learning-output-style
claudeInteractive learning mode that requests meaningful code contributions at decision points (mimics the unshipped Learning output style)
hooks
Practical life-admin skills: live-verified cheap flight search, airline pricing myth-buster, one-minute focus steps for stuck tasks, and a four-hour learn-anything plan.
Plugin everyday-tools from marketplace everyday-tools in captkernel/claude-everyday-tools. Commands read from the repo's manifest — 27 days ago.
farecheckUse to explain how airline pricing actually works and separate real mechanisms from myths. Triggers: \"do flight prices go up if I search twice\", \"how does airline pricing work\", \"is incognito cheaper for flights\".
flightsUse to find cheaper flight options for a trip. Triggers: \"find cheap flights\", \"cheapest way to fly\", \"flight deal\", \"how do I fly cheaper to\".
focusUse when the user is stuck and cannot start a task. Triggers: \"I can't start\", \"help me focus\", \"I'm procrastinating\", \"break this down\", \"I'm overwhelmed by\".
learn-fastUse to create a fast \"make me functional\" crash plan for a new skill. Triggers: \"help me learn X fast\", \"crash course on\", \"get me functional in\", \"I have a few hours to learn\".
/everyday-tools:farecheckSeparates real airline pricing mechanisms from myths, then gives an evidence-based method
/everyday-tools:flightsFlight-deal scanner — ranks cheaper-routing options by cost and risk (estimates, verify before booking)
/everyday-tools:focusCan't start? Break a task into sub-1-minute steps and give just the first
/everyday-tools:learn4-hour \"make me functional\" crash plan for a new skill
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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