Brain Bootstrap

brain-bootstrap

brain-setup scaffolds an empty brain — six root-page templates plus an empty pages/. This skill fills it with real, durable project knowledge for the first time. It is the bridge between "a brain exists" and "the brain is worth reading".

You gather information by reasoning over the project itself — reading code, docs, and git log, or interviewing the user — but you never write the brain by hand. Every landing of knowledge is a brain CLI subcommand.

NEVER hand-edit any file under the brain directory. All reads and writes MUST go through the brain CLI. Manual edits are unsupported and illegitimate. There is no validator and nothing at the file layer can catch a bad manual edit; correctness is guaranteed only by going through the CLI, so a hand edit silently breaks the brain's invariants.

The exact command surface (update-root / create-page / update-truth / reindex / ls …) and the page-category taxonomy live in the brain-page skill — read it before creating or modifying any page. Resolve <brain-page-bundle> to wherever that skill is installed (in the brain.md source repo, skills/brain-page/); define the shell function brain() { node <brain-page-bundle>/bin/brain.mjs "$@"; } (a function is portable across bash and zsh, unlike BRAIN="node …"; $BRAIN …, which only word-splits in bash) and run everything from the project root.

Step 0 — Pick the mode

Inspect the project to decide which path you are on:

• Brownfield — there is substantial source code, and/or real git log history. There is something to read; go to Brownfield.
• Greenfield — a near-empty repo: no meaningful source, little or no history. There is nothing to read; go to Greenfield.

When it is genuinely mixed (a little code, a little history), prefer Brownfield for whatever can be inferred, and fall back to interview questions for the parts the code can't tell you.

Brownfield — synthesize from code, docs, and history

Gather from three sources, then synthesize (do not transcribe):

1. Existing code — directory structure, module boundaries, entry points, the tech stack and dependencies (manifest files: package.json, pyproject.toml, go.mod, Cargo.toml, …). This is your strongest evidence for architecture and stack.
2. Existing docs — README, docs/, CONTRIBUTING, design notes. Good for stated intent, goals, and naming.
3. git log — read the commit messages (git log --oneline -n 200 and spot-read full messages for the interesting ones). Mine them for the real decisions that were made over time.

Draft the six root pages

Write each with echo "<body>" | brain update-root <slug> (body on stdin). Lean on ```mermaid blocks (graph / sequenceDiagram / mindmap / gantt) to keep them visual.

• architecture — layers, modules, boundaries, a mermaid graph. Inferable from code — write it with confidence.
• stack — domain / choice / rationale table from the dependencies and how they're used. Inferable from code.
• flow — the end-to-end path of a typical request/operation, a mermaid sequenceDiagram. Inferable where the entry points and call paths are clear.
• mindmap — main feature branches from the project root, a mermaid mindmap. Inferable from the module/feature layout.
• background — why the project exists / goals / non-goals / target users. Often NOT inferable from code — see the guardrails.
• roadmap — milestones, a mermaid gantt. Usually NOT inferable from code — see the guardrails.

Capture key historical decisions as pages

For each genuine decision you can see in the history or the code (e.g. "switched from X to Y", "adopted pattern Z", a deliberate constraint), create a decision page and fill in its understanding:

brain create-page --id <kebab-id> --category decision --title "<one-line decision>" --source "git log / code"
echo "<what was decided, the alternatives, the rationale, the blast radius>" | \
  brain update-truth --id <kebab-id> --summary "captured from project history" --source "git log"

Link related pages and the relevant root area with [[page-id]].