Skill

cm-notebooklm

CodyMaster NotebookLM — Cloud-based AI brain/soul engine. Stores the most valuable knowledge (skills, lessons learned, coding experiences, key decisions) into Google NotebookLM for cross-machine sync and AI-powered recall. Combines cm-dockit (codebase → docs) + cm-deep-search (local BM25) + NotebookLM (cloud AI memory + podcast + flashcards). Offers LOCAL vs CLOUD choice for large codebases. Auto-sync mechanism. Selective indexing — only high-value content, not everything. Use when user says: "notebooklm", "notebook lm", "nlm", "nạp kiến thức", "knowledge base", "create notebook", "sync skills to notebook", "tạo notebook", "knowledge memory", "podcast từ skills", "flashcards từ docs", "add to notebooklm", "query notebooklm", "hỏi notebooklm", "lưu kinh nghiệm", "bộ nhớ AI", "AI memory", "tạo podcast", "codymaster notebook", "skill notebook", "sync knowledge", "cloud brain", "soul sync", "cross-machine sync".

From cm

Install

Run in your terminal

npx claudepluginhub tody-agent/codymaster --plugin cm

Tool Access

This skill uses the workspace's default tool permissions.

Supporting Assets

View in Repository

references/command_reference.md

references/workflows.md

resources/knowledge_sources.md

scripts/brain-sync.sh

scripts/graduate_wisdom.py

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Stats

Stars30

Forks15

Last CommitMar 26, 2026

Actions

View Source View Plugin View on GitHub View README

Goal

Cloud brain / soul cho AI — lưu trữ kiến thức giá trị nhất, đồng bộ qua nhiều máy tính. brain.md = compiled source of truth, upload 1 lần thay vì 50.

How It Works

Skills + Lessons + Experiences
        ↓ compile
  ~/.codymaster/brain.md  (local file = backup)
        ↓ upload (1 API call)
  NotebookLM (cloud = cross-machine sync)

All automation via scripts/brain-sync.sh — AI chỉ cần gọi script.

Instructions

The Dual-Brain Architecture

CodyMaster uses a Dual-Brain approach to scale memory across multiple projects without context collapse:

Master Brain (codymaster): Global brain storing Meta-Learnings, proven Architecture Decisions, and universal patterns. Evolved via the "Rule of 3" (knowledge graduation).
Project Brain (Isolated): Optional local brain created per project to hold internal PRDs, APIs, and local code context from ./docs.

Level	Goal	Query Command
Master	Tìm pattern chung	`nlm notebook query codymaster "..."`
Project	Tìm context domain	`nlm notebook query $(cat .cm/notebook_id) "..."`

🤖 AI Rule: Tự đưa quyết định khi hỏi: Hỏi codymaster cho các giải pháp mang tính hệ thống chung. Hỏi qua .cm/notebook_id cho các business logic đặc thù dự án đang làm.

Master Brain Setup (Global)

# 1. Install CLI
uv tool install notebooklm-mcp-cli

# 2. Setup Master Brain
bash ~/.gemini/antigravity/skills/cm-notebooklm/scripts/brain-sync.sh init

Project Brain Setup (Local - Optional)

Nếu dự án đủ lớn và nhiều doc:

# Tạo Project Brain riêng cho thư mục hiện tại
bash ~/.gemini/antigravity/skills/cm-notebooklm/scripts/brain-sync.sh init-project

Daily Usage

SCRIPT=~/.gemini/antigravity/skills/cm-notebooklm/scripts/brain-sync.sh

# Add a lesson learned
bash $SCRIPT lesson "Tên bài học"
# → Edit ~/.codymaster/lessons.md → fill in details

# Add coding experience
bash $SCRIPT experience "Tên pattern"
# → Edit ~/.codymaster/experiences.md → fill in details

# Sync to Master Brain (Thêm rule of 3)
bash $SCRIPT sync

# Sync to Project Brain (Up tài liệu local docs/)
bash $SCRIPT sync-project

# Check status
bash $SCRIPT status

# Query
nlm notebook query codymaster "your question"

Auto-Sync Triggers

AI detect và hỏi user (không tự động):

Trigger	Prompt
Skill mới tạo	"Sync skill mới vào brain?" → `bash $SCRIPT sync`
Bug fixed / post-mortem	"Lưu bài học?" → `bash $SCRIPT lesson "..."`
Architecture changed	"Update brain?" → `bash $SCRIPT sync`
User nói "sync/update"	→ `bash $SCRIPT sync`

Cross-Machine (Máy Mới)

uv tool install notebooklm-mcp-cli
nlm login
nlm notebook list          # CodyMaster Brain already there
nlm alias set codymaster <id>
# Done! Query ngay: nlm notebook query codymaster "..."

Content Generation

nlm audio create codymaster --format deep_dive --confirm   # Podcast
nlm report create codymaster --format "Study Guide" --confirm
nlm flashcards create codymaster --difficulty medium --confirm
nlm studio status codymaster

What Gets Indexed

✅ HIGH-VALUE (auto-compiled into brain.md):
├── Skill Index (names + descriptions — NOT full SKILL.md)
├── Lessons Learned (~/.codymaster/lessons.md)
├── Coding Experiences (~/.codymaster/experiences.md)
└── AGENTS.md (project identity)

❌ NOT INDEXED (use qmd/cm-deep-search instead):
├── Full SKILL.md files (too many, hard to maintain)
├── Source code, tests, configs
└── Duplicated content

Memory Architecture

Session  → variables        → temporary
Working  → CONTINUITY.md    → ~500 words/turn
Local    → qmd              → BM25+vector, offline, stable
Cloud    → NotebookLM       → AI brain, cross-machine, podcast

Integration

Skill	Role
`cm-deep-search`	Local search complement (code)
`cm-dockit`	Generate docs → select high-value → feed to brain
`cm-continuity`	Session memory, brain = long-term
`skill-creator-ultra`	TRIGGER: new skill → prompt sync
`cm-debugging`	TRIGGER: bug fixed → prompt lesson

Constraints

🔌 nlm CLI = third-party (jacob-bd). May break. Fallback: cm-deep-search.
🧠 Selective only — quality > quantity. Don't dump everything.
🔐 NO secrets in NotebookLM — cloud service.
❌ NO delete without user confirmation.
🤖 NO nlm chat start — use nlm notebook query only.
🔄 Auto-sync = ask first, never silent upload.