tracking, add observability, or integrate MLflow into their project. Triggers on "get started with MLflow", "set up MLflow", "onboard to MLflow", "add MLflow to my project", "how do I use MLflow".
Code context using Exa. Finds real snippets and docs from GitHub, StackOverflow, and technical docs. Use when searching for code examples, API syntax, library documentation, or debugging help.
Discover trending Claude Code resources that are rising on GitHub right now
This skill enriches vague prompts with targeted research and clarification before execution. Should be used when a prompt is determined to be vague and requires systematic research, question generation, and execution guidance.
Discover patterns, rules, and interfaces through iterative analysis cycles. Use when analyzing business rules, technical patterns, security, performance, integration points, or domain-specific areas. Includes cycle pattern for discovery to documentation to review workflow.