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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/thiagofinch/mega-brain/llms.txt

Use this file to discover all available pages before exploring further.

Schemas

All Mega Brain state and artifacts use JSON Schema validation for data integrity.

Schema Index

SchemaState FilePurpose
chunks-state.schema.jsonCHUNKS-STATE.jsonSemantic chunks with embeddings
canonical-map.schema.jsonCANONICAL-MAP.jsonEntity canonicalization mappings
insights-state.schema.jsonINSIGHTS-STATE.jsonExtracted insights by priority
narratives-state.schema.jsonNARRATIVES-STATE.jsonSynthesized narratives
file-registry.schema.jsonfile-registry.jsonProcessed file tracking
decisions-registry.schema.jsondecisions-registry.jsonCouncil decisions and precedents
Location: core/schemas/

State File Locations

processing/
β”œβ”€β”€ chunks/
β”‚   β”œβ”€β”€ CHUNKS-STATE.json           # Master chunk index
β”‚   └── {source-id}.json            # Per-source chunks
β”œβ”€β”€ canonical/
β”‚   β”œβ”€β”€ CANONICAL-MAP.json          # Entity mappings
β”‚   β”œβ”€β”€ ENTITY-REGISTRY.json        # Entity tracking
β”‚   └── review_queue.jsonl          # Merge candidates
β”œβ”€β”€ insights/
β”‚   └── INSIGHTS-STATE.json         # Extracted insights
└── narratives/
    └── NARRATIVES-STATE.json       # Synthesized narratives

system/REGISTRY/
└── file-registry.json              # File tracking

logs/SYSTEM/
└── decisions-registry.json         # Council decisions

chunks-state.schema.json

Validates chunk state with embeddings and metadata. Schema Version: 1.0.0

Structure

{
  "metadata": {
    "version": 1,
    "created_at": "2026-03-05T12:00:00Z",
    "updated_at": "2026-03-05T14:30:00Z",
    "total_sources": 15,
    "total_chunks": 342
  },
  "chunks_by_source": {
    "CG001": {
      "source_id": "CG001",
      "source_name": "Cole Gordon",
      "source_file": "inbox/COLE-GORDON/PODCASTS/farm-system.txt",
      "source_hash": "sha256:...",
      "chunk_count": 23,
      "processed_at": "2026-03-05T12:00:00Z",
      "chunks": [
        {
          "chunk_id": "CG001-001",
          "content": "The farm system is...",
          "word_count": 847,
          "embedding": [0.123, -0.456, ...],  // 1024-dim vector
          "persons_mentioned": ["Cole Gordon"],
          "roles_mentioned": ["CLOSER", "BDR"],
          "themes": ["02-PROCESSO-VENDAS"],
          "priority": "HIGH",
          "metadata": {
            "chunk_index": 0,
            "start_char": 0,
            "end_char": 5234
          }
        }
      ]
    }
  },
  "change_log": [
    {
      "timestamp": "2026-03-05T12:00:00Z",
      "action": "source_added",
      "source_id": "CG001",
      "chunk_count": 23
    }
  ]
}

Field Definitions

metadata
object
required
Schema metadata and statistics
chunks_by_source
object
required
Dictionary mapping source_id to chunk data
change_log
array
required
Audit trail of all changes to this state file

Validation

import json
import jsonschema

# Load schema
with open('core/schemas/chunks-state.schema.json') as f:
    schema = json.load(f)

# Load data
with open('processing/chunks/CHUNKS-STATE.json') as f:
    data = json.load(f)

# Validate
jsonschema.validate(data, schema)
Source: core/schemas/chunks-state.schema.json:1-xxx

canonical-map.schema.json

Entity canonicalization mappings and aliases. Schema Version: 1.0.0

Structure

{
  "metadata": {
    "version": 15,
    "updated_at": "2026-03-05T14:30:00Z"
  },
  "persons": {
    "Alex Hormozi": {
      "canonical": "Alex Hormozi",
      "aliases": ["alex hormozi", "hormozi", "Alex H"],
      "sources": ["HR001", "HR002", "CG005"],
      "mention_count": 147,
      "has_agent": true,
      "has_dna": true
    }
  },
  "roles": {
    "CLOSER": {
      "canonical": "CLOSER",
      "aliases": ["closer", "sales closer", "closers"],
      "mention_count": 89,
      "mention_breakdown": {
        "direct": 75,
        "inferred": 10,
        "emergent": 4
      },
      "weighted_score": 85.5,
      "sources": ["CG001", "CG002", "JM001"],
      "has_agent": true,
      "domain_ids": ["SALES"]
    }
  },
  "themes": {
    "processo-vendas": {
      "canonical": "processo-vendas",
      "theme_code": "02-PROCESSO-VENDAS",
      "aliases": ["sales process", "processo de vendas"],
      "occurrence_count": 234,
      "sources": ["CG001", "JM001", "HR003"],
      "has_dossier": true,
      "domain_ids": ["SALES"]
    }
  },
  "concepts": {
    "Farm System": {
      "canonical": "Farm System",
      "aliases": ["farm system", "the farm"],
      "layer": "L4",  // DNA layer
      "occurrence_count": 42,
      "sources": ["CG001", "CG002"]
    }
  }
}

