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Found 8,332 Skills
AI perspective journaling - document daily experiences, emotions, and learnings from the agent's viewpoint. Use when asked about diary, journal entries, self-reflection, or documenting AI experiences. Creates structured daily entries capturing projects, wins, frustrations, learnings, and emotional states.
Multi-language Workers development with Rust, Python, and WebAssembly. Use when building Workers in languages other than JavaScript/TypeScript, or when integrating WASM modules for performance-critical code.
FastAPI production-grade best practices and guidelines for building scalable, high-performance web APIs. Covers project structure, async concurrency, Pydantic validation, dependency injection, and database patterns.
Official Notion Model Context Protocol Server for workspace interaction.
Check and configure UX testing infrastructure (Playwright, accessibility, visual regression)
Check for stale generated content and offer regeneration or promotion
Teaches AI assistants how to develop FlutterFlow apps using MCP tools. Use this skill when working with FlutterFlow projects, editing FF YAML, creating or inspecting pages and components, reading project configuration, or navigating FlutterFlow widget trees. It covers all 25 MCP tools for discovery, reading, editing, and settings. Triggers on: FlutterFlow, FF YAML, FF page, FF component, FF widget, FF theme, FF project.
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.
Creates a QA planning subtask tagged `qa-plan` using handoff-first context loading, lazy artifact reads, and compact JSON handoff output.
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).
Handles Depot CLI installation, authentication, login, project setup, organization management, and API access. Use when installing the Depot CLI, logging in with `depot login`, creating or managing Depot projects, configuring API tokens or OIDC trust relationships, setting up depot.json, managing organizations, resetting build caches, or using the Depot API/SDKs. Also use when the user asks about Depot authentication methods, token types, environment variables, or general Depot platform setup that isn't specific to container builds, GitHub Actions runners, or Depot CI.
コード・プラン・スコープを多角的にレビュー。品質の番人、参上。Use when user mentions reviews, code review, plan review, scope analysis, security, performance, quality checks, PRs, diffs, or change review. Do NOT load for: implementation work, new feature development, bug fixes, or setup.