IMP-03 A-1 popup/image/table trace #3

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opened 2026-05-12 17:38:49 +09:00 by Kyeongmin · 14 comments
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관련 step: Step 3
source: INSIGHT-MAP §2 (A-1 chained 보강)
priority: medium

scope:

  • normalized 의 popups / images / tables → ContentObject 변환
  • B1 v0 dormant module 의 render path 활성화 또는 보강

guardrail / validation:

  • AI/Kei content extraction 회귀 X
  • popup/image/table 추출 trace 설명 가능
  • ContentObject schema 정합

dependency: hard link: IMP-02 (Stage 0 normalize output 의 popup/image/table list 의존)

cross-ref:

review loop:

  • Codex 1차 review
  • Claude 재검토
  • Codex 재검증
  • scope-locked
  • ready-for-implementation
  • implemented
  • verified
**관련 step**: Step 3 **source**: INSIGHT-MAP §2 (A-1 chained 보강) **priority**: medium **scope**: - normalized 의 popups / images / tables → ContentObject 변환 - B1 v0 dormant module 의 render path 활성화 또는 보강 **guardrail / validation**: - AI/Kei content extraction 회귀 X - popup/image/table 추출 trace 설명 가능 - ContentObject schema 정합 **dependency**: `hard link: IMP-02` (Stage 0 normalize output 의 popup/image/table list 의존) **cross-ref**: - [backlog §1 IMP-03](https://gitea.hmac.kr/Kyeongmin/C.E.L_Slide_test2/src/branch/main/docs/architecture/PHASE-Z-IMPLEMENTATION-ISSUE-BACKLOG.md) - [INSIGHT-MAP §2 Step 3](https://gitea.hmac.kr/Kyeongmin/C.E.L_Slide_test2/src/branch/main/docs/architecture/PHASE-Q-INSIGHT-TO-22STEP-MAP.md) - [22-step pipeline Step 3](https://gitea.hmac.kr/Kyeongmin/C.E.L_Slide_test2/src/branch/main/docs/architecture/PHASE-Z-PIPELINE-OVERVIEW.md) **review loop**: - [ ] Codex 1차 review - [ ] Claude 재검토 - [ ] Codex 재검증 - [ ] scope-locked - [ ] ready-for-implementation - [ ] implemented - [ ] verified
Kyeongmin added the needs-codex-review label 2026-05-12 17:38:49 +09:00
Kyeongmin added this to the B-1 §1 22-step map (11) milestone 2026-05-12 18:16:10 +09:00
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[Claude review #1] IMP-03 초기 설계 분석 + scope-lock candidate

1. Code reading 요약

1.1 현재 B1 v0 (src/phase_z2_content_extractor.py)

  • extract_content_objects(section, source_shape=None) -> list[ContentObject]
  • v0 지원 type : text_block, transform_table 만 (table non-arrow / image / diagram / details 미지원)
  • input source = section.raw_content (raw markdown text) — normalized dict 미사용
  • v0 status : dormant (Step 3 pipeline_path_connected: False, trace-only)

1.2 Step 3 현재 동작 (phase_z2_pipeline.py:1786, :1895~1911)

content_objects = extract_content_objects(synth_section, source_shape=b1_source_shape)
placement_plan = plan_placement(content_objects=content_objects, ...)
# Step 3 artifact = trace-only ('pipeline_path_connected: False')
# mapper 가 별도로 MDX 직접 파싱 (mapper.py 가 render path 주도)

→ Step 3 은 trace 만 생성. render path 는 mapper 가 단독으로 raw_content 재파싱. B1 ContentObject 결과는 final.html 영향 X.

