manga-recap-pipeline/JOURNAL.md

JOURNAL

Append-only, newest last. One block per session or run. Not a changelog: this records what happened on the day a number was produced, so a later postmortem can find it.

2026-08-11 Audit second pass [no task]

Command: none. Source reading only. Outcome: finished. AUDIT.md grew from 565 to 771 lines with a ## Second-pass findings section: 4 new P0, 6 new P1, 13 P2, 5 additions to the Phase 1 list. Produced: commit 6d9df5b, AUDIT.md:566.

2026-08-11 Audit Phase 1 implemented [#203]

Command: python worker_scene.py worker_script.py worker_vision.py session_manager.py, pytest -q --ignore=test_api.py in the orchestrator. Outcome: finished. All self-checks pass, 108 orchestrator tests pass. No GPU work, no pipeline run. test_api.py was skipped because fastapi is not installed in the workpc venv. Produced: decisions/audit-phase1.md, caveats/audit-open.md, ROADMAP.md, and this scaffold.

One existing test asserted the bug: test_name_binding.test_conflict_flags_and_stays_unnamed relied on orphan flags leaking into every chapter, because it never created panel rows. It now creates them.

2026-08-11 Orchestrator half committed and deployed [no task]

Command: pytest -q --ignore=test_api.py, then docker compose up -d --build orchestrator on homesrv. Outcome: finished. 108 tests pass. Commits 1c60710 (orchestrator half) and 94bd4d8 (minio pin) in /mnt/server/home/kami/docker-apps. Orchestrator and minio both answer health on homesrv.

The rebuild recreated minio as a side effect and it crash-looped with exec format error: the compose pin was the arm64 manifest digest of minio/minio:latest and homesrv is amd64. Repinned to the amd64 digest. Nothing about Phase 1 caused this, but any compose action that recreates minio would have hit it, so it was latent, not new.

Still unrun against a real chapter.

2026-08-11 S3 viewer and storage swap, tasks #116/#117 [#116 #117]

Command: docker compose on homesrv, dig, openssl s_client. No pipeline, no GPU. Outcome: partial. Viewer works, storage swap staged and unfinished.

#117 needed no new software. stowage at ~/docker-apps/stowage was already configured against the manga MinIO and had been dead since 2026-07-19 with exec /sbin/tini: exec format error: its digest pin was the arm64 manifest. Repinned to amd64 sha256:91be7f13, chowned data/ to uid 65532 for the new image, and it serves. MinIO had the identical bug, repinned to sha256:a1a8bd4a. A sweep of all 470 local images on homesrv found exactly those two arm64; nothing else in the homelab is affected.

#116 is staged, not done. rustfs runs alongside MinIO on 127.0.0.1:9010/9011, pinned sha256:19b105cc, data at /mnt/hdd2/rustfs. Buckets are empty: the mc mirror of audio layers manga panels raw video (350M, all in manga) has NOT run. /mnt/hdd2/minio/data is untouched and is the rollback. RustFS is 1.0.0-beta.12, labeled build-type=prerelease. Cutover would give rustfs 9000/9001 and repoint MINIO_ENDPOINT=minio:9000 in the orchestrator plus stowage/config.yaml; transport.py:95 needs no change if rustfs takes 192.168.1.104:9000.

Side quest, unrelated to the pipeline: the shared 41-domain cert stopped renewing. Root cause was DNS, not nginx. Every *.kvmx.ru name pointed at a hard A record for 109.229.102.117 while the line had moved to 109.229.127.149; the Mercusys DDNS at kvmx-home.mercusysddns.com was correct the whole time but nothing in the zone referenced it. Fixed with CNAME * -> kvmx-home.mercusysddns.com at reg.ru. Certificate now issues.

Two measurement traps worth remembering. The ISP transparently intercepts ports 80 and 443 by Host/SNI, so curl from workpc to ANY address returns kvmx.ru content and proves nothing about external reachability; bare TCP connects also succeed against arbitrary addresses and then hang. Three wrong root causes came out of trusting those probes before checking them.

Also patched ~/scripts/migrate-kvmx-https.sh:54 on homesrv. need_stream_module used sudo -n nginx -V and sudo -n nginx -T; the NOPASSWD rule covers only nginx -t, so it reported "stream module is not loaded" whenever it meant "could not ask for a password". Both checks now run without sudo. bash -n passes and both conditions evaluate true.

2026-08-11 Per-artifact buckets, rustfs buckets, baseline chapter run [#116]

Command: mc mb on rustfs, docker compose up -d --build orchestrator, pytest -q --ignore=test_api.py, ./start_workers.sh, then /job/create + /stage/clear + /job/resume for chapter 7c944dd4-e972-42c7-ba60-9f6939548e80 of "Teto X Egen" as job 778297bc-e7ce-439d-91b5-8a027060d17f. Outcome: partial. Storage split landed and is proven by the run. The run itself was still in direct when the session ended. Produced: decisions/storage-layout.md, caveats/speaker-attribution.md, 109 orchestrator tests pass.

Artifacts now split one bucket per class instead of everything under manga (decisions/storage-layout.md#bucket-per-artifact). Both MinIO and rustfs hold all six buckets. The run put 79 pages in raw and 116 panel crops in panels, so the split works end to end.

Two containers on homesrv had been dead for two weeks and blocked the work. manga-fetch was exited, so /job/create failed with httpx.ConnectError; manga-web was exited, so manga.kvmx.ru had nothing behind it on port 8083. Both started with docker compose up -d. Neither is related to the storage change. Neither was caught by any check, because nothing watches these containers.

Stage timings, 116 panels: crop 85s, vision ~4min, identity ~1min, reconcile ~7min for 35 pairs, dialogue ~8min. Faster than the 2026-07-17 run at 75 panels. The webtoon crop that 500'd in July succeeded this time.

