# Implementation Status: Brain Interface Complete

## Milestone: Foundation Orchestration Layer — DELIVERED

### What was delivered
- **ops/brain/** — 4 bash+Python CLI scripts, zero external dependencies
  - `brain-query.sh` — Multi-source grounded Q&A via Gemini 2.5 Flash
  - `brain-push.sh` — Upload new sources to NotebookLM with local mirror safety
  - `brain-pull.sh` — Sync source inventory from NotebookLM API
  - `brain-status.sh` — Notebook state report (sources, words, tokens, sync status)
  - `_brain_common.py` — Shared module: config, auth, API helpers, source loading, session logging
- **GitHub repo** — `jgatlit/CMS-aiChemist` (private), pushed to origin/master
- **Session logging** — All operations logged to `.brain/sessions/YYYY-MM-DD.log`
- **Source inventory** — `.brain/inventory.json` synced with NotebookLM API
- **Milestone/Decision Loop** — Encoded in CLAUDE.md: query brain at milestones, proceed autonomously, push status back

### End-to-end validation results
- PULL: 4 sources synced successfully
- QUERY: Cross-source grounded answer returned correctly (Penpot/Stitch/Claude Code workflow)
- PUSH: Session notes uploaded, SOURCE_STATUS_COMPLETE, local mirror saved first
- STATUS: 5 sources, 9,230 words, 5/5 mirrored, auth valid

### Current notebook sources (5 total)
1. Agentic Frontend CMS Spec (5,030 words)
2. Research - Development Pipeline (1,411 words)
3. Research - Penpot Assessment (1,269 words)
4. Research - Agentic CMS Architecture (1,385 words)
5. Session Notes - 2026-04-06 - Brain Interface Built (135 words)

### Architecture decisions made
- Bash + Python hybrid (bash wrappers call Python for API/JSON)
- Query bridge pattern: local source mirrors → Gemini 2.5 Flash as grounding context
- Local-first safety: mirror always written before API push
- Project root resolution: scripts callable from any working directory
- Zero pip dependencies: Python stdlib only

### Next recommended priority (from brain query)
Per architecture spec: Align GitHub issue templates, PR templates, labels, and branch protections to the handoff model. Then pilot one bounded surface end-to-end.

### Known limitations
- NotebookLM API has no chat/query endpoint — bridge uses Gemini with source content
- Source GET returns metadata only, not content body — must maintain local mirrors
- NotebookLM API does not support notebook rename or delete