explanatory-output-style

Comprehensive codebase analysis and steering context generation for AI agents. Automatically detects project type and generates architecture documentation, design patterns, quality reports, and AI-ready context files.

7 commands · 20 agents

Enterprise Auth0 OAuth 2.0 implementation plugin with setup wizards, framework-specific code examples, security audits, compliance checklists (GDPR/HIPAA/SOC2), and troubleshooting guides for production OAuth deployments.

5 commands · 4 agents

Comprehensive code quality automation with linting, testing, security scanning, and pre-commit hooks. Enforces coding standards, catches issues before commit, and provides detailed quality reports.

5 commands · 3 agents · hooks

Video generation pipeline management for InfiniteMedia. Submit jobs, monitor status, manage queues, review quality, and debug pipeline issues. Supports idea-to-video and script-to-video workflows with specialized AI agents.

5 commands · 3 agents

Automated documentation generation from code. Creates API references, README updates, architecture docs, and docstrings. Keeps documentation in sync with code changes automatically.

5 commands · 2 agents

DevOps automation toolkit for deployment, CI/CD, environment management, and infrastructure. Streamlines deployment workflows, Docker builds, and infrastructure monitoring.

5 commands · 2 agents

Interactive learning mode that requests meaningful code contributions at decision points (mimics the unshipped Learning output style)

hooks

Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data

9 skills · 9 commands · 11 agents · 1 MCP server

Cross-session memory and token savings for coding agents.

6 skills · 1 agent · 1 MCP server · hooks

Full Domino Data Lab platform support — workspaces, jobs, model deployment, experiment tracking, GenAI tracing, Spark/Ray/Dask, and app deployment for data science teams

26 skills · 4 commands · 3 agents · 1 MCP server

Claude Code native multi-agent orchestration with intelligent model routing across agents and skills. Zero learning curve. Maximum power.

85 skills · 20 commands · 19 agents · 1 MCP server · hooks

Turn any learning intent into a personalized Coursera experience. Asks three quick questions (topic, familiarity, preferred format), searches Coursera's catalog, and delivers the right next step — a course, hands-on project, short video, or live roleplay — then maps a path forward. Requires the Coursera connector for catalog tools.

1 skill