Skill UI

Wraps any existing HTML artifact (landing page, dashboard, etc.) with a live sidebar panel of controls. This panel allows users to instantly adjust design variables—such as accent color, typography scale, layout density, and dark mode—by rewriting CSS custom properties in real time. All changes are persisted via localStorage, enabling continuous exploration and variant testing without losing state.

Automatically generates a professional, single-file, horizontal-swipe HTML slide deck for weekly team updates. Ideal for routine status meetings, this skill structures key information into specific sections: what was shipped, what is in flight, blocked items, key metrics, and next week's asks. Streamlines team communication and reporting processes.

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.

Use this comprehensive skill to generate, manipulate, and export draw.io diagrams. It converts diagrams into native .drawio files and allows exporting to high-quality formats like PNG, SVG, and PDF. Crucially, it embeds the editable XML data, ensuring the resulting diagrams are professional, scalable, and easily integrated into documents.

A code-generation toolkit for implementing compile-time dependency injection in Golang. Wire analyzes the dependency graph to generate plain Go constructor code, eliminating the need for runtime containers or reflection. This ensures that dependency errors are caught during compilation (via `wire ./...`) rather than at runtime startup. It is ideal for building robust, large-scale Go applications that require strict dependency management.

A comprehensive skill for building professional, Unix-native Command Line Interfaces (CLIs) in Go using the spf13/cobra library. It details command tree setup, flag management (persistent vs. local), advanced argument validation, and the command execution hook chain (RunE). Ideal for engineers developing robust Go applications that interact deeply with the terminal.

This comprehensive tool provides annotations and tooling to automatically generate industry-standard OpenAPI/Swagger documentation for Go backend services. By treating documentation as a contract, developers can annotate handlers, define complex parameters, and specify security schemes (JWT, OAuth2). It integrates seamlessly with major Go frameworks like Gin, Echo, and Fiber, ensuring the Swagger UI is the accurate source of truth for API consumers and maintaining clean API contracts.

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.

This skill analyzes the comprehensive commit history between two branches to generate a concise, objective, and highly structured Pull Request (PR) description. It automatically groups changes by domain, summarizing the purpose, technical notes, and user impact, ensuring consistency and minimizing manual documentation effort.

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.

This skill analyzes the user's historical workflow data, passively captured via a local screenpipe daemon. It detects recurring activity patterns (e.g., research steps) and clusters them. It then compares these patterns against existing skills, automatically drafting proposals for new skills or optimized composition recipes that chain existing tools together. It is designed for privacy, running all detection and processing locally, and only sending redacted summaries to the LLM.