Quality cross-check against the panel images, the point of the run. Dialogue text extraction is accurate. Character detection is accurate. Speaker attribution is not: three of three sampled two-character panels attribute both speakers to the wrong person, always swapped (caveats/speaker-attribution.md#tail-is-not-geometry). 24 of 81 speech lines resolve to a named character, which is the Phase 1 headline metric at 30%, and the sample says that 30% is not trustworthy. 26 of 113 detected people got an identity, and 25 of those 26 went to one character that turns out to cover two different women.

The run then reached scene 116/116 and failed in script at 87/116, not on OOM: 28 beats were rejected by the script verifier as unsupported-proper-noun: ['Choi', 'Haeseon'] (caveats/speaker-attribution.md#multiword-name-verifier). No two-word cast name can pass that check.

2026-08-11 Speaker provenance and the multi-word cast name

Command: .venv/bin/python worker_vision.py, pytest -q --ignore=test_api.py in the orchestrator. Outcome: both pass, 110 orchestrator tests. Nothing deployed, no GPU work, no pipeline run. Produced: decisions/speaker-attribution.md, two caveats rewritten.

_annotate_speaker_methods stopped stamping tail on a model guess. With two or more characters present the guess is dropped to unknown at confidence 0.0. With one present it is kept as model_solo at 0.7, the same claim the solo backstop already makes (decisions/speaker-attribution.md#no-fake-tail). Grounded som_face and solo_prior rows are untouched. Nothing outside worker_vision.py reads the literal tail, checked across both repos.

verify_script now tokenizes each cast name into allowed, so Choi Haeseon passes as two tokens (decisions/speaker-attribution.md#multiword-cast-names). That is the 28 beats job 778297bc lost.

The remaining ['Blur'] beat is a true positive that still halts the whole chapter, now recorded as caveats/speaker-attribution.md#one-word-halts-chapter.

Neither fix is live. The orchestrator container is not rebuilt and the workers are not restarted.

2026-08-11 Rerun from dialogue: the honest speaker number is 9%

Command: /job/cancel, /stage/clear dialogue, ./start_workers.sh, /job/resume on job 778297bc-e7ce-439d-91b5-8a027060d17f, twice. docker compose up -d --build orchestrator three times. Outcome: dialogue 116/116. 112 orchestrator tests pass, worker_vision.py self-check passes.

The named-speaker share is 9%, 9 of 95 speech lines, down from a reported 30% that counted fake tails. Multi-character panels contribute 0 of 40 lines by design. Single-character panels give 9 of 55. All 9 binds are Choi Haeseon, the row that covers two different women.

Five defects, four of them found by measuring the run rather than by reading code.

1. The fake tail label, fixed before the run (decisions/speaker-attribution.md#no-fake-tail).
2. The multi-word cast name in the script verifier (decisions/speaker-attribution.md#multiword-cast-names).
3. /stage/clear dialogue deleted nothing and reported success. dialogue and direct write onto the per-panel vision blob and had no _STAGE_TABLES entry, so run_stage_dialogue saw "dialogue" in vision and would have skipped all 116 panels. The proof is the second clear: 116 dialogue blobs and 75 direct blobs stripped that the first had left. This is caveats/audit-open.md#dishonest-clearing firing exactly where it was filed.
4. gemma answers the speaker field with whatever the prompt showed, most often the character description, and every such answer became a free-form name that no registry entry matched. 28 of 51 sampled lines (decisions/speaker-attribution.md#prompt-label-answers). After the fix, 3 of 95.
5. All 7 som_face lines pointed at a mark whose face paired to no present character, so the highest-trust provenance sat on a line with no speaker. Same defect class as the fake tail.

Identity is now the binding constraint, not attribution. 26 of 113 detected people carry an identity, 23%, and 25 of the 26 are the one over-merged row. Even perfect balloon binding caps this chapter near 23% named. The person who does hold an identity is stored as Lim Seonho while a separate row is named Seonho with alias Lim Seonho, so either name matches two rows, raises ambiguous-speaker and binds nothing.

Two more defects surfaced after dialogue finished. All 7 som_face lines pointed at a mark whose face paired to no present character (decisions/speaker-attribution.md#unpaired-mark). Then script halted at 112/116 because the narrator wrote "...Hm?" for the source line "Uh... hum...?", and both verifier rules fired on that two-letter interjection (decisions/speaker-attribution.md#interjection-false-positive). After the fix, script passed 116/116, the first time this chapter has cleared the verifier. tts then ran for the first time.

The run then completed end to end for the first time: tts 116/116, layers 116/116, render 116/116, assemble 1/1, finished 2026-08-11T20:08:16Z. s3://video/ holds 49 clips and a 50MiB chapter.mp4, s3://audio/ 49 objects at 32MiB. The per-artifact bucket split is now proven for every class except layers (decisions/storage-layout.md#bucket-per-artifact).

Two honesty defects surfaced at the finish, both recorded rather than fixed. layers reported completed 116/116 with an empty bucket, and the completed job still carries error: "partial: 112/116 completed" from the failure three resumes earlier.

2026-08-12 — the video got watched

No pipeline ran. The user watched chapter.mp4 for the first time and read out 19 timestamped defects. That found more than the previous four sessions of measuring, because the recorded metrics were all measuring whether code ran rather than whether the result was right.

Two measurements came out of it. First, chapter.mp4 is video 436.39s over audio 363.67s, so the narration finishes 72.7s before the picture and the gap accumulates. The 49 clips are clean: every one is 25fps exactly, video and audio agree to 0.03s, and they sum to 363.6s. Assembly adds 72.7s of video and no audio. Second, this manga holds 19 character rows of which 3 carry a name, and Choi Haeseon holds 25 of the chapter's 26 identity assignments. That is why the video calls the colleague Choi, never names the MC, and flips gender.

