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2 changes: 1 addition & 1 deletion agents/faculties/memory/AGENTS.md
Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ memory.sh "delaunay regularization prior work"
- **No indexes, no embeddings, no new infra** — grep + the wikis' own
structure, the same as a careful human session, kept deterministic.
- **No layout coupling** — sub-wikis are discovered at query time
(`*_wiki/` directories); when Memory grows a wiki, the faculty sees it with
(`wiki/<domain>/`, plus legacy root `*_wiki/`); when Memory grows a wiki, the faculty sees it with
no edits (the standing "do not couple to Memory's internal layout" rule).
- Operational history stays Mind's: `complete.md` is *read* here as a recall
surface, but the boundary prose in ORGANISM.md is unchanged.
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6 changes: 5 additions & 1 deletion agents/faculties/memory/_memory.py
Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,11 @@ def terms_of(query: str) -> list[str]:
def surfaces(memory: Path | None, assistant: Path | None, mind: Path | None):
"""Yield (surface-name, root, md-file) triples, discovered at query time."""
if memory and memory.is_dir():
for wiki in sorted(memory.glob("*_wiki")):
# wiki/<domain>/ is the current layout; root-level *_wiki/ is the
# pre-2026-07 layout, kept for older checkouts and forks.
wikis = sorted(d for d in memory.glob("wiki/*") if d.is_dir())
wikis += sorted(memory.glob("*_wiki"))
for wiki in wikis:
for f in wiki.rglob("*.md"):
yield f"PyAutoMemory/{wiki.name}", memory, f
if assistant and assistant.is_dir():
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2 changes: 1 addition & 1 deletion skills/sampler_pipeline/reference.md
Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,7 @@ table.
the candidate on lensing use cases via `autolens_profiling` — the
`/profile_likelihood` skill drives the sweep machinery; A100/HPC runs go
through that repo's conventions.
- Record durable findings in `PyAutoMemory/methods_wiki/concepts/
- Record durable findings in `PyAutoMemory/wiki/methods/concepts/
sampler-benchmarks.md` (internal; never cited in public output).

## Stage 3 — promotion: the PyAutoFit implementation
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