Cognitive Brain

Unified memory system modeled on human brain architecture. One CLI (brain) for all memory operations.

Architecture

Installation

# 1. Initialize the database
sqlite3 brain.db < scripts/schema.sql

# 2. Link the CLI
ln -sf "$(pwd)/scripts/brain.sh" ~/.local/bin/brain
chmod +x scripts/brain.sh

# 3. (Optional) Migrate existing daily logs
python3 scripts/migrate-daily-logs.py --dir /path/to/memory/ --db brain.db

Environment Variables

Credentials & Scope

Required for brain proc evolve only:

• BRAIN_LLM_KEY — Your API key for the LLM provider. Set via env var or brain config set key .
• No credentials are auto-discovered or read from platform stores.
• Without a key, proc evolve falls back to local pattern-based evolution (no LLM needed).

Data scope:

• All data stays in your brain.db file (local SQLite).
• brain facts reads/writes BRAIN_FACTS_DB (default: facts.db in skill directory).
• brain wm reads/writes SESSION_STATE (default: SESSION-STATE.md in workspace root).
• No data is sent externally except LLM API calls during proc evolve.

Quick Reference

Store & Recall

brain store "Fixed the deploy pipeline" --title "Deploy Fix" --emotion relieved --importance 8
brain ingest "Docker OOM at 3 AM" --title "OOM Event" --source mqtt  # attention-gated
brain recall "deploy pipeline" --type all --limit 5
brain episodes 2026-03-15
brain emotions 7
brain important 8 14

Facts (Semantic Memory)

brain facts get Darian favorite_movie
brain facts set Mae birthday "September 12" --category date --permanent
brain facts search "SSH" --limit 5
brain facts list --entity Darian --limit 10
brain facts stats

Procedures (Cerebellum)

brain proc create deploy-api --title "Deploy API" --steps '["Pull latest","Run tests","Deploy"]'
brain proc success deploy-api
brain proc fail deploy-api --step 2 --error "Tests timed out" --fix "Increased timeout to 60s"
brain proc evolve deploy-api           # LLM rewrites steps from failure patterns
brain proc evolve deploy-api --dry-run # preview without applying
brain proc history deploy-api          # full evolution timeline
brain proc list

Attention Filter

brain filter "GPU temperature 72°C" --source mqtt    # → discard (routine)
brain filter "SSH brute force from new IP" --source security  # → store (novel threat)

Consolidation

brain consolidate --dry-run    # preview what would be processed
brain consolidate              # run sleep replay

Health (Soul Erosion Detection)

brain health           # 7-metric scored report
brain health -v        # verbose with all details
brain health --json    # machine-readable for crons

Configuration

brain config show              # current LLM config
brain config set model gpt-4o  # change model
brain config set url http://localhost:11434/v1/chat/completions  # switch to Ollama

Multi-Agent

brain --agent bud store "Patrol complete" --title "Bud Patrol" --importance 3
brain --agent bud proc list   # sees own + shared procedures
brain who                     # show all agents in the system

Procedure Evolution Flow

The core innovation — procedures that rewrite themselves from failure patterns:

1. Record failures with step-level granularity: brain proc fail --step N --error "desc"
2. At 3+ failures, brain suggests evolution
3. brain proc evolve analyzes patterns:
• Repeat offender steps (same step failing multiple times)
• Brittle chains (consecutive step failures)
• Error keyword clustering (timeout, auth, permission, etc.)
4. LLM synthesizes and rewrites steps — adds pre-checks, reorders, annotates with [vN: reason]
5. Local fallback if LLM unavailable — pattern-matching inserts defensive steps
6. Full version history preserved: brain proc history

Health Metrics

Seven metrics, each scored 1-10:

Schema

Database: SQLite with WAL mode, FTS5 full-text search, foreign keys.

Tables: episodes, episodes_fts, facts, facts_fts, procedures, procedure_history, working_memory, consolidation_log, brain_meta.

Initialize with: sqlite3 brain.db < scripts/schema.sql

Files