Agent Skills Hub

test-environment-management

Manage test infrastructure with IaC, Docker, and service virtualization. Optimize testing costs, ensure dev/prod environment parity, and automate environment provisioning for consistent, scalable software testing.

data-extraction-patterns

Proven patterns for extracting, caching, and processing analytics data from GA4 and GSC using MCP servers.

dev-cycle

Interactive development workflow manager. Coordinates discovery, planning, review, and build phases using a specialized team of AI agents (Scout, Bob, Garry, Arlo) for consistent project delivery.

hs

Pre-execution security guardrails for AI agents. Validates shell commands and file reads against 400+ security patterns to block destructive operations, credential theft, and unauthorized system access.

hf-mcp

Connect your AI agent to the Hugging Face Hub via MCP. Search models, datasets, and papers, manage repos, run cloud compute jobs, and invoke Gradio Spaces as functional AI tools.

sonoscli

Control and manage Sonos multi-room audio systems directly via CLI, including playback, volume, grouping, and queue management.

refactoring-patterns

Safely refactor code to improve structure and maintainability while preserving behavior through TDD cycles and automated test verification.

command-executor

Safely execute, test, and verify commands discovered in documentation with real output capture, performance tracking, and git-aware safety protocols.

commit-safe

A secure Git commit workflow agent that prevents accidental mass commits and promotes surgical, file-specific staging and semantic commits.

bdg

A terminal-based Chrome DevTools Protocol client designed for AI agents. Provides direct, session-persistent control over browser navigation, DOM manipulation, scraping, and network inspection.

error-handling-patterns

Master cross-language error handling patterns: exceptions, Result types, and graceful degradation for resilient application development.

plan-down

Method-driven planning workflow that intelligently decomposes tasks into structured plan.md files using zen-mcp tools, adapting to user clarity and automation needs.