# photonlayer Drop-in

One zip. Two halves. The NotebookLM studio media rides **inside** this zip.

## What's inside

```
photonlayer-dropin/
  for-humans/   — read & listen first
    photonlayer-primer.md
    studio/
      🎧 photonlayer-audio.m4a   — NotebookLM AUDIO OVERVIEW (play this first)
      📄 photonlayer-report.md  — the written deep-dive briefing
      audio-overview-prompt.md  — the prompt that generated the audio
  for-ai/       — the searchable knowledge pack (wire this into your agent)
    photonlayer-kb.rvf            — single 384-dim bge-small vector DB (the "brain")
    photonlayer-kb.passages.jsonl — full passage text (tagged source_type: src|test|example|doc|config)
    photonlayer-kb.ids.json       — id → passage index
    photonlayer-symbols.json      — exact public API: every symbol + signature + doc + location
    photonlayer-dep-graph.json    — component dependency graph (what depends on what)
    photonlayer-entrypoints.json  — build/test/run/install commands + binaries
    ask-kb.mjs · kb-mcp-server.mjs · kb.config.mjs · resolve-deps.mjs · package.json
  README.md     — this file
  manifest.json — build metadata + Gate A score
```

## Studio (NotebookLM)
Start with the audio: play `for-humans/studio/photonlayer-audio.m4a` — a friendly two-host overview of photonlayer.
Prefer reading? Open `for-humans/studio/photonlayer-report.md`.


## Three steps to wire the AI half in
```bash
# 1 — unzip + install (two deps, Node 18+)
unzip photonlayer-dropin.zip && cd photonlayer-dropin/for-ai && npm install

# 2 — ask the brain a question straight away
node ask-kb.mjs photonlayer "what does photonlayer actually do"

# 3 — point your AI host at it with a .mcp.json in your project root:
#   { "mcpServers": { "photonlayer-kb": { "command": "node", "args": ["for-ai/kb-mcp-server.mjs"] } } }
```

Built with the Repo-Primer recipe (ADR-0001 v1.3.1). Embedder: Xenova/bge-small-en-v1.5 (384-dim, single variant, recipe v1.3.1).
Source: github.com/ruvnet/photonlayer @ 5b5dd7247bd9e0f61bdce2fee6730692b9606977.