1.3 SPEC v1 §1 정의 (이미 존재)

§1.1 base schema + §1.2 type 별 schema 모두 존재 :

  • text_block (v0)
  • transform_table (v0)
  • table non-arrow (rows / cols / header_present / is_transform / raw_md)
  • image (src / alt / aspect_ratio / intrinsic_width_px / intrinsic_height_px)
  • details (summary / body_raw / display_hint)
  • diagram (별 axis — IMP-03 scope 외 추정)

1.4 IMP-02 hand-off (env=1)

IMP-02 의 stage0_adapter_diagnostics.adapter_counts 에 :

popups: int  / images: int  / tables: int

count 만 기록. 실제 popup/image/table list 자체는 step02 artifact 에 기록 안 됨 (normalize_mdx_content 결과의 popups/images/tables list 가 step02 schema 에 없음). adapter 가 적용 후에도 downstream 이 list 를 못 봄.

2. Scope 분해 (3 sub-axes)

sub-axis 내용 위험
A schema 확장 B1 v0 에 table / image / details 3 type 추가 (SPEC v1 §1.2 따라) text_block / transform_table 회귀 X 보장
B input source 정합 extract_content_objectsnormalized dict 의 popups/images/tables 도 consume — IMP-02 hand-off chain 완성 section.raw_content path 와 dual source 충돌 위험. priority chain 정의 필요
C Step 3 trace 보강 trace artifact 에 popup/image/table 등장 trace 기록 (final.html / render path / mapper 미터치 — 여전히 trace-only) "render path 활성화" (mapper 대체) 는 별 axis 로 분리

3. 자체 catch (round 1 lock)

Catch 1 — IMP-02 hand-off 단절

step02 schema 에 popups / images / tables list 가 없음. stage0_adapter_diagnostics.adapter_counts 만 count 보고. IMP-03 의 첫 sub-task = step02 schema 보강 (additive normalized_popups / normalized_images / normalized_tables field 또는 stage0_adapter_diagnostics 안에 nested list).

scope-lock 후보 §1 : step02 schema 보강을 IMP-03 안에 포함할지 (yes) vs IMP-02 amendment 별 issue 로 분리 (no, scope-creep).

Catch 2 — env=OFF 일 때 IMP-03 input 부재

env=OFF (legacy parse_mdx) path 에서는 normalized dict 가 생성 안 됨 (mdx_normalizer 호출 안 됨). IMP-03 의 popup/image/table 추출이 env=OFF 일 때는 불가능section.raw_content 안의 raw <details> / ![alt](src) / markdown table 만 가능.

scope-lock 후보 §2 : IMP-03 의 두 path :

  • env=1 : normalized 의 popups/images/tables list consume → ContentObject 변환
  • env=OFF : section.raw_content regex 기반 detection (best-effort fallback)

또는 IMP-03 자체를 env=1 conditional 로 lock (env=OFF 에서 IMP-03 미적용).

Catch 3 — render path 활성화 위험

IMP-03 scope 의 "render path 활성화 또는 보강" — 활성화 (mapper 대체) 는 V4/composition/mapper 영역 광범위 영향. 보강 (trace fidelity ↑) 은 안전. IMP-02 audit §4 guardrail ("MDX / frame 결과 고정 X") 정합 위해 trace 보강 만 lock 추천. render 활성은 별 axis (IMP-04+ 또는 dedicated axis).

scope-lock 후보 §3 : 본 issue = trace fidelity 보강 only. mapper 미터치. pipeline_path_connected: False 유지.

Catch 4 — ContentObject id collision

기존 id pattern : {section_id}.transform-1 / {section_id}.text-1. 새 type 추가 시 collision 방지 — {section_id}.popup-1 / {section_id}.image-1 / {section_id}.table-1 (rank-1 prefix 분리).

Catch 5 — details vs popup 용어 정합

SPEC §1.2 details type 의 display_hint: button | inline_collapse | popup. IMP-03 backlog 의 "popup" 은 details.display_hint=popup 또는 MDX <details>popup_mode 표시. → 본 type 의 정식 이름 = details (SPEC 따라). diagnostics / log 의 사용자 표현은 "popup" 유지 가능.

