Skill UI

This skill is designed for tackling complex, multi-step software development tasks. It generates highly detailed, structured implementation plans that strictly adhere to best practices like TDD, YAGNI, and DRY. The plan breaks down features into small, atomic, executable tasks, specifying required file changes, writing initial failing tests, implementing minimum necessary code, and committing. It ensures the resulting plan is ready for efficient, autonomous execution by AI agents or human teams.

Use this skill to prompt the agent to zoom out from a specific code section, providing a broader, higher-level perspective. It helps map out the overall system architecture, identifying relevant modules, calling relationships, and how the current code snippet fits into the larger picture. Ideal when you are unfamiliar with a specific area or need system-level understanding.

This guide outlines a sophisticated development workflow using dedicated subagents for each independent task within a plan. It mandates a two-stage review process—first for specification compliance, then for code quality—ensuring highly reliable, high-quality, and rapidly iterative development cycles while maintaining strict context isolation.

This framework enforces high output quality, intellectual honesty, and continuous improvement across all AppSec agents. It mandates structured processes, including self-critique loops, anti-rationalization guards, and self-reflection quality gates (≥8 scoring). Applicable during code review, SAST, SCA, and threat modeling, it ensures rigorous and verifiable security analysis.

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 skill analyzes your entire codebase to ensure it is optimized for AI contributions and developer tooling. It automatically generates essential configuration files such as `AGENTS.md`, Copilot instructions, CI workflows, and customizable issue templates. It learns from your existing PR review patterns to tailor the setup precisely to your project's stack. Use it when you need to prepare a repository for advanced AI-assisted development.

This skill integrates BuyWhere's product catalog surface, allowing AI agents to perform structured product searches, compare prices across various merchants, and discover deals. It is designed for developers building advanced e-commerce shopping agents, guiding them through the necessary API key setup and MCP configuration.

This skill pulls the latest GEO-SEO components, including skills, agents, scripts, and schema templates, from the official upstream repository. It performs a detailed comparison (diff) to show all changes—new, modified, or removed—before applying the update. It ensures local customizations are preserved while keeping the toolkit current. Use this whenever you suspect your local setup might be outdated.

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.

Cavecrew provides a set of specialized subagents (investigator, builder, reviewer) designed for efficient code development delegation. Unlike vanilla agents, Cavecrew compresses output results, drastically reducing the token usage injected back into the main context. This allows users to maintain context over much longer, complex coding sessions, effectively preventing context exhaustion during large-scale refactoring, debugging, or multi-step feature development.

This comprehensive, zero-trust security auditor scans third-party AI agent skills before installation. It performs a rigorous 6-phase review process, analyzing surface patterns, script integrity, permissions, and supply chain risks. It is designed to detect malicious payloads, credential theft, instruction overrides, and prompt injection attacks, ensuring secure AI development and deployment.

This skill generates comprehensive, tailored instruction files for AI coding assistants like GitHub Copilot and Claude. It supports multiple strategies (flat or nested) and is specifically designed for managing complex monorepos by creating area-scoped instructions using `applyTo` globs. Use it to standardize AI tooling usage across large codebases.