Skill UI

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 Use this whenever you suspect your local setup might be outdated.

Logic Lens is an advanced AI skill that performs deep, formal logic-driven code review. Unlike standard linters, it analyzes code for complex issues like race conditions, security vulnerabilities (SQL injection, XSS), type safety flaws, and algorithmic errors across 9 critical risk categories. It is ideal for pre-merge PR reviews, auditing sensitive code paths, and refactoring complex business logic.

This skill generates a complete, standalone, and highly structured pricing page in standalone HTML. It automatically respects the active design system (colors, typography, components) and supports defining 2-4 plan tiers, including feature cards, comprehensive comparison tables, and an FAQ section. Ideal for product marketing and sales-focused websites.

Generates a complete, single-page SaaS landing page structure. This tool produces a fully contained HTML file, integrating required sections such as Hero, Features, Social Proof, Pricing, and Call-to-Action (CTA). It strictly adheres to an existing design system for colors, typography, and layout, making it ideal for product launches and marketing campaigns.

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 library facilitates compile-time dependency injection in Go using the google/wire framework. Unlike runtime container solutions that rely on reflection, Wire analyzes the entire dependency graph during compilation and generates plain Go constructor calls in `wire_gen.go`. This approach guarantees that dependency errors are caught during the build phase (via `wire ./...`), leading to highly robust, performant, and easy-to-debug Go applications.

Master the art of building robust, Unix-native Command Line Interfaces (CLIs) using the spf13/cobra library in Go. This skill covers the entire command tree lifecycle, including setting up subcommands, managing local and persistent flags, implementing advanced argument validation, and understanding the execution hook chain (RunE family). Essential for Go developers creating professional command-line tools.

A powerful utility that converts Markdown (`.md`) files into richly formatted Word (`.docx`) documents. Built using pure JavaScript, it requires no external dependencies like Pandoc or LibreOffice. Features include automatic generation of title pages (from YAML front-matter), dynamic table of contents, and accurate embedding of PNG images, making it ideal for technical documentation and reports.

Analyzes commit history using advanced heuristics to create a clean, objective, and highly structured Pull Request (PR) description. It automatically groups changes by domain, infers feature types, and summarizes the functional impact, minimizing manual effort and required tokens. Ideal for maintaining consistency and improving code review clarity across large codebases.

This skill assesses the AI readiness of a codebase by running a comprehensive audit against multiple technical and governance pillars. It generates a self-contained, detailed HTML dashboard that provides an overall maturity score, identifies strengths, and, most importantly, delivers a prioritized remediation plan (Fix First / Fix Next). Ideal for auditing repositories before major AI feature development.

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.