Usage

from core.intelligence.entity_normalizer import normalize_entity

result = normalize_entity("alex hormozi", "person")
# Returns: {"canonical": "Alex Hormozi", "match_type": "alias", ...}
Source: core/schemas/canonical-map.schema.json:1-xxx

insights-state.schema.json

Extracted insights with DNA layer classification. Schema Version: 1.0.0

Structure

{
  "metadata": {
    "version": 8,
    "updated_at": "2026-03-05T14:30:00Z"
  },
  "insights_state": {
    "persons": {
      "Cole Gordon": {
        "HIGH": [
          {
            "insight_id": "INS-CG001-001",
            "chunk_id": "CG001-005",
            "content": "The farm system requires 3 closers per setter to maintain balance.",
            "dna_layer": "L4",  // FRAMEWORKS
            "priority": "HIGH",
            "confidence": 0.95,
            "themes": ["01-ESTRUTURA-TIME", "02-PROCESSO-VENDAS"],
            "extracted_at": "2026-03-05T12:30:00Z"
          }
        ],
        "MEDIUM": [...],
        "LOW": [...]
      }
    },
    "themes": {
      "processo-vendas": {
        "HIGH": [...],
        "MEDIUM": [...],
        "LOW": [...]
      }
    }
  }
}

DNA Layer Mapping

LayerNameExample Insight
L1PHILOSOPHIES”Sales is a transfer of belief”
L2MENTAL-MODELS”Think in systems, not tactics”
L3HEURISTICS”If close rate < 20%, problem is qualification”
L4FRAMEWORKS”CLOSER framework: C-L-O-S-E-R steps”
L5METHODOLOGIES”Step 1: Clarify problem. Step 2: Label pain…”
Source: core/schemas/insights-state.schema.json:1-xxx

narratives-state.schema.json

Synthesized narratives with patterns and tensions. Schema Version: 1.0.0

Structure

{
  "metadata": {
    "version": 3,
    "updated_at": "2026-03-05T14:30:00Z"
  },
  "narratives_state": {
    "persons": {
      "Cole Gordon": {
        "narrative": "Cole Gordon's sales philosophy centers on...",
        "last_updated": "2026-03-05T14:00:00Z",
        "scope": "sales_methodology",
        "corpus": ["CG001", "CG002", "CG003"],
        "insights_included": ["INS-CG001-001", "INS-CG001-005", ...],
        "patterns_identified": [
          {
            "pattern": "Emphasis on team structure over individual performance",
            "evidence": ["CG001-005", "CG001-012"],
            "frequency": "recurring"
          }
        ],
        "tensions": [
          {
            "tension": "Balance between setter autonomy and farm system structure",
            "manifestation": "Wants setters to be creative but follow farm ratios",
            "evidence": ["CG001-008", "CG002-003"]
          }
        ],
        "open_loops": [
          {
            "question": "How to scale farm system beyond 50 closers?",
            "context": "CG001-015",
            "importance": "HIGH"
          }
        ],
        "next_questions": [
          "What's the maximum setter-to-closer ratio before quality drops?",
          "How does farm system adapt for different price points?"
        ]
      }
    },
    "themes": {
      "processo-vendas": {
        "narrative": "...",
        "perspectives": [
          {
            "person": "Cole Gordon",
            "viewpoint": "Farm system with 1:3 setter-closer ratio",
            "evidence": ["CG001-005"]
          },
          {
            "person": "Jeremy Miner",
            "viewpoint": "NEPQ methodology for consultative selling",
            "evidence": ["JM001-003"]
          }
        ],
        "consensus_points": [
          "Qualification is more important than closing skills"
        ],
        "tensions": [
          "Farm system (Cole) vs solo closer model (Jeremy)"
        ]
      }
    }
  }
}

Usage

# Use narratives for knowledge extraction
/extract-knowledge "auto"  # Reads NARRATIVES-STATE.json
Source: core/schemas/narratives-state.schema.json:1-xxx

file-registry.schema.json

Processed file tracking with checksums.

