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+# Closets — The Searchable Index Layer
+
+## What closets are
+
+Drawers hold your verbatim content. Closets are the index — compact pointers that tell the searcher which drawers to open.
+
+```
+CLOSET: "built auth system|Ben;Igor|→drawer_api_auth_a1b2c3"
+         ↑ topic           ↑ entities  ↑ points to this drawer
+```
+
+An agent searching "who built the auth?" hits the closet first (fast scan of short text), then opens the referenced drawer to get the full verbatim content.
+
+## Lifecycle
+
+### When are closets created?
+
+Closets are created during `mempalace mine`. For each file mined:
+1. Content is chunked into drawers (verbatim, ~800 chars each)
+2. Topics, entities, and quotes are extracted from the content
+3. A closet is created with pointer lines to those drawers
+
+### What's inside a closet?
+
+Each line is one atomic topic pointer:
+```
+topic description|entity1;entity2|→drawer_id_1,drawer_id_2
+"verbatim quote from the content"|entity1|→drawer_id_3
+```
+
+Topics are never split across closets. If adding a topic would exceed 1,500 characters, a new closet is created.
+
+### When do closets update?
+
+When a file is re-mined (content changed), its drawers are replaced and new closets are built from the fresh content. The old closet content is replaced via upsert.
+
+### What about stale topics?
+
+If a file's content changes and a topic no longer exists, the closet is rebuilt entirely from the new content — stale topics are gone. Closets are tied to source files, not to individual topics.
+
+If you add content to an existing file (e.g., a daily diary growing throughout the day), new topics are appended to the existing closet until the 1,500-char limit, then a new closet is created.
+
+### Do closets survive palace rebuilds?
+
+Closets are stored in the `mempalace_closets` ChromaDB collection alongside `mempalace_drawers`. If you delete and rebuild the palace, closets are recreated during the next `mempalace mine`.
+
+## How search uses closets
+
+```
+Query → search mempalace_closets (fast, small documents)
+         ↓
+    top closet hits → extract drawer IDs from pointer lines
+         ↓
+    fetch drawers from mempalace_drawers (full verbatim content)
+         ↓
+    BM25 hybrid re-rank (keyword match + vector similarity)
+         ↓
+    return results to user
+```
+
+If no closets exist (palace created before this feature), search falls back to direct drawer search. Closets are created on next mine.
+
+## Limits
+
+| Setting | Value | Reason |
+|---------|-------|--------|
+| Max closet size | 1,500 chars | Leaves buffer under ChromaDB's working limit |
+| Max topics per file | 12 | Keeps closets focused |
+| Max quotes per file | 3 | Most relevant only |
+| Max entities per pointer | 5 | Top names by frequency |
+| Max response chars | 10,000 | Prevents hydration blowup on large files |
+
+## For developers
+
+Closet functions live in `mempalace/palace.py`:
+- `get_closets_collection()` — get the closets ChromaDB collection
+- `build_closet_lines()` — extract topics/entities/quotes into pointer lines
+- `upsert_closet_lines()` — write lines to closets respecting the char limit
+- `CLOSET_CHAR_LIMIT` — the 1,500 char limit constant