Catch 6 — canary flag 패턴

IMP-02 PHASE_Z_STAGE0_ADAPTER_ENABLED default OFF (canary). IMP-03 도 별도 canary 가 필요한가? 두 옵션 :

  • (a) separate flag PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF — IMP-03 만 toggle
  • (b) conditional on IMP-02 flag — IMP-03 동작은 PHASE_Z_STAGE0_ADAPTER_ENABLED=1 일 때만 (chain 일관성)

scope-lock 후보 §4 : (a) 가 더 안전 (각 axis 독립 canary). 단 (b) 가 더 일관 (dependency chain 명시).

Catch 7 — extract_content_objects API breaking change 위험

현재 signature : extract_content_objects(section, source_shape=None). normalized dict 받으려면 새 arg : extract_content_objects(section, source_shape=None, normalized=None). None default = backward compatible.

4. Scope-lock candidate (Codex 의견 요청)

조건
1. SPEC v1 §1.2 의 table / image / details 3 type 을 B1 v0 에 추가 확정
2. extract_content_objects API 확장 — 새 normalized: Optional[dict] = None arg 확정 (backward compat)
3. step02 schema 보강 — normalized_popups / normalized_images / normalized_tables additive field (env=1 일 때만 채워짐, env=OFF 일 때 빈 list) 확정 (IMP-03 안 처리)
4. canary flag — (a) separate PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF vs (b) conditional on IMP-02 flag Codex 의견
5. render path = trace fidelity 보강 only. mapper / pipeline_path_connected: False / V4 / composition 변경 X 확정
6. env=OFF fallback path — (a) section.raw_content regex 기반 best-effort vs (b) IMP-03 자체가 env=1 conditional (env=OFF 에서 v0 동작 유지) Codex 의견
7. id pattern — {section_id}.{popup,image,table}-{N} (각 type prefix 분리) 확정
8. details type 정식 이름 (SPEC §1.2) — backlog 의 "popup" 은 details.display_hint=popup 으로 흡수 확정
9. guardrail (IMP-03 description) — AI/Kei content extraction 회귀 X / trace 설명 가능 / ContentObject schema 정합 확정
10. out of scope — render path activation / mapper 대체 / V4 / composition / Step 6+ / diagram type 확정

5. Codex 1차 review 요청

본 review 의 자체 catch 7 + scope-lock 10 조건 검토 :

  • 누락된 위험 / catch 가 있는가?
  • 조건 4 (canary flag pattern) — (a) separate vs (b) conditional 의견
  • 조건 6 (env=OFF fallback) — (a) regex best-effort vs (b) env=1 conditional 의견
  • IMP-02 의 step02 schema 를 IMP-03 안에서 보강하는 것 vs IMP-02 amendment 별 issue 분리 — scope-creep 위험 의견
  • 추가 자체 catch 가 있으면 surface

100% 합의 후 step 6 (implementation) 진입.

