By 8b-is
Personalized coding tutorials that use your actual codebase for examples with spaced repetition quizzes
A Claude Code plugin that makes each unit of engineering work easier than the last.
/plugin marketplace add https://github.com/8b-is/8b-is-mp
/plugin install 8b-compound-engineering
Plan → Work → Review → Compound → Repeat
| Command | Purpose |
|---|---|
/workflows:plan | Turn feature ideas into detailed implementation plans |
/workflows:work | Execute plans with worktrees and task tracking |
/workflows:review | Multi-agent code review before merging |
/workflows:compound | Document learnings to make future work easier |
Each cycle compounds: plans inform future plans, reviews catch more issues, patterns get documented.
Each unit of engineering work should make subsequent units easier—not harder.
Traditional development accumulates technical debt. Every feature adds complexity. The codebase becomes harder to work with over time.
Compound engineering inverts this. 80% is in planning and review, 20% is in execution:
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub 8b-is/8b-is-mp --plugin coding-tutorAI-powered development tools. 27 agents, 23 commands, 14 skills, 1 MCP server for code review, research, design, and workflow automation.
Personalized coding tutorials that use your actual codebase for examples with spaced repetition quizzes
In-context coding tutor for Claude Code. Learn from your real project with explanations, quizzes, diagnostics, and belt-based progression — locally and privately.
Codebase learning through knowledge extraction, code knowledge graph, challenges, and spaced repetition. Prevents knowledge atrophy for experienced developers and accelerates onboarding for new ones.
Science-based learning exercises for deliberate skill development during AI-assisted coding
互動式學習模式,在決策點請求有意義的程式碼貢獻(模擬未發布的學習輸出風格)
Agent skills that package evidence-backed pedagogical methodologies (explain-and-check, quiz-me, connect-to-what-you-know, ask-me-questions, learn-by-doing, linked-notes, flashcards) as workflows applied to code. The anti-cognitive-surrender layer: closes the comprehension gap that opens when an LLM has done the work on the human's behalf.