Interactive learning mode that requests meaningful code contributions at decision points (mimics the unshipped Learning output style)
Plugin learning-output-style from marketplace claude-code-plugins in AnttiRask/claude-code. Commands read from the repo's manifest — 1 month ago.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
${CLAUDE_PLUGIN_ROOT}/hooks-handlers/session-start.sh
Comprehensive toolkit for developing Claude Code plugins. Includes 7 expert skills covering hooks, MCP integration, commands, agents, and best practices. AI-assisted plugin creation and validation.
7 skills · 1 command · 3 agents
Easily create custom hooks to prevent unwanted behaviors by analyzing conversation patterns or from explicit instructions. Define rules via simple markdown files.
1 skill · 4 commands · 1 agent · hooks
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
1 command · 6 agents
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review
1 command · 3 agents
Interactive self-referential AI loops for iterative development. Claude works on the same task repeatedly, seeing its previous work, until completion.
3 commands · hooks
Development kit for working with the Claude Agent SDK
1 command · 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
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