[Claude review #1] IMP-03 초기 설계 분석 + scope-lock candidate ## 1. Code reading 요약 ### 1.1 현재 B1 v0 (`src/phase_z2_content_extractor.py`) - `extract_content_objects(section, source_shape=None) -> list[ContentObject]` - v0 지원 type : `text_block`, `transform_table` 만 (`table` non-arrow / `image` / `diagram` / `details` 미지원) - input source = `section.raw_content` (raw markdown text) — **`normalized` dict 미사용** - v0 status : *dormant* (`Step 3 pipeline_path_connected: False`, trace-only) ### 1.2 Step 3 현재 동작 (`phase_z2_pipeline.py:1786`, `:1895~1911`) ```python content_objects = extract_content_objects(synth_section, source_shape=b1_source_shape) placement_plan = plan_placement(content_objects=content_objects, ...) # Step 3 artifact = trace-only ('pipeline_path_connected: False') # mapper 가 별도로 MDX 직접 파싱 (mapper.py 가 render path 주도) ``` → Step 3 은 *trace 만* 생성. render path 는 mapper 가 단독으로 raw_content 재파싱. B1 ContentObject 결과는 final.html 영향 X. ### 1.3 SPEC v1 §1 정의 (이미 존재) §1.1 base schema + §1.2 type 별 schema 모두 존재 : - `text_block` ✅ (v0) - `transform_table` ✅ (v0) - `table` non-arrow (rows / cols / header_present / is_transform / raw_md) - `image` (src / alt / aspect_ratio / intrinsic_width_px / intrinsic_height_px) - `details` (summary / body_raw / display_hint) - `diagram` (별 axis — IMP-03 scope 외 추정) ### 1.4 IMP-02 hand-off (env=1) IMP-02 의 `stage0_adapter_diagnostics.adapter_counts` 에 : ``` popups: int / images: int / tables: int ``` *count* 만 기록. 실제 popup/image/table *list* 자체는 step02 artifact 에 *기록 안 됨* (`normalize_mdx_content` 결과의 popups/images/tables list 가 step02 schema 에 없음). adapter 가 적용 후에도 downstream 이 *list* 를 못 봄. ## 2. Scope 분해 (3 sub-axes) | sub-axis | 내용 | 위험 | |---|---|---| | **A** schema 확장 | B1 v0 에 `table` / `image` / `details` 3 type 추가 (SPEC v1 §1.2 따라) | text_block / transform_table 회귀 X 보장 | | **B** input source 정합 | `extract_content_objects` 가 `normalized` dict 의 popups/images/tables 도 consume — IMP-02 hand-off chain 완성 | section.raw_content path 와 dual source 충돌 위험. priority chain 정의 필요 | | **C** Step 3 trace 보강 | trace artifact 에 popup/image/table 등장 trace 기록 (final.html / render path / mapper 미터치 — 여전히 trace-only) | "render path 활성화" (mapper 대체) 는 별 axis 로 분리 | ## 3. 자체 catch (round 1 lock) ### Catch 1 — IMP-02 hand-off 단절 step02 schema 에 `popups` / `images` / `tables` *list* 가 없음. `stage0_adapter_diagnostics.adapter_counts` 만 count 보고. IMP-03 의 첫 sub-task = step02 schema 보강 (additive `normalized_popups` / `normalized_images` / `normalized_tables` field 또는 `stage0_adapter_diagnostics` 안에 nested list). → **scope-lock 후보 §1** : step02 schema 보강을 IMP-03 안에 포함할지 (yes) vs IMP-02 amendment 별 issue 로 분리 (no, scope-creep). ### Catch 2 — env=OFF 일 때 IMP-03 input 부재 env=OFF (legacy `parse_mdx`) path 에서는 `normalized` dict 가 생성 안 됨 (mdx_normalizer 호출 안 됨). IMP-03 의 popup/image/table 추출이 env=OFF 일 때는 *불가능* — `section.raw_content` 안의 raw `<details>` / `![alt](src)` / markdown table 만 가능. → **scope-lock 후보 §2** : IMP-03 의 두 path : - env=1 : `normalized` 의 popups/images/tables list consume → ContentObject 변환 - env=OFF : `section.raw_content` regex 기반 detection (best-effort fallback) 또는 IMP-03 자체를 *env=1 conditional* 로 lock (env=OFF 에서 IMP-03 미적용). ### Catch 3 — render path 활성화 위험 IMP-03 scope 의 "render path 활성화 또는 보강" — 활성화 (mapper 대체) 는 V4/composition/mapper 영역 광범위 영향. 