academy-guide
claudeRecommends relevant Claude Academy courses, tutorials, and use cases when users ask how to use Claude
19 skills
Turn what you learn with your AI into courses with spaced-repetition reviews: design and save courses, learn what a coding session or a codebase taught you, and train today's BrainyGym session.
Plugin brainygym from marketplace brainygym in siostechlabs/brainygym-skills. Commands read from the repo's manifest — 19 days ago.
brainygym-course-designUse when the user wants a course, study plan or training on a topic saved to BrainyGym. Explains how to design modules, concepts, readings and multiple-choice questions in the format save_course accepts. Also use when the learner wants to train or continue today's BrainyGym session with you (questio
learn-codebaseUse when the user wants to understand or get onboarded to the current repository or project ("help me learn this codebase", "I'm new to this repo", "make me a course about how this project works"). Reads the project's documentation and structure, proposes a course on its architecture, concepts and w
learn-from-sessionUse when the user wants to learn or remember what was done in this coding session ("teach me what we just did", "turn this session into a course", "I don't want to forget how this works", "quiz me on what you changed"). Extracts the general concepts the session relied on (technologies, patterns, dec
/brainygym:cursoDesign a course on a topic and save it to BrainyGym to train it.
/brainygym:hoyTrain today's BrainyGym session with Claude.
/brainygym:repasarReview what is due today in BrainyGym.
brainygymconnects to: https://brainygym.com/mcp
Recommends relevant Claude Academy courses, tutorials, and use cases when users ask how to use Claude
19 skills
Adds educational insights about implementation choices and codebase patterns (mimics the deprecated Explanatory output style)
hooks
AI-powered codebase understanding — analyze, visualize, and explain any project
9 skills · 10 agents · 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
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