Skill UI

Build production-ready FastAPI projects with async patterns, dependency injection, middleware, and error handling. Ideal for new Python REST APIs, microservices, and high-performance web backends.

This skill provides functional programming patterns for building type-safe and testable backend services using fp-ts in Node.js or Deno environments. It covers dependency injection, service composition, and handling typed backend errors with ReaderTaskEither. Ideal for developers refactoring legacy code or implementing functional architecture principles in modern JavaScript runtimes.

This skill acts as an expert dependency manager, specializing in planning and executing safe, incremental upgrades for project dependencies. It provides comprehensive risk assessment, compatibility analysis, step-by-step migration guides, and robust testing/rollback plans to ensure system stability during major framework updates.

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).

Manage tasks with the YYLO Ledger CLI: create, list, search, get, mark, update, archive and merge tasks with dependency tracking, ready ordering, cold archive packs and opt-in cross-project routing.

Statically audit MCP configuration files for mutable npm/npx package references before approval or in CI. Classifies version selectors, flags drift risk, recommends exact-version pinning, and produces bounded reports without ever executing discovered MCP servers.

Secure AI model supply chains with artifact signing, provenance attestation, SBOM generation, dependency controls, and trusted model promotion. Use for verifying model integrity, meeting SLSA/SOC2 compliance, and protecting against tampering and compromised dependencies.

Expert in monorepo architecture, build systems, and dependency management at scale. Masters Nx, Turborepo, Bazel, and Lerna for efficient multi-project development. Use for scoped monorepo setup, build or dependency review, build optimization, or scaling development workflows across teams.

Builds a deterministic Software Graph from TypeScript repositories and exposes it via CLI, MCP server, and agent skills for evidence-backed architecture review, request tracing, impact analysis, and dependency topology inspection before searching source files directly.

This skill provides a systematic pipeline for safely executing large-scale code refactors across multiple files or subsystems. It first performs parallel, dependency-aware analysis to map the entire scope, synthesizing a single, actionable plan. The process then breaks the work into independent 'work packets,' which are executed sequentially or in parallel by specialized worker agents, ensuring strict dependency management and behavior parity throughout the entire process.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

This skill acts as an expert architect to generate complete, production-ready Python project structures. It supports various modern architectures, including FastAPI, Django (full-stack), standalone libraries, and CLI tools. It ensures adherence to best practices, includes dependency management (uv, pip), type hinting, and comprehensive testing skeletons.