The A/V bug was narrowed with a per-round probe over the 49 real clips. Round 0 of _assemble_batched is correct, losing only the xfade overlap per group. Round 1 turns 359s of video into 100s while the audio survives at 358.79s. The round-1 filtergraph is arithmetically correct, and re-running the same chain by hand over only the 6 encoded intermediates gives a correct 348.24s with no warnings. Round 1 differs by holding a 7th input: the leftover 49th clip, which _assemble_batched passes through un-encoded. That passthrough is a third path beside concat and xfade and is the prime suspect.

worker_render.py gained an FPS = 25 constant, fps normalization in the xfade branch to match the concat branch, a _stream_dur helper, and a self-check that compares video against audio rather than asserting the file is non-empty. The old check only asserted getsize(out) > 0, which is how a 20% sync failure shipped. Pinning -r FPS on the output encodes was tried and reverted: it collapsed the chapter to exactly 100.00s by dropping frames to force CFR, which the comment at the concat branch already warned about. None of it is committed and none of it fixes the chapter yet.

The fps inconsistency between the two branches is real but not proven to be the shipped cause. The scene graphs hold 356 cut against 6 fade_black, so the real run's final round most likely stayed on the concat branch where no mixing happens.

Panel 7, checked against the art

The same day, the user pulled up panel 7 and checked every detection by eye. It overturned the framing this file carried an hour earlier, and it overturned two theories I proposed before being corrected.

Panel 7c944dd4-e972-42c7-ba60-9f6939548e80_p007, a wide establishing shot of an office through a window, crop 900x1650. Vision emitted 6 characters. Zero of the two identity bindings are correct and the one character who matters is unbound. person_5, described as "yellow sweater", is Seonho in the foreground and got no identity. person_6 is the colleague, who has no name in the story, and was assigned Choi Haeseon at 0.9. person_2 is a background extra and was assigned Lim Seonho at 0.9. person_1 is a window frame with nobody in it. person_3 and person_4 are background extras.

Three defects stack, recorded as caveats/speaker-attribution.md#bbox-wrong-space, #no-anonymous-identity and #extras-as-cast. The bbox values are consumed as absolute pixels, and on this panel that puts all six boxes in the top third with two inside a speech balloon. Divided by 1000 four of the six fit tightly. Identity therefore embedded crops of balloon edges and window frames, which is how a 0.9 confidence lands on the wrong person. Blank crops embed alike, a plausible mechanism for one row absorbing 25 of 26 assignments.

Two claims I made and had to withdraw. First, that rescaling by 1000 makes the boxes correct: after scaling, person_1 still sits on an empty window frame and person_6 clips its subject, and the descriptions are unreliable anyway, since person_6 reads "white shirt" for a green dress. Second, that the constraint is 16 nameless rows needing names. The opposite is true. The pipeline mints names onto people who have none, and at least one nameless row is a real recurring person who should stay nameless.

The "26 of 113 detected people carry an identity" figure that framed the roadmap counted mostly background extras. It should not be quoted again.

2026-08-12, chapter assembly, root cause and fix

Reproduced the A/V collapse offline with 49 synthetic clips at ASSEMBLE_BATCH=8 and six fade_black boundaries. It came out worse than the shipped run: two round-0 groups of 8 fresh clips collapsed on their own, so the single-item passthrough theory from yesterday is dead (decisions/chapter-assembly.md#passthrough-innocent).

Bisected one collapsing group by truncating the chain stage by stage:

k=7 out= 52.52   correct
k=8 out= 52.52   the last xfade contributed nothing
    [v6][n7]xfade=duration=0.050:offset=52.500   <- [v6] is 52.52s long, 0.02s of margin

_xfade_chain took its durations from _audio_dur, which is format=duration, which is max(video, audio). Each clip's audio outlasts its video by about a frame, so the offset accumulator crept ahead of the picture. Once the creep passed the transition width, xfade emitted the transition and threw away the second input and every clip after it, at rc 0 with nothing on stderr.

Fix: offsets come from min(_stream_dur(v), _stream_dur(a)), every input is floored to a whole frame count and trim/atrimed on both streams, and _check_assembled now verifies each encode against the predicted timeline instead of trusting the exit code (decisions/chapter-assembly.md#offsets-from-min-stream, #check-assembled).

Verified on the 49 real clips of chapter 7c944dd4, re-downloaded from MinIO:

before  r1 n=7 XFADE  in v=359.29 a=359.60 -> out v= 99.96 a=358.79
after   r1 n=7 XFADE  in v=359.61 a=359.62 -> out v=358.76 a=358.76
chapter v=358.76 a=358.76 gap=+0.00        (shipped: v=436.39 a=363.67 gap=+72.72)

worker_render.py __main__ passes. Two checks were added there, because the existing 4-clip A/V assert passed all the way through the broken build. One asserts the frame-exact trim on both streams, one assembles three clips whose audio outlasts their video by 0.4s. Mutation-tested by putting _audio_dur back: the new check fires with video=1.80 audio=3.56 expected=3.56.

Not done: s3://video/.../chapter.mp4 is still the broken 436s file. Rebuilding it means clearing the assemble stage and resuming, which is CPU-only and was not run.

2026-08-12, the chapter rebuilt, and the bbox space settled

The rebuild came out byte-identical to the broken file. Clearing assemble and resuming produced video 436.392031s over audio 363.674667s and nb_frames 9902 again, which proved the xfade fix committed earlier today never runs for this chapter. With all-cut transitions assemble takes the else branch, a concat demuxer with -c copy.

