Memory — PyAutoMemory#

What it owns: long-term domain knowledge — what the science says. Cross-linked wikis distilling literature, concepts and methods, backed by canonical citation metadata, so agents planning domain work reason from verifiable knowledge instead of vibes.

Repo: PyAutoLabs/PyAutoMemory

The read contract#

Memory is pull-only, on demand. No agent loads it automatically; the Brain’s memory faculty consults it when a task is scientific, returning a cited digest (pages + snippets) rather than bulk content. Operational history — what the organism did — deliberately lives in the Mind (complete.md, issues), not here: Memory is what the domain says, Mind is what the organism did.

The pieces#

  • Sub-wikis, each self-contained with the same schema: in the live instance, strong lensing, black holes, detector calibration, inference methods, galaxy evolution.

  • bibliography/ — canonical BibTeX metadata every wiki claim cites against; make validate-literature-citations keeps claims and metadata honest together.

  • An index-first layout — agents reach pages through index.md chains, never hard-coded paths, so the wiki can grow without breaking readers.

For an adopter#

You do not fork this repo — the content is the upstream instance’s personal research knowledge. You create your own Memory with the same shape: sub-wikis per domain, the shared schema, the bibliography layer, the validation make target. The generic asset is the structure (MIT-licensed; the upstream content itself is CC BY 4.0), and the coupling point to the rest of the organism is a single keyword map in the Brain’s memory faculty — adopter config like everything else.