learning-output-style
claudeInteractive learning mode that requests meaningful code contributions at decision points (mimics the unshipped Learning output style)
hooks
可验证性治理的全自动产物管线——输入任务要求文档,全自动产出可交付产物(含代码、环境、产物、文档、执行留痕)
Plugin homework-pipeline from marketplace homework-dev in 86thAuspiciousVerse/HomeWork-PipeLine. Commands read from the repo's manifest — 1 month ago.
hw启动 HomeWork-PipeLine。输入课程要求文档,在当前目录全自动产出可交付作业。
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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