Reproduced that path offline in seconds and got the shipped numbers exactly. The cause is mixed frame rates: 14 of the 49 clips are r_frame_rate=30/1 at time_base=1/15360, the other 35 are 25/1 at 1/12800. -c copy writes the output in the first input's timebase, so those 14 play 15360/12800 = 1.2 too long with their audio untouched. collage_cmd hardcoded -r 30, which yesterday's FPS sweep missed. decisions/chapter-assembly.md#mixed-rate-stream-copy.

Fixed collage_cmd to emit -r FPS, and made assemble probe r_frame_rate across the clips and route mixed rates through the re-encoding tree. Rebuilt:

before  v=436.392  a=363.675  nb_frames=9902  avg_frame_rate=22.69
after   v=364.120  a=364.122  nb_frames=9101  r=25/1

The 14 clips in the bucket are still 30fps. Assembly normalizes them, so the chapter is correct without re-rendering, but the fast stream-copy path stays disabled for this chapter until render re-runs.

The bbox space is 0-1000, not pixels. Pulled all 113 detections from /review/identity and measured: 47 boxes have x2 past the 900px panel width, none has y2 past 1000 on panels 1257 to 2307px tall, 21 clamp at exactly 1000 in x, and the whole range is [0, 1000]. /vision now converts to pixels before returning, so identity crops, gated face pairing, the set-of-mark boxes and the review UI all read pixels (decisions/identity-bbox.md#bbox-is-normalized).

Checked by eye the way the user did. Drew the converted boxes on panel 7: five of six land on their subject, including person_5, who is Seonho in the foreground with headphones and carried no identity. person_1 still frames an empty window mullion, which is the extra-versus-cast caveat, not this one.

Not done: vision and identity have not re-run, so every box, embedding and ref_image_uris in the registry is still from the wrong space. That rerun is GPU work and was not started.

2026-08-12, third session — the rerun, and the run that did not count

Asked: move on from the chapter rebuild. Scope chosen mid-session: reset the registry, rerun vision, identity and reconcile only, and inspect before spending the ~80 minutes downstream.

The registry had to be wiped first, and nothing could do it. clear_stage_data maps identity to identity_assignments only and spares characters on purpose (db.py:790), because the registry is cross-run. So a rerun would have matched fresh crops against 19 stale grid-space embeddings and kept the duplicate Lim Seonho / Seonho rows that raise ambiguous-speaker. Added db.reset_registry and POST /characters/reset (confirm=true required), which also clears identity_assignment_sources — untouched by any stage clear, and a leftover manual row there makes assign_identity refuse the next model assignment (db.py:663). Covered by test_db.py:TestResetRegistry; 115 orchestrator tests pass. The orchestrator image bakes its source, so it needed docker compose up -d --build orchestrator.

The first full cycle was void: the worker was serving pre-fix code. vision + identity + reconcile completed 116/116/20 and reproduced the defect exactly — 46 of 110 boxes past the 900px panel width, coordinates clamping at 1000. The vision worker started 12:00:09, worker_vision.py changed 12:11:35, and the commit carrying _bbox_to_pixels landed 12:16:22. Python had already bound the old module. Nothing in the stage output said so (decisions/identity-bbox.md#stale-worker-invalidates). Added check_stale.sh, which compares every worker's process start against its module mtime and exits non-zero; mutation-tested by touching worker_tts.py.

The rerun against restarted workers. 8 minutes for all three stages.

                        before        stale run      after
x2 past panel width     47/113        46/110         0/110
coords exactly on 1000  21            27             1
max y2                  1000          1000           2307
characters              19            8              8
coverage                26/113 = 23%  77/110 = 70%   77/110 = 70%
top character's share   96% Haeseon   47%            47%

Choi Haeseon, which had absorbed 25 of 26 assignments, no longer exists in the registry. On panel 7 Seonho is bound for the first time, and the unnamed colleague took an anonymous id instead of being called Choi Haeseon at 0.9.

Fixing the boxes made the extras problem worse. With crops finally landing on their subjects, a background extra bound to Seonho at confidence 1.00, putting an extra into the lead's reference set. /vision now stamps has_face per character via face_detect + _pair_faces_to_present, and identity skips has_face is False before it crops or embeds (decisions/identity-bbox.md#face-gates-enrollment). Fails open on a missing or raising detector. Self-checked in both workers. Not yet proven on a GPU run — that is the next command.

Deleted along the way and not recoverable: the rebuilt chapter.mp4 and all 49 clips, by the cascade from /stage/clear vision. The user chose not to keep a copy.

2026-08-12, fourth session — identity 2b, the resolver NONE branch

Asked: "how much will has_face help with character and identity problems?", then "fix 2b first".

Answered the first honestly: has_face reaches 2 of 6 detections on panel 7 and nothing else. It does not touch naming or merging, and it cannot touch the chibi at 1:35, because an anime face detector detects a chibi face. Also flagged its real cost: the model is face-only by design, so back-turned cast lose enrollment along with the extras, and coverage is where that shows up first.

Measured before writing anything, read-only, no GPU:

registry: 8 characters, 1 named -> ['Seonho']
detections: 110  assignments: 77 = 70% coverage
spread: Seonho 36, character_565c88 24, character_759e23 9, character_f7a4fd 3,
        character_25f682 3, character_d72710 1, character_823aba 1

That killed the assumed cause. Anonymous ids already recur, so the identity worker's own pending-promote path gives stable anonymous identities. The defect was elsewhere.

