Study and learning helpers
Plugin akbun-learning from marketplace akbun-aitools in choisungwook/akbun-aitools. Commands read from the repo's manifest — yesterday.
akbun-describe-twitter-transcriptx.com(트위터) post 링크와 함께 영상 자막 변환을 요청할 때만 사용한다.
akbun-describe-youtube-transcript유튜브 링크 또는 영상 ID와 함께 자막 변환을 요청할 때만 사용한다.
akbun-driven-learning가설 검증형 학습자를 위한 기술 개념 설명 스타일. 학습자가 자기 언어로 재구성한 이해를 확인받으며 연쇄 질문으로 파고드는 대화형 학습에 사용한다.
akbun-learning-englishakbun-learning-japaneseakbun-make-anki-japaneseVideo editing skills — DaVinci Resolve vlog edits: speech-free travel vlogs (cut/stabilize, exposure/white balance, face mosaic, Gmarket Sans subtitles) and faceless talking developer vlogs (subtitles, project style guide, shot sketches)
29 skills
Image drawing skills — image-generation prompts and editable SVGs in fixed akbun styles
27 skills
Writing, review, and blog support skills
12 skills · 2 agents
YouTube skills written as YAML for people and AI — a channel settings sheet that follows official YouTube documentation, Codex computer-use skills that set an uploaded video's metadata and register AI-translated titles and descriptions (English, Japanese, French, Simplified Chinese), and analysis of your own videos' metrics and style
5 skills
Code review and change analysis skills — why/how investigation of PRs from git history, diff blast-radius proof by execution, credential authn/authz checks, and adversarial review
4 skills
Agent operations skills — set up a project's memory layout once, rebuild working context at session start, and turn each session's lessons into approved edits to the memory structure the codebase already has
3 skills
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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