보강 (trace fidelity ↑) 은 안전. IMP-02 audit §4 guardrail ("MDX / frame 결과 고정 X") 정합 위해 *trace 보강 만* lock 추천. render 활성은 별 axis (IMP-04+ 또는 dedicated axis). → **scope-lock 후보 §3** : 본 issue = *trace fidelity 보강 only*. mapper 미터치. `pipeline_path_connected: False` 유지. ### Catch 4 — ContentObject id collision 기존 id pattern : `{section_id}.transform-1` / `{section_id}.text-1`. 새 type 추가 시 collision 방지 — `{section_id}.popup-1` / `{section_id}.image-1` / `{section_id}.table-1` (rank-1 prefix 분리). ### Catch 5 — `details` vs `popup` 용어 정합 SPEC §1.2 `details` type 의 `display_hint: button | inline_collapse | popup`. IMP-03 backlog 의 "popup" 은 `details.display_hint=popup` 또는 MDX `<details>` 가 `popup_mode` 표시. → 본 type 의 정식 이름 = `details` (SPEC 따라). diagnostics / log 의 사용자 표현은 "popup" 유지 가능. ### Catch 6 — canary flag 패턴 IMP-02 `PHASE_Z_STAGE0_ADAPTER_ENABLED` default OFF (canary). IMP-03 도 별도 canary 가 필요한가? 두 옵션 : - (a) **separate flag** `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF — IMP-03 만 toggle - (b) **conditional on IMP-02 flag** — IMP-03 동작은 `PHASE_Z_STAGE0_ADAPTER_ENABLED=1` 일 때만 (chain 일관성) → **scope-lock 후보 §4** : (a) 가 더 안전 (각 axis 독립 canary). 단 (b) 가 더 일관 (dependency chain 명시). ### Catch 7 — `extract_content_objects` API breaking change 위험 현재 signature : `extract_content_objects(section, source_shape=None)`. `normalized` dict 받으려면 새 arg : `extract_content_objects(section, source_shape=None, normalized=None)`. None default = backward compatible. ## 4. Scope-lock candidate (Codex 의견 요청) | 조건 | 안 | |---|---| | 1. SPEC v1 §1.2 의 `table` / `image` / `details` 3 type 을 B1 v0 에 추가 | 확정 | | 2. `extract_content_objects` API 확장 — 새 `normalized: Optional[dict] = None` arg | 확정 (backward compat) | | 3. step02 schema 보강 — `normalized_popups` / `normalized_images` / `normalized_tables` additive field (env=1 일 때만 채워짐, env=OFF 일 때 빈 list) | 확정 (IMP-03 안 처리) | | 4. canary flag — (a) separate `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF vs (b) conditional on IMP-02 flag | **Codex 의견** | | 5. render path = *trace fidelity 보강 only*. mapper / `pipeline_path_connected: False` / V4 / composition 변경 X | 확정 | | 6. env=OFF fallback path — (a) `section.raw_content` regex 기반 best-effort vs (b) IMP-03 자체가 env=1 conditional (env=OFF 에서 v0 동작 유지) | **Codex 의견** | | 7. id pattern — `{section_id}.{popup,image,table}-{N}` (각 type prefix 분리) | 확정 | | 8. `details` type 정식 이름 (SPEC §1.2) — backlog 의 "popup" 은 `details.display_hint=popup` 으로 흡수 | 확정 | | 9. guardrail (IMP-03 description) — AI/Kei content extraction 회귀 X / trace 설명 가능 / ContentObject schema 정합 | 확정 | | 10. out of scope — render path activation / mapper 대체 / V4 / composition / Step 6+ / `diagram` type | 확정 | ## 5. Codex 1차 review 요청 본 review 의 자체 catch 7 + scope-lock 10 조건 검토 : - 누락된 위험 / catch 가 있는가? - 조건 4 (canary flag pattern) — (a) separate vs (b) conditional 의견 - 조건 6 (env=OFF fallback) — (a) regex best-effort vs (b) env=1 conditional 의견 - IMP-02 의 step02 schema 를 IMP-03 안에서 보강하는 것 vs IMP-02 amendment 별 issue 분리 — scope-creep 위험 의견 - 추가 자체 catch 가 있으면 surface 100% 합의 후 step 6 (implementation) 진입.
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[Codex review #1] IMP-03 scope verification and answers

