Total 34,666 skills
Showing 12 of 34666 skills
Systematically diagnose and resolve bugs through conversational investigation and root cause analysis
Scaffold, status-check, and manage specification directories. Handles auto-incrementing IDs, README tracking, phase transitions, and decision logging in docs/specs/. Used by both specify and implement workflows.
Provides comprehensive guidance for NestJS using the official documentation. Use when the user asks about NestJS architecture, controllers, providers, modules, middleware, guards, pipes, interceptors, dependency injection, GraphQL, WebSockets, microservices, OpenAPI/Swagger, security, or testing.
Enterprise SaaS frontend — Tailwind v4, shadcn/ui, Next.js App Router or Vite SPA, accessibility, responsive design, component patterns. Use when: React component, Next.js page, frontend UI, Tailwind, shadcn, accessibility, a11y, responsive design, form validation, server component, client component, design system, dark mode, SaaS UI, dashboard, pricing page, enterprise UI, data table, landing page, Vite, React Router, SPA, single page app.
Development best practices and project patterns. Use when starting projects, setting up CLAUDE.md, coding TypeScript/Next.js/React/Supabase, implementing AI flows, data fetching, testing, deployment, git workflows, browser automation, centralized configuration, or Tailwind CSS v4.
Work with spoint - a multiplayer physics game server SDK. Scaffolds apps locally, runs engine from npm package.
Configures Depot-managed GitHub Actions runners as a drop-in replacement for GitHub-hosted runners. Use when setting up or migrating GitHub Actions workflows to use Depot runners, choosing runner sizes (CPU/RAM), configuring runs-on labels, setting up ARM or Windows or macOS runners, troubleshooting GitHub Actions runner issues, configuring egress filtering, using Depot Cache with GitHub Actions, or running Dagger/Dependabot on Depot runners. Also use when the user mentions depot-ubuntu, depot-windows, depot-macos runner labels, or asks about faster/cheaper GitHub Actions runners.
Configures and runs Depot remote container builds using `depot build` and `depot bake`. Use when building Docker images, creating Dockerfiles with Depot, pushing images to registries, building multi-platform/multi-arch images (linux/amd64, linux/arm64), debugging container build failures, optimizing Dockerfile layer caching, using docker-bake.hcl or docker-compose builds, or migrating from `docker build` / `docker buildx build` to Depot. Also use when the user mentions depot build, depot bake, container builds, image builds, or asks about Depot's build cache, build parallelism, or ephemeral registry.
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
Analyzes an MLflow session — a sequence of traces from a multi-turn chat conversation or interaction. Use when the user asks to debug a chat conversation, review session or chat history, find where a multi-turn chat went wrong, or analyze patterns across turns. Triggers on "analyze this session", "what happened in this conversation", "debug session", "review chat history", "where did this chat go wrong", "session traces", "analyze chat", "debug this chat".
Synthesize multiple inputs into a concise one-page executive summary (under 500 words). Use when a PM needs help with one-pager.
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).