/vision/resolve can answer "none of these" and always could: worker_vision.py:1071 returns state="new" for choice: 0 and state="unresolved" for an out-of-range index. service.py read only character_id and unassigned every crop of the tracklet for either. The stale ponytail: comment above that block named the real blocker and was right: minting needs an embedding_uri the orchestrator cannot compute, since siglip and gemma cannot both be resident.

Fixed by carrying the embedding, not by adding a GPU pass. /identity/resolve writes each crop's embedding to the crop's key with a .npy suffix and returns emb_uri. tracklets.resolve_outcome holds the three-way decision as a pure function. service.py mints via the existing create_character and falls into the existing assign loop. decisions/identity-bbox.md#none-mints-an-anonymous-character.

Checks: worker_identity self-check ok, tracklets self-check ok, 115 passed on homesrv. Deployed: image rebuilt, resolve_outcome verified inside the running container, audit_registry.py re-copied after the recreate. Vision and identity restarted, ./check_stale.sh exits 0.

New trap: tmux respawn-window -k does not re-run the window command. It leaves a bare shell and the worker down. Both workers were dead for two minutes before /health caught it.

Not run: the GPU cycle. has_face and the NONE mint are both unproven on real panels and now land in the same run.

2026-08-12, fourth session, continued — identity 2c, extras versus cast

Asked: "fix extra-vs-cast?"

Traced the three places that read vision["characters"] raw before changing anything. That corrected an inference made earlier in the session. build_scene already drops an unassigned detection from characters and present (worker_scene.py:63), so extras never reached the cast list at all.

The leak was their ACTIONS. actions was built from every detection, and that list is what the script prompt renders and what the correctness verifier uses as evidence. So a background extra's "standing at the window" arrived as a fact about the panel with no character attached, and the verifier confirmed it, because the action really was in the blob. That is a second mechanism behind the invented-narration complaints in item 3, independent of the model inventing anything.

Gated two consumers on has_face is False, matching the enrollment gate's semantics exactly: worker_scene's actions/action, and service._beat, which picks the director's "who" from the first three detections and falls back to an action when a detection has no name.

Left service._present_characters ungated on purpose. It builds the dialogue stage's candidate speakers and the set-of-mark boxes. An extra picked as speaker already resolves to unknown, not to a wrong name, so the failure is contained. And the gate's cost lands hardest there, since a character drawn from behind has no face box and gating would delete a real speaker from the only list that can attribute their line. decisions/identity-bbox.md#extras-gate-consumers.

Checks: worker_scene self-check ok with three cases (cast action survives, faceless dropped, missing key survives), 115 passed on homesrv. Deployed: image rebuilt, _beat verified inside the container, scene worker restarted, ./check_stale.sh clean. Committed ca46617 and 8b27aec.

Still not run on a GPU. Three changes now ride the same cycle: has_face, the NONE mint, and this.

2026-08-12, fourth session, continued — identity 2d, merge and split

Asked: "2d? merge and split?"

Checked the registry before planning anything, and 2d as written is stale. The registry reset earlier today deleted both worked examples. There is no Lim Seonho to merge into, character_afa7623b does not exist, and the current registry is 8 rows with one named character (Seonho). Nothing to merge or split until the rerun mints a new set.

So the useful work was the safety net for that rerun, since reconcile runs inside it. The caveat's cost line was the reason: one bad merge was unrecoverable without rebaselining the whole manga, and the cycle about to run includes a merge pass over embeddings nobody has seen yet.

merge_characters no longer deletes the loser. It sets merged_into = keeper, so the row keeps its embedding, description and gender, and it stamps every repointed assignment with method = merged_from:<loser_id> in identity_assignment_sources. That reuses a free-form column on a table that already existed rather than adding a merge log. source is left alone, so a reviewer's manual assignment keeps its veto in assign_identity after being repointed.

Roster readers filter merged_into IS NULL, including the name-dedup in create_character, which would otherwise fold new crops back into a character reconcile had retired. Lookup by id does not filter, because an assignment or a narration reference may still point at a merged id.

Two existing assertions asserted the old destructive behaviour (test_db.py:235, test_merge_refs.py:37) and were rewritten, not deleted: the invariant changed on purpose.

Checks: 116 passed on homesrv, up from 115. Additive ALTER TABLE through the existing init_db migration block, verified on the live database (merged_into present, 0 rows merged). Committed 00096cc.

Deliberately not built: the unmerge path and the split. No wrong merge has been observed since the crops were fixed, so the consumer of these records waits for one. The forward case is partly covered by 2b, since a resolver NONE now mints instead of folding a stranger into the nearest match.

2026-08-12, fifth session — the GPU cycle all four changes were waiting for

Asked: "go ahead" on the rerun.

First correction: the vision/identity/reconcile timestamps in /job/status are UTC and the git log is local (UTC+4), so the run that looked like a rerun was the pre-change baseline. _mark_has_face landed at 19:07 local, the run finished 13:17 local. The handoff was right that nothing had run.

Reset the registry for ef105a86 (8 characters, 77 assignments, 101 sources, 142 S3 objects), cleared vision and everything downstream (116 vision results), restarted the identity worker for its in-process known-character cache, then ran vision, identity and reconcile. 6 minutes wall: vision 3m48s, identity 1m25s, reconcile 48s. All three completed, 116/116/16.

What the four changes did

change	verdict
has_face stamp	works, present on all 110 detections, 67 true / 43 gated (39%)
extras gate	works, panel 7's two wrong bindings are gone
NONE mints	works, 16 characters minted where 8 existed
non-destructive merge	works, 7 rows carry merged_into, 9 assignments stamped merged_from:

Coverage went 70% -> 61% (77 -> 67 assignments over the same 110 detections). That is the gate's price and it is mostly correct, see below.