Structure

{
  "metadata": {
    "version": 42,
    "updated_at": "2026-03-05T14:30:00Z"
  },
  "files": [
    {
      "source_id": "CG001",
      "source_file": "inbox/COLE-GORDON/PODCASTS/farm-system.txt",
      "source_hash": "sha256:...",
      "source_name": "Cole Gordon",
      "source_company": "Cole Gordon",
      "processed_at": "2026-03-05T12:00:00Z",
      "chunk_count": 23,
      "status": "complete",
      "artifacts": [
        "/processing/chunks/CG001.json",
        "/knowledge/dossiers/persons/COLE-GORDON.md"
      ]
    }
  ]
}
Source: core/schemas/file-registry.schema.json:1-xxx

decisions-registry.schema.json

Council decisions and precedents.

Structure

{
  "metadata": {
    "version": 7,
    "updated_at": "2026-03-05T14:30:00Z"
  },
  "decisions": [
    {
      "decision_id": "20260305130249-CRO-CFO",
      "query": "Should we increase closer commission from 10% to 15%?",
      "date": "2026-03-05T13:02:49Z",
      "participants": ["CRO", "CFO", "CMO"],
      "council": ["critico-metodologico", "advogado-do-diabo", "sintetizador"],
      "recommendation": "Pilot 15% with top 20% performers for Q2",
      "confidence": 72,
      "chunk_ids": ["CG001-005", "HR003-012"],
      "sources": [
        "/knowledge/SOURCES/COLE-GORDON/04-COMISSIONAMENTO/closer-comp.md"
      ],
      "residual_risks": [
        "May increase CAC if close rate doesn't improve"
      ],
      "next_steps": [
        {
          "action": "Design pilot program criteria",
          "owner": "CRO",
          "deadline": "2026-03-15"
        }
      ]
    }
  ],
  "precedents": [
    {
      "precedent_id": "PREC-2026-001",
      "pattern": "Commission increase decisions",
      "guideline": "Always pilot with top performers first",
      "based_on": ["20260305130249-CRO-CFO", "20260201142035-CRO-CFO"]
    }
  ]
}
Source: core/schemas/decisions-registry.schema.json:1-xxx

ID System

Source IDs

Format: PREFIX + NNN Examples: CG001, JL003, HR005 Registered Prefixes:
PrefixPerson/ChannelCompany
JLJordan LeeAI Business
CJCharlie Johnson Show-
MTMax TornowMax Tornow Podcast
HRAlex Hormozi-
CGCole Gordon-
SSSam OvenSetterlun University
JMJeremy Miner7th Level

Chunk IDs

Format: {SOURCE_ID}-{NNN} Examples: CG001-001, JL003-015

Decision IDs

Format: YYYYMMDDHHMMSS-{ORIGIN}-{DEST} Example: 20260305130249-CRO-CFO

Precedent IDs

Format: PREC-YYYY-NNN Example: PREC-2026-001

Foreign Keys

Rastreability graph:
file-registry.json
  β”œβ”€ source_id ───────────────┐
  └─ chunk_count                  β”‚
                                 β”‚
                                 β–Ό
CHUNKS-STATE.json β—„β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
  β”œβ”€ source_id
  └─ chunks[]
      └─ chunk_id ──────────────┐
                                 β”‚
INSIGHTS-STATE.json β—„β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
  └─ chunk_id                    β”‚            β”‚
      └─ insight_id ─────────────│───────────
                                 β”‚            β”‚
NARRATIVES-STATE.json β—„β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜            β”‚
  └─ evidence_chain[] (chunk_ids)           β”‚
                                              β”‚
decisions-registry.json β—„β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
  β”œβ”€ chunk_ids[]
  └─ sources[] (knowledge files)

Validation Tools

Python

import json
import jsonschema

def validate_state_file(state_file, schema_file):
    with open(schema_file) as f:
        schema = json.load(f)
    with open(state_file) as f:
        data = json.load(f)
    
    try:
        jsonschema.validate(data, schema)
        return True, "Valid"
    except jsonschema.ValidationError as e:
        return False, str(e)

CLI

# Validate all state files
python3 core/intelligence/validate_json_integrity.py

# Validate single file
python3 -m jsonschema -i CHUNKS-STATE.json core/schemas/chunks-state.schema.json

Schema Evolution

Version Increment Rules

  1. Never delete fields - Mark as deprecated
  2. Always validate before save - Use jsonschema
  3. Increment version on each schema change
  4. Maintain change_log for auditability

Migration

When schema changes:
  1. Create migration script: scripts/migrate_v{N}_to_v{N+1}.py
  2. Update schema file with new version
  3. Run migration on all state files
  4. Validate with new schema

See Also