Skill UI

This skill provides a robust system for tracking all code modifications using structured JSON records and enforcing a defined state machine (e.g., planned -> deployed). It is critical for AI coding workflows, ensuring that if a session expires or is abandoned, the next session receives the full context, progress summary, and blockers to resume seamlessly. Ideal for complex, multi-stage development projects and onboarding new codebases.

This skill provides a systematic approach to debugging and error recovery when tests fail, builds break, or behavior deviates from expectations. It emphasizes stopping feature development to preserve evidence, diagnosing root causes through a triage checklist, and guarding against recurrence with tests. Ideal for developers facing runtime bugs, production incidents, or unexpected errors, ensuring efficient problem-solving without guessing.

Master Git best practices for code management, including trunk-based development, atomic commits, and descriptive messages. Organize parallel work streams, manage branches effectively, and prepare for releases with semantic versioning. Essential for maintaining clean, reviewable, and reversible code history in modern development environments.

This comprehensive guide dives deep into the internals of Go's built-in data structures (slices, maps, arrays) and standard library packages. It covers critical topics like capacity growth mechanics, preallocation strategies, pointer types (unsafe/weak), and the optimized usage of specialized containers (heap, list, ring). Use this resource to select the correct structure for optimal performance and memory safety in expert Go development.

A comprehensive guide to achieving high code quality in Go projects using `golangci-lint`. This skill covers the entire development lifecycle, including setting up the essential `.golangci.yml` configuration, running automated linters (style, security, complexity), automatically fixing issues, interpreting detailed lint output, and correctly suppressing false positives using `//nolint` directives. Ideal for enforcing best practices in CI/CD pipelines and maintaining legacy codebases.

This skill acts as an advanced extension layer, implementing a self-evolution protocol, maintaining session state continuity (Compaction), and providing KPI-style performance summaries. It allows users to simulate continuous professional development, track metrics, and master complex role-playing and interaction skills across multiple sessions, ensuring performance baselines are continuously adjusted and internalized.

This comprehensive guide details the correct usage of the Flutter `provider` package, a widely adopted state management solution. It covers various provider types, including `ChangeNotifierProvider`, `FutureProvider`, and `StreamProvider`. Learn best practices for setting up state with `MultiProvider` and mastering state consumption techniques like `context.watch`, `context.read`, and `Selector`, ensuring efficient and type-safe application development.

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.

Security-first development practices for web applications. Covers threat modeling with STRIDE, OWASP Top Ten defenses, input validation, parameterized queries, authentication and session hardening, security headers, dependency auditing, and supply-chain risk assessment.

This skill enables users to create new AI skills from scratch, modify existing ones, and optimize performance through evaluation and benchmarking. It supports iterative development loops, including drafting, testing with prompts, quantitative analysis, and refining descriptions for better triggering accuracy. Ideal for developers building custom agent workflows.

A software development methodology where tests are written before implementation code. It follows the red-green-refactor loop to ensure code quality and reliability. Ideal for bug fixing, new feature implementation, and maintaining existing functionality. Helps prove code correctness and reduces technical debt.

This tool analyzes specification files to extract all defined requirements and cross-references them with the current codebase implementation status. It systematically checks for unimplemented features, searches existing GitHub issues to prevent duplicates, and automatically generates detailed issues using a standardized feature request template. It is essential for robust product management, ensuring every defined requirement is tracked and scheduled for development.