Panel 7, the worked example, before and after

person_1  Seonho           1.00   ->  -- none --   has_face=False
person_2  character_f7a4fd 0.00   ->  character_519d2b  0.00   has_face=True
person_4  character_d72710 0.94   ->  -- none --   WRONG binding removed
person_5  Seonho           1.00   ->  -- none --   WRONG binding removed

The two wrong bindings the gate existed to kill are dead. It also took person_1, and that is correct: ran face_detect.detect_faces on p006.png directly and it finds exactly one face on the whole panel, conf 0.599, inside person_2. Swept the threshold to 0.04 and nothing else appears above 0.056. Looked at the crop: person_1 is the lead drawn from behind at his desk, back of the head and headphones, no face in frame. The detector is right and the gate is right. The cost is that a back-turned character cannot be identified from that panel at all.

Also worth recording: person_1's new box frames the lead correctly. The old note that it framed an empty window mullion was written against the pre-fix boxes.

The new defect: a roster hint named the wrong man

The registry holds three real people and one wrong name.

• character_92129ac7 "Lim Seonho", 22 assignments. Verified against the art: the p010 introduction panel captioned LIM SEONHO (29), yellow plaid shirt and headphones, which is the roster's description for "Seonho". This is the lead and the name is right.
• character_556aef60, 25 assignments, unnamed. Verified: the woman with short black hair and pearls, the roster's second character, whom the roster itself calls "Unknown".
• character_dbadfff7 "Seonho", 15 assignments. Verified: a different man, glasses, dark clothing, in profile. He carries the lead's roster name.

p020 assigns Seonho to person_1 and Lim Seonho to person_3, so the pipeline holds them as two people in one panel. inference: the roster hint injected at service.py:882 puts a name in front of detection, and detection attached it to the wrong face before the caption panel could mint the real one. This is not the alias-merge case and merging the two rows would be wrong. It needs name binding to require evidence, the way name_claims already does for captions and address.

Two smaller things the run exposed

• Merge chains. character_e1ab7776 -> character_521c301f -> character_556aef60. merged_into points at a row that is itself merged, so a single-hop resolve lands on a retired character. Roster readers are fine because they filter merged_into IS NULL. Anything that follows one hop is not.
• Orphan name_claims. All 5 rows point at character_afa7623b, which the reset deleted. The reset clears characters and assignments but not claims.

Not run: dialogue and everything downstream. The job sits at dialogue waiting.

Same session — the three fixes the run's evidence asked for

All three are orchestrator-side, so no worker changed and check_stale.sh is not in play.

• Roster hints no longer seed detection. Deleted the two lines at service.py:882 that appended _roster_char_hints to known_characters. build_detect_prompt drops any hint without a name, so a nameless hint would have contributed nothing anyway. Names now reach detection only from registry rows, which are embedding-backed and were themselves named from an in-panel caption or address. The roster still feeds roster_cast in run_stage_dialogue, where names are matched against speech.
• merge_characters resolves the keeper to its chain root before merging, so merged_into stays one hop deep. Bounded 64-step walk, the cap only exists so a cycle cannot hang reconcile.
• reset_registry deletes name_claims for the manga's panels and reports the count.

Checks: 117 passed on homesrv, up from 116. The new chain test was confirmed to fail with the walk disabled, then the walk was restored and the suite re-run. Deployed by rebuilding the image; verified inside the running container by parsing the deployed source, not by grepping it, because the first check matched the word _roster_char_hints inside the comment that explains its removal.

Also copied audit_registry.py into the repo before the rebuild. It had only ever been docker cp'd, so every rebuild dropped it. Dockerfile has COPY . ., so it is baked now and the trap is gone.

Open risk on the next run: without the roster hint the lead is unnamed until the p010 caption, so panels 1 to 9 may mint him as an anonymous character that reconcile then has to merge. Watch whether "Lim Seonho" comes back as one row or two.

Same session — run B, 17:38-17:44

Reset (16 characters, 67 assignments, 67 sources, 5 name_claims, 156 S3 objects), cleared vision, restarted the identity worker, ran the three stages. The name_claims: 5 line is the orphan fix confirmed on live data.

117 detections, 59 assignments, 50% coverage, 20 characters, 72 with has_face (45 gated).

The registry split is fixed. "Lim Seonho" is one row with 25 assignments, "Seonho" fell from 15 to 1. So dropping the roster hint did not split the lead across the panels before his caption, which was the risk recorded before the run.

Two findings, both now filed:

• detection still names from in-panel text and can attach the name to the wrong body (p011, p026), which is decisions/identity-bbox.md#roster-does-not-name's "not covered" paragraph
• one degenerate bbox, caveats/audit-open.md#degenerate-bbox

And one fix of my own that was incomplete: the merge chain came back as 477c1894 -> a92d9df4 -> 4fb94c15 with the keeper walk deployed. The walk only sees the pair being merged now. Retiring a row that is already somebody's keeper needed the second half, a repoint of the loser's dependents. Both halves and both tests are in decisions/identity-bbox.md#merge-chains-flatten.

Checks: 118 passed, was 116. Each new merge test was run with its fix disabled and confirmed to fail first. Deployed by rebuild and verified by parsing the container's source.

Coverage is now 70 -> 61 -> 50 across three runs and is the open question, recorded as caveats/audit-open.md#coverage-trend. identity_labels already holds 145 rows of ground truth, so the next move is to score with eval_identity.py rather than to keep reading the coverage number.

2026-08-12, sixth session — the ground truth is for the wrong manga

No GPU work. Two things, both cheap.

_bbox_to_pixels orders its corners. Each coordinate pair is sorted after clamping. The self-check feeds it run B's real [226, 417, 130, 551] and asserts [117, 688, 203, 909]. Unsorted the call returns [203, 688, 117, 909], so the assert fails without the fix. worker_vision.py self-check passes. The vision worker is now STALE and needs a restart before the next cycle.

