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AI Knowledge Management System - Transform expert materials into actionable playbooks

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Mega Brain

Mega Brain

AI Knowledge Management System
Transform expert materials into structured playbooks, DNA schemas, and mind-clone agents.

Version Node Python License


What is Mega Brain?

Mega Brain is a Claude Code-powered system that ingests expert materials — videos, PDFs, transcriptions, podcasts, training courses — and transforms them into structured knowledge. It produces playbooks, DNA schemas, and AI agents that reason with traced evidence.

Built for solo entrepreneurs and small teams who want to operationalize the expertise they have accumulated across dozens of courses, mentors, and resources.

Quick Start

# 1. Install dependencies (only in the first run)
npm install

# 2. Install and configure
npx mega-brain-ai setup

# 3. Fill in API keys when prompted (only OPENAI_API_KEY is required)

# 4. Open Claude Code and check system status
/jarvis-briefing

Setup auto-triggers on first use if .env is missing.

Prerequisites

Requirement Version Notes
Claude Code Max or Pro plan Core runtime
Node.js >= 18.0.0 CLI and tooling
Python >= 3.10 Intelligence scripts

API Keys

Key Purpose Required?
OPENAI_API_KEY Whisper transcription Yes
VOYAGE_API_KEY Semantic embeddings (RAG) Recommended
GOOGLE_CLIENT_ID Google Drive import Optional

Run /setup in Claude Code to configure keys interactively. Keys are stored in .env (gitignored).

Features

Knowledge Pipeline

  • Ingest any format — videos, PDFs, transcriptions, podcasts, training courses
  • Extract structured DNA across 5 knowledge layers (philosophies, mental models, heuristics, frameworks, methodologies)
  • Build playbooks, dossiers, and theme-based knowledge bases with full source traceability

AI Agents

  • Mind Clones — AI agents that reason like specific experts, grounded in their actual materials
  • Cargo Agents — Functional role agents (Sales, Marketing, Operations, Finance) that synthesize knowledge from multiple sources
  • Conclave — Multi-agent deliberation sessions with evidence-based debate and structured output

Developer Experience

  • 20+ hooks for automated validation, session management, and quality control
  • Slash commands for common operations (/ingest, /save, /resume, /conclave)
  • Skill system with keyword-based auto-routing
  • Session persistence with auto-save and resume

Architecture

mega-brain/
├── core/           -> Processing engine (tasks, workflows, protocols, schemas)
├── agents/         -> AI agent definitions (conclave, cargo, minds, templates)
├── bin/            -> CLI tools and entry points
├── .claude/        -> Claude Code integration (hooks, skills, commands, rules)
├── knowledge/      -> Knowledge base (playbooks, dossiers, DNA schemas)
├── artifacts/      -> Pipeline processing stages (chunks, insights, narratives)
├── inbox/          -> Raw materials input directory
├── docs/           -> Documentation, PRDs, plans
└── logs/           -> Session and processing logs

Layer System

Content is organized into three distribution layers:

Layer Content Distribution
L1 (Community) Core engine, templates, hooks, skills, CLI npm package (public)
L2 (Pro) Populated knowledge base, mind clones, pipeline Premium (tracked)
L3 (Personal) Your materials, sessions, environment config Local only (gitignored)

Community vs Pro

Feature Community (L1) Pro (L2)
CLI and setup wizard Yes Yes
Core engine and templates Yes Yes
Skills and hooks Yes Yes
Agent templates and examples Yes Yes
Populated knowledge base -- Yes
Mind clone agents -- Yes
Pipeline processing -- Yes
Council / Conclave -- Yes

Commands

Use these slash commands inside Claude Code:

Command Description
/jarvis-briefing System status and health score
/ingest Ingest new material into the pipeline
/process-jarvis Run the 5-phase processing pipeline
/conclave Multi-agent deliberation session
/save Save current session state
/resume Resume previous session
/setup Environment setup wizard

DNA Schema

Knowledge is extracted and structured in 5 layers:

Layer Name Description
L1 Philosophies Core beliefs and worldview
L2 Mental Models Thinking and decision frameworks
L3 Heuristics Practical rules and decision shortcuts
L4 Frameworks Structured methodologies and processes
L5 Methodologies Step-by-step implementations

Every piece of extracted knowledge traces back to its source material with file path, line number, and original context.

Validation

Verify the package before publishing:

# Check that only L1 content is in the package
npm run validate:layers

# Full pre-publish gate (secrets scan + layer validation)
node bin/pre-publish-gate.js

Contributing

See CONTRIBUTING.md for guidelines.

License

UNLICENSED — See package.json for details.

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