Skill UI

This internal agent skill defines a systematic, multi-step procedure for scanning GitHub repositories to gather comprehensive evidence supporting or explaining bug clusters. The process covers searching open issues, inspecting recent commits, analyzing code paths, and checking deployment history. It assigns evidence confidence tiers (Exact, Strong, Moderate, Weak) to provide a deep, actionable understanding of potential software defects.

A software development methodology that delegates independent tasks to isolated subagents in the current session, ensuring high quality through two-stage reviews focusing on spec compliance and code quality.

This comprehensive guide serves as a decision flowchart for developers using Claude Code. It details when to use specific slash commands (/plan, /compact, /loop), select specialized agents (planner, code-reviewer, build-error-resolver), or invoke workflow skills (e2e-testing, tdd-workflow). It helps users select the optimal tool combination for complex tasks across the entire software development lifecycle, including feature planning, bug fixing, testing, and architectural design.

This advanced code reviewer analyzes your codebase through the principles of 12 classic software engineering books (e.g., Clean Code, DDIA, Mythical Man-Month). It detects conceptual flaws, design smells, tight coupling, missing abstractions, and architectural risks—issues that standard linters and basic AI tools often miss. Essential for major refactoring and pre-design validation.

Automates the end-to-end software release workflow for a GitHub repository. This skill handles Semantic Versioning (SemVer) version bumping, analyzes code changes by generating sophisticated diffs, and automatically creates a formatted changelog and release pull request. It relies exclusively on the GitHub CLI (gh) and Git for robust version control and deployment.

Squirrel is an advanced, full-cycle AI coding skill designed to guide software development from concept to production. It automatically detects the current project state (greenfield, in-progress, or mature) and adapts an 8-phase engineering pipeline. This comprehensive workflow covers planning, building, rigorous testing, bug hunting, code polishing, documentation, and deployment readiness, ensuring high-quality, maintainable results.

A systematic, multi-phase guide for tackling hard bugs and performance regressions. It mandates building a robust feedback loop (e.g., failing tests, harnesses), formulating falsifiable hypotheses, targeted instrumentation, and rigorous regression testing. This methodology ensures that debugging efforts are structured, efficient, and highly reproducible, making it ideal for complex software defects.

This skill details advanced techniques for exploiting formula injection vulnerabilities within CSV, Excel, LibreOffice, and Google Sheets environments. It covers DDE, obfuscation methods, and high-risk functions like IMPORT* that can be triggered when user-controlled data is exported or imported into spreadsheet software. Use this for penetration testing of data pipelines and export features.

An expert playbook for identifying and simulating dependency confusion attacks in software supply chains. It comprehensively covers how internal package names can be squatted on public registries, leading to malicious code execution via package manager lifecycle hooks (e.g., npm, pip, Maven). Use this guide for authorized red-team exercises and deep vulnerability assessment of build processes.

This playbook provides expert techniques for reverse engineering custom virtual machines and proprietary bytecode. It guides users through identifying dispatchers (switch/table), mapping unknown opcodes, reconstructing custom ISAs, and writing dedicated disassemblers. Essential for solving complex CTF challenges, analyzing protected software, or tackling custom runtime environments.

This orchestrator acts as a central hub for Go development, managing the complexity of modern software projects. Instead of using single skills, it reads the task context (e.g., building gRPC, debugging a panic) and automatically loads the most relevant combination of specialized skills (like testing, error handling, safety, or security) simultaneously. It ensures comprehensive coverage throughout the entire Go development lifecycle, making it ideal for advanced AI coding agents.

This meta-skill provides a comprehensive, step-by-step plan for complex software migrations. It intelligently coordinates multiple steps, including gathering migration requirements, classifying the source and target stacks (e.g., CJS to ESM, Py2 to Py3), searching authoritative guides, and analyzing repository diffs to ensure a guided, reliable upgrade path for large-scale projects.