Skill UI

This skill drives an existing browser instance using the Chrome DevTools Protocol (CDP). It is essential for complex web automation tasks that require visible interaction, JavaScript execution, or handling authenticated, stateful sessions. Use it when static data fetching is insufficient, such as simulating user logins, interacting with iframes, or performing visual verification. Supports headless and remote environments.

A comprehensive utility for managing complex cmux topologies, including workspaces, panes, and surfaces. This tool is essential for inspecting, controlling, and monitoring multiple AI coding agents running in parallel within a macOS terminal environment. It supports advanced functionalities such as browser automation and real-time status notifications, optimizing developer workflows.

Run comprehensive, read-only exposure checks against your local machine or project directories in response to security advisories and CVEs. This tool systematically checks various ecosystems (Node.js, Python, Homebrew, etc.) to generate a structured, non-invasive audit report, helping users understand their actual risk exposure without making any system changes.

This skill integrates with DeepAPI to facilitate advanced web scraping, market research, and controlled email workflows. It handles scraping data from various sources like websites, LinkedIn, GitHub, and Twitter, while managing costs and ensuring explicit user approval for sensitive actions like sending emails. Use it for robust data extraction and automated reporting.

This guide details how to effectively delegate complex, multi-step tasks to various specialized AI agents (Codex, Pi, Claude, Hermes). It covers best practices for maintaining conversation context, handling TUI prompts (e.g., avoiding newlines, using quotes), techniques for reliable polling, and choosing the optimal agent for coding, design, or general purpose work. Essential for advanced AI workflow automation.

This guide details the comprehensive workflow for distributing a single AI skill across various local agent skill directories (Codex, Claude, Pi, Hermes). It addresses canonical locations, symlink management, and specific synchronization commands to ensure that all agents detect the latest skill version while correctly navigating common development pitfalls.

This guide provides a comprehensive reference on Agent Skills, a standardized and powerful method for providing structured context, workflows, and tools to Large Language Models (LLMs). It details the anatomy of the SKILL.md file, the three-stage progressive disclosure loading process, and best practices for creating both capability (tool-based) and process (workflow-based) primitives. Use this resource when designing, reviewing, or debugging agent-driven applications to ensure reliable and context-efficient performance.

This skill is designed to mitigate false-positive safety triggers from strict AI classifiers (e.g., cyber, bio/chem, reasoning). It operates by making minimal, surgical edits to sensitive phrases, abstracting away specific domains or actions while preserving the original benign intent and structure. It ensures the prompt remains policy-compliant without losing its core purpose, making it ideal for academic or defensive inquiries.

This skill helps developers create highly focused, folder-specific documentation (`CLAUDE.md` and `AGENTS.md`). It systematically analyzes all files in a target directory to extract project purpose, operational constraints, naming conventions, and critical decisions. This deep context ensures that future AI agents (like Claude or Codex) operate with localized knowledge, preventing them from relying on global, generalized instructions and improving their accuracy in that specific domain.

The /goal command converts standard agent prompts into persistent, self-correcting loops (plan → act → test → review → iterate). It is designed for long-running, complex engineering tasks like migrations, coverage lifts, or refactoring, ensuring progress is tracked against a verifiable stop condition and mandated documentation.

Provides deep semantic code intelligence for the Go language, utilizing the official `gopls` language server. Key features include precise go-to-definition, finding references, analyzing call graphs, performing safe refactoring (rename, extract, inline), generating diagnostics, and formatting code. It is essential for navigating, understanding dependencies, and maintaining large Go codebases.

This skill guides the safe, systematic, and at-scale refactoring of existing Go codebases. It ensures that structural changes maintain observable behavior by following a rigorous process: mapping blast radius, strengthening safety nets (tests), applying small tool-driven transforms, and committing changes atomically via staged PRs. Ideal for cleaning up large functions, resolving code smells, renaming packages, or tackling complex architectural improvements in Go.