Skill UI

This comprehensive guide covers advanced Dart 3 features, including pattern matching, exhaustive switch expressions, and records. Learn how to refactor complex if-else chains, perform type-safe destructuring from various data sources (maps, lists, records), and utilize modern control flow constructs for writing idiomatic, robust, and highly maintainable Dart code.

This guide provides comprehensive solutions for common Flutter runtime and layout errors, such as RenderFlex overflow, unbounded constraints, and improper state management (setState during build). It explains the cause, the specific error message, and provides actionable code fixes for various UI and state issues.

A comprehensive guide to disciplined version control using Git. It outlines best practices for atomic commits, descriptive message formatting (feat, fix, refactor), adopting trunk-based development, and managing feature branches. Use this whenever making code changes, committing, or coordinating complex work streams to ensure code stability and traceability.

A comprehensive guide for adhering to idiomatic Go code style. It covers best practices for line breaking, variable declaration, explicit initialization of composite types, and improving control flow clarity. Use this skill when reviewing or writing Go code to ensure maximum readability and maintainability, going beyond what automated linters can enforce.

This comprehensive guide provides best practices for creating, reviewing, and auditing documentation for Go projects. It covers writing principles (e.g., Intent over paraphrase, Concision), structuring documentation (godoc comments, README, CHANGELOG), and workflow orchestration for both libraries and CLI applications. Ideal for technical writers and developers ensuring code is discoverable and maintainable.

Defensive Golang guidance for avoiding panics, nil traps, append aliasing, overflow, float comparison bugs, and resource leaks. Useful for writing safer code and reviewing runtime risks.

A comprehensive guide for systematically diagnosing and fixing bugs, crashes, deadlocks, and performance issues in Go code. It covers debugging methodology, utilizing tools like Delve and pprof, detecting race conditions, and following the Golden Rules to find the root cause, ensuring robust and reliable Go development practices.

This CLI alias implements the PUA Loop protocol, designed for running structured, iterative verification cycles. It helps developers set up and manage complex coding tasks that require explicit verification commands and defined stop conditions. It serves as a powerful wrapper for AI coding assistants like Codex/Claude, ensuring robust and traceable development workflows.

Spec-Driven Development (SDD) is a structured methodology that mandates defining comprehensive specifications before writing any code. It guides users through a gated process: SPECIFY -> PLAN -> TASKS -> IMPLEMENT. This workflow ensures all assumptions are surfaced, requirements are concrete, and the final product has clear success criteria, minimizing ambiguity and architectural risk in large projects.

Test-Driven Development (TDD) is a software development process where tests are written before the actual implementation code. The core cycle involves three steps: RED (write a failing test), GREEN (write minimal code to pass the test), and REFACTOR (clean up the code while ensuring tests remain passing). This methodology is crucial for building robust, maintainable, and bug-free codebases, making it ideal for implementing new features or fixing bugs.

This meta-skill set provides a structured framework covering the entire software development lifecycle (SDLC). It guides developers through every phase, from initial concept refinement and requirement specification to incremental implementation, testing, code review, and deployment. It enforces critical professional behaviors like surfacing assumptions, managing ambiguity, and maintaining scope discipline to ensure high-quality, robust engineering outcomes.

This skill provides robust mechanisms to verify the integrity of AI agent plugins, tools, and dependencies. It generates deterministic SHA-256 manifests (INTEGRITY.json) for all components, allowing users to detect unauthorized modifications, track provenance, and ensure that deployed assets match their published versions. Use this during CI/CD pipelines, code review, and pre-production promotion to secure the entire agent ecosystem.