Skill UI

This skill helps users design robust and optimal software interfaces (APIs) for a module by applying the 'Design It Twice' philosophy. It generates multiple, radically different architectural designs using parallel agents, allowing for comprehensive comparison of trade-offs (e.g., simplicity vs. flexibility, specialized vs. general-purpose). Use this when you need to explore various structural options or compare module shapes before committing to a final design.

A guide to building resilient software integrations when dealing with external APIs that lack formal versioning, changelogs, or guaranteed backward compatibility. Learn defensive coding patterns, implementing schema drift detection via CLI tools (curl, jq), using fallback field names, and executing gradual feature flag rollouts to maintain production stability.

A comprehensive methodology for discovering potential software vulnerabilities. It outlines advanced techniques including static analysis, dynamic analysis, fuzzing, taint tracking, and modern attack surface mapping (e.g., kernel, drivers). Ideal for professional code audits, bug bounty hunting, and building robust vulnerability research pipelines.

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.

This skill executes implementation plans by assigning a dedicated sub-agent to each independent task. It ensures quality through task-specific reviews and a final branch review. It emphasizes continuous execution, autonomous decision-making, and isolated contexts to prevent context pollution, suitable for structured software development workflows.

This workflow establishes a structured, multi-agent system to manage the entire software development lifecycle. It uses specialized roles (Producer, Developer, QA) to clarify scope, implement robust features, conduct rigorous testing, and maintain project context across sessions. Ideal for adopting new projects or coordinating complex, multi-step implementations.

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.