explanatory-output-style
claudeAdds educational insights about implementation choices and codebase patterns (mimics the deprecated Explanatory output style)
hooks
Tutor-mode skills and agents for Code Dojo.
Plugin code-dojo from marketplace code-dojo in Expo39/Code-Dojo. Commands read from the repo's manifest — yesterday.
dojo-assessSetup, placement and re-assessment for a Code Dojo learner. Use when a learner is new (no progress/profile.json), says "set me up", "assess me", "placement", "I already know X", "import my notes/progress", "bring the system up to my level", "show my modules", or once a month. Builds or updates progr
dojo-drillShort drills for reading, debugging and recognising code in the Code Dojo. Use when the learner says "read drill", "debug drill", "discriminate drill", "work drill", "practise <concept>", or an older name ("predict" or "trace drill" = read drill; "bug" or "review drill" = debug drill).
dojo-mockRun a realistic live-coding mock interview or a single timed interview problem for the Code Dojo learner, then give scored feedback and log it. Use when the learner says "mock interview", "interview problem", "practice interview", or on mock day (its frequency follows the learner's mode, docs/METHOD
dojo-new-exerciseCreate new verified Code Dojo exercises. Use when the learner says "new exercise on <topic>", "more like <exercise>", "from scratch <topic>", when a planned module from a track README is reached, or when a weak spot needs more practice.
dojo-new-trackDesign a new Code Dojo track, or review an existing one, from the best free material on the web (university courses, official docs, well-regarded repos and books), judged critically and kept current. Use when the learner or a maintainer says "design a track for X", "build the X track", "review the X
dojo-probeGoal-first mini test that finds what a Code Dojo learner already knows and what they need for a goal, using the track's concept graph. Use when the learner says "probe me", "what do I need for X", "test what I know about X", "I want to start <track>", when a roadmap starts a new track, at the close
dojo-roadmapPlan which tracks a Code Dojo learner follows, in what order and mix, from their goals and measured progress. Use when the learner says "plan my learning", "replan", "I want to learn X", "when should I start X", "should I learn X before Y", "I have an interview/exam on <date>", "focus on X", during
dojo-sessionStart-of-session catch-up for the Code Dojo learner. Use on the learner's first message of every session, or when they say "catch up", "where am I", "what's today". Syncs untracked work, reads their plan and reports, and proposes today's session.
dojo-teachTeach one concept to the Code Dojo learner using Predict-Run-Investigate-Modify-Make. Use when the learner says "teach me <topic>", "explain <concept>", or when a weak spot needs a lesson before more exercises.
dojo-weeklyWeekly review for the Code Dojo learner. Use when the learner says "weekly review", "how was my week", at the end of their last training day, or when a weekly report is missing for a finished week.
Adds educational insights about implementation choices and codebase patterns (mimics the deprecated Explanatory 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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