Item 1 of the plan cannot run as written. All 145 rows of identity_labels belong to chapter 8ca8249b, a different manga with cast "Rico" and "Ikekin", spread over 81 panels. Chapter 7c944dd4 has none, so /review/identity?job_id=778297bc... returns labeled: 0, correct: 0, accuracy: null.

Scoring 8ca8249b anyway gives 7/138, with 113 rows labelled as a real person and left unassigned. That chapter's identity run is stale: 44 assignments over 246 panels, predating every fix. The number measures old code on the wrong chapter.

So the eval path is proven end to end and the ground truth is absent. A precision number for the current registry needs a hand-labelling pass over 7c944dd4 through POST /review/identity/label, keyed by bbox rather than by local_id, because vision reassigns local_id every run.

2026-08-12 18:07-18:13 UTC, third GPU cycle

Restarted vision (window 3) and identity (/characters/reset returned restart_identity_worker: true), both by send-keys C-c then re-sending the launch line, never by pgrep. check_stale.sh exit 0 before the run. Reset dropped 20 characters, 59 assignments, 69 sources, 168 S3 objects.

vision 116/116 in 3m59s, identity 116/116 in 1m24s, reconcile 18/18 in 50s.

metric	17:38 run	18:07 run
detections	117	119
assignments	59	68
coverage	50%	57%
degenerate boxes	1	0
has_face true / gated	72 / 45	71 / 48
assigned among face-bearing	59/72 = 82%	68/71 = 96%
assigned among gated	--	0
registry rows / merged	20 / 7	18 / 9
merged_from stamps	9	22
chains deeper than one hop	1	0

The corner-ordering fix works: 0 degenerate boxes. The merge-chain fix holds under a heavier merge load, 9 merges and no chain.

Coverage is now the gate and nothing else. Every assignment landed on a face-bearing detection and none on a gated one. Recall among face-bearing detections is 96%. So the 43% with no assignment is the 40% the gate drops plus 3 detections, and the resolver is not losing cast. That closes the part of #coverage-trend that suspected the resolver.

The open question moved to precision. The lead holds 36 of 68 assignments, 53%, against 25 of 59 before, and audit_registry.py flags it as absorbing. The merge count rose from 7 to 9 over the same interval. Whether 36 is a protagonist in half the panels or an over-merge cannot be told apart without labels, which is item 1.

Panel 7 got worse, not better: 5 of its 6 detections carry has_face = False, and person_6, the one that does, went unassigned. The previous run bound its colleague. That is the cost of requiring a face, item 4.

2026-08-12, sixth session, later — the lead was over-merged, and cosine cannot fix it

The user checked the lead's crops in the review UI. LIM SEONHO's 36 assignments cover at least six different men, a chibi, and a cat. So 36 of 68 is a bug, not a protagonist.

Split by mechanism: 22 native resolves, 14 from reconcile merges. Both are broken, for different reasons.

The tracklet linker chained across the chapter. window=8 bounds each pair, transitivity was unbounded. The 22 native assignments came from 3 tracklets spanning 0, 22 and 30 panels, visible as two confidence blocks of eleven rows at 0.95 and ten at 1.0. Fixed by capping the merged group's span (decisions/identity-bbox.md#tracklet-span-cap).

Both tokenizers linked on words that are not identity. Whole chains hung on short; one pair linked on the word hair itself. There is now one tokenizer with a GENERIC stopword set, shared with reconcile's pre-filter (decisions/identity-bbox.md#generic-tokens).

Measured on the same 22 real crops, candidate overlap forced to pass: 3 tracklets at worst span 30 becomes 9 at worst span 8.

Then the obvious next fix was ruled out by measurement. Pulled all 22 crop embeddings from MinIO and computed the pairwise cosine. The cat scores up to 0.82 against men, two different men score 0.93, and the highest pair in the matrix is 0.96. No threshold exists, so crop-to-crop cosine is not a link signal, and the candidates overlap condition is close to noise. Filed as caveats/audit-open.md#cosine-not-identity. Inference: identity embeds the whole person box, so cosine measures scene and style, not face.

Also seen: vision boxes cats as people and dresses them. p081 and p108 are cats, described short brown / yellow plaid shirt and short brown / white t-shirt.

Checks: tracklets.py self-check ok, orchestrator 118 passed. Both new asserts confirmed to fail with their fix disabled. Nothing deployed, nothing re-run on a GPU.

Artefact: lead_tracklets.png, the 22 panels with boxes, insets and tracklet grouping. Session scratchpad only, not committed.

2026-08-12, 19:44-19:52 UTC — fourth GPU cycle: the cast is the gallery

Three fixes ran together for the first time: the tracklet span cap and the shared GENERIC tokenizer, both written last session and never deployed, plus the new one (decisions/identity-bbox.md#cast-is-the-gallery). Job 778297bc, chapter 7c944dd4, registry reset, vision cleared, vision -> identity -> reconcile. Vision 116/116 in 3m55s, identity 116/116 in 2m44s, reconcile 20/20 in 44s.

metric	18:07 run	19:44 run
detections	119	119
assignments	68	60
coverage	57%	50%
tracklets over crops	12 / 64	33 / 72
lead's assignments	36	16
top character's share	--	16/60 = 27%
characters after reconcile	18	14
minted / cleared	--	10 / 12

Coverage went down and that is the fix working. gemma cleared 12 crops it used to be forced to name from a cosine top-k that did not contain the right person. 72 crops entered resolution against 64, because a crop with an empty cosine shortlist is no longer dropped.

Checked by eye, which is the only check that sees this. Contact sheets of every assigned crop, per character, confirmed by the user. The lead holds 16 crops. 14 are him and 2 are art inside a panel, the photograph at order 17 and the chibi at order 20. character_2b1b12a1 holds 13, all of them her, and she is a main character the registry never named. character_f0d4e901 holds 9, of which 7 are her and 2 are 2b1b12a1 (order 31, order 33). Against the 18:07 run, where the lead's 36 covered six different men, a chibi and a cat.

Every wrong crop on the lead is one defect: vision treats art inside a panel as the scene. It is not a linker failure and no identity change will fix it.

The cap fired twice and dropped the wrong rows. GALLERY_CAP = 10 truncated a 16-row gender-compatible cast at p097 and an 11-row one at p109. cast_gallery orders named first, so what it drops is exactly the recently minted anonymous rows, which is the population a later tracklet most needs to match against. Filed as caveats/audit-open.md#gallery-cap-drops-the-unnamed.

Checks: worker_vision.py self-check ok, tracklets.py self-check ok, orchestrator 118 passed, ./check_stale.sh exit 0 before the cycle. Vision and identity workers both restarted, the second because /characters/reset asked for it.

Artefacts: sheet_*.png, one contact sheet per character. Session scratchpad only, not committed.

2026-08-13 — the dialogue stage names nobody, and why

Ran dialogue 116/116 in 5m57s on the fourth cycle's registry, to see whether the fixed identity lets the existing name_claims path name the female lead. It does not, and the six claims it produced name three separate defects.

p040  character_2b1b12a1  "Choi Haeseon"  caption  1.00   -> NOT promoted
p010  character_b1dd5659  "Lim Seonho"    caption  1.00   -> conflict flag
p047  character_b1dd5659  "Seonho"        address  0.90   -> conflict flag
p011  character_f0d4e901  "Seonho"        address  1.00   -> PROMOTED
p026  character_f0d4e901  "Seonho"        address  1.00   -> PROMOTED
p110  character_028d4a49  "Haeseon"       address  1.00   -> already named

All three are fixed in db.add_name_claim and recorded in decisions/identity-naming.md: alias grouping, a confident caption as strong evidence, and one name per character. test_name_binding.py replays these six claims, 121 tests pass, and each new assert was confirmed to fail with its fix disabled.

Also wired merge_faceless_captions into both crop endpoints. It had been written and never called; both endpoints called the non-destructive context_fragment_links instead, and no decision recorded that choice. It does not cover the head-in-one-shot, body-in-the-next split that prompted the question, because a body fragment has no text and _merge_plan only folds a fragment that has text and no face.

Found while wiring it: crop_webtoon skips an upload when the key exists, which is right for a resume and silently wrong after a slicing change. Documented at the line and in NEXT.md.

Wrote ARCHITECTURE.md from the user's design: region graph, occurrence/identity/name, speaker as a scored graph edge with a typed union, narrative plane for art-in-art, and a persistent story state machine. Every section carries what exists against it today. Nothing in it is built.

Nothing ran on a GPU after the dialogue stage.

2026-08-13 — the measurement spine, built and checked against the run it describes

ARCHITECTURE.md step 0. No GPU, no stage run. The 19:44 run of 2026-08-12 was still in /data/manga.db, which is what made this possible before the fifth cycle destroys it.

eval/chapter-truth.json holds 38 labelled occurrences over the three characters the user walked crop by crop. audit_registry.py now matches them to the run's assignments and prints purity per cluster and fragmentation per person:

truth: 38 labelled occurrences, 38 matched an assignment at IoU >= 0.5, 0 unmatched
  LIM SEONHO [b1dd5659]  lead      14/16 = 0.88 = baseline   (wrong: photo_of_lead 1, chibi_of_lead 1)
  character_2b1b12a1     woman_a   13/13 = 1.00 = baseline
  Seonho [f0d4e901]      woman_b     7/9 = 0.78 = baseline   (wrong: woman_a 2)
  fragmentation  lead 1, woman_a 2, woman_b 1               all = baseline

NEXT.md recorded that 2 of woman B's 9 crops were really woman A, and never said which. They are panel_order 31 and 33, identified by pulling p030 and p032 from s3://panels and looking. Woman A wears a cream top with black trim and a pearl necklace, and both crops are unmistakably her at zoom. That closes the 7-and-2 arithmetic and is why her fragmentation is 2.

The design is in decisions/measurement-spine.md. Rows key on page-space geometry rather than panel_id, purity is a share and fragmentation a count of ids rather than anything naming a character_id. So the file survives both the re-crop and /characters/reset that the fifth cycle runs. audit_registry.py --selftest covers the IoU match, the greedy tie-break and the purity maths without a database.

Four things the audit itself was getting wrong, all pre-existing:

• it counted 20 characters where 14 are live and 6 are merge losers kept on purpose
• it keyed the assignment spread on name, so the two characters both named Seonho summed to one line
• its default worked example was panel_index 7, a balloon-only panel vision skips. NEXT.md's "panel 7" is panel_order 7, one lower, the office shot with 6 detections
• it said nothing about skipped panels. 41 of 116 are skip=True, so 119 detections come from 75 panels. Four skips were checked by eye and all four are correct

The skip count carries one new fact worth more than the audit fix. Those 41 panels hold 28 of the chapter's 122 dialogue lines, and a skipped panel has no character at all. 23% of the dialogue has no visible speaker to attribute to under any linker. That is the case for offscreen as a fourth speaker_ref kind, now measured rather than assumed.

Step 0's dialogue half is not written. It needs 30 lines watched panel by panel, and NEXT.md holds no per-line speaker truth to transcribe.