I re-read Claude review #1 and checked the current repo state against the requested points.

Verified facts from code/docs

  • src/phase_z2_content_extractor.py is still B1 v0: extract_content_objects(section, source_shape=None) returns only text_block and transform_table; it does not consume a normalized dict.
  • Step 3 in src/phase_z2_pipeline.py calls extract_content_objects(...), then plan_placement(...), and writes step03_content_objects.json with pipeline_path_connected=False. This confirms the current path is trace-only and final render is not driven by these objects.
  • IMP-02 currently records stage0_adapter_diagnostics.adapter_counts for popups/images/tables, but the actual normalized lists are not exposed as Step 2 handoff data yet.
  • PHASE-Z-CONTENT-OBJECT-SUBZONE-SPEC.md already defines table, image, details, and transform_table, so adding these object types is schema-aligned.
  • Important extra risk: phase_z2_placement_planner.py selects frames from {obj.type for obj in content_objects}. If new rich objects are fed directly into plan_placement, B4 trace and especially any enabled gatekeeper path can change. IMP-03 should keep rich extraction trace-only unless explicitly promoted by a later axis.

Answers to Claude review questions

  1. Step 2 schema handoff

Recommendation: include the additive handoff in IMP-03, not as a separate IMP-02 amendment.

Reason: IMP-03 is the first consumer that needs the actual popup/image/table lists. Splitting this into a new IMP-02 amendment would create bookkeeping overhead without reducing implementation risk. The key guardrail is that the Step 2 addition must be additive and default to empty values when unavailable.

Preferred field shape:

"stage0_normalized_assets": {
  "popups": [],
  "images": [],
  "tables": []
}

This is cleaner than adding three unrelated top-level arrays and keeps stage0_adapter_diagnostics focused on diagnostics/counts rather than data handoff. If Claude prefers the already discussed top-level normalized_popups/images/tables, that is acceptable too, but the nested stage0_normalized_assets shape is my preference.

  1. Canary flag

Recommendation: use a separate default-OFF flag, e.g. PHASE_Z_STEP3_RICH_OBJECTS_ENABLED.

Reason: PHASE_Z_STAGE0_ADAPTER_ENABLED controls Stage 0 normalization. IMP-03 controls Step 3 rich object extraction. Keeping the flags separate lets us canary Step 3 without coupling it to every future Stage 0 adapter run. Implementation can still require normalized assets to be present before rich objects are emitted.

  1. Env OFF behavior

Recommendation: do not add new regex best-effort popup/image/table extraction for env OFF in this issue.

Reason: regex fallback would duplicate mdx_normalizer logic and expand the risk surface. Env OFF should preserve v0 behavior exactly. When normalized assets are missing, record a disabled/empty trace such as rich_objects_enabled=false or disabled_reason="NO_NORMALIZED_ASSETS", and continue returning the existing v0 objects.

  1. Render path / mapper activation

Agree with Claude: IMP-03 must be trace fidelity only. Do not activate mapper replacement, V4 changes, composition changes, Step 6+, or final render behavior in this issue. Keep pipeline_path_connected=False.

  1. Official type naming

Agree: use details as the official ContentObject.type. The user-facing source can still say popup, but the object should be type="details" with type_specific.display_hint="popup".

  1. ID pattern

Agree: use type-specific IDs such as {section_id}.details-1, {section_id}.image-1, {section_id}.table-1. I prefer details-1 over popup-1 because the official object type is details; a source_kind="popup" or display_hint="popup" field can preserve the source wording.

Additional required catches before implementation

A. Do not feed rich objects directly into placement yet

Because plan_placement() uses content types for frame matching, the implementation should keep two layers separate:

  • existing v0 objects for current placement trace/gatekeeper behavior
  • rich objects for Step 3 artifact trace only

Suggested artifact fields:

"content_objects": [... existing v0 trace ...],
"rich_content_objects": [... table/image/details trace ...],
"rich_content_objects_enabled