Inventory dated 2026-05-02 is preserved as a point-in-time snapshot. Today's
updates are layered on top in a dated addendum section after "Findings
summary" and before "Phase 1 — Scripts" so the original snapshot reads as
written and readers can see what changed and when.
Resolved:
- NREM-shape divergence #1 (`dream.py` cumulative cross-night exclusion
500-cap) — replaced with session-scoped novelty.
Corrections to existing findings:
- `stage2_metadata` lives on `stage_3_queue`, not `stage_2_queue` (the
2026-05-02 entry implied otherwise). Verified by direct schema read.
- Stage 2 char_length gate runs *before* the Mistral call. For sub-2000-char
docs, Mistral is never invoked — frames are not extracted then discarded,
they are simply not extracted. Reframes the architecture's "Stage 2
produces orientation for everything" commitment.
New findings (from the 2026-05-03 frame analysis):
- `ingest_conversations.py` bypasses Stage 2 entirely. 198 conversation
sources have zero frame coverage by design. Combined with the char-gate
exclusion and Stage 2 failures, only 56% of corpus has any frame data.
- All 14 voice notes and all 39 dream outputs are in the 339-doc gap.
Primary capture and self-reflection channels are silent to the frame
system; dreamer cannot frame-condition on its own output.
- File-type \u00d7 frame stratification provides discriminating signal that
cross-links Improvement #3 to the existing `embeddings.type` NULL-rate
finding.
Same NREM shape as the original cumulative-exclusion bug — the architecture's
stated commitment and what the code actually does diverge silently. This is
exactly what the inventory exists to surface.
Read-only inspection of the frame data Mistral produces in Stage 2, in
service of Track 2 substrate design (Step 2.4 operation set spec).
Artifacts:
- New SQL view `stage2_frames_v` over `stage_3_queue.stage2_metadata`
(CREATE OR REPLACE; idempotent; raw JSONB exposed alongside structured
fields so worker-version drift is inspectable).
- Analysis script: frequency, label-hygiene collisions, per-doc count,
co-occurrence (top-K), file-type \u00d7 frame cross-tab, worker-version split,
data-gap accounting, corpus-wide coverage.
- JSON sidecar for diff-across-runs reproducibility.
- Markdown report with explicit Track 2 viability section.
Headline findings:
- Frames cluster meaningfully on the framed-doc subset (subject to
validation on larger samples for the file-type cross-tab).
- Only 56% of corpus has frame coverage. 198 conversation sources bypass
Stage 2 by design (`ingest_conversations.py` writes directly to
embeddings); 339 short docs (<2000 chars) skip Mistral by char-gate;
12 Stage 2 failures.
- All 14 voice notes and all 39 dream outputs are in the data gap.
Primary capture and self-reflection channels are silent to the frame
system. Dreamer cannot frame-condition on its own output.
- 54 normalized label collisions (`Professional Experience` vs
`Professional_Experience`, etc.) — any router must normalize first.
- "Education" is a near-universal frame (36% of frame-extracted docs);
cheap 20-doc hand-inspection diagnostic in report \u00a78 to distinguish
prompt artifact from corpus shape.
- File-type \u00d7 frame stratification is concrete signal that ties to
Improvement #2 (`embeddings.type` backfill); currently NULL for 71% of
rows.
No production code touched. View is droppable; script is read-only.
These are working artifacts of the 2026-05-02 Track 1 stabilization
work. Versioning them alongside the code keeps the operational
narrative coherent and gives future sessions clear reference docs.
The inventory document includes the cross-repo verification finding
on share_time — captured at the document level so future sessions
don't repeat the same dead-code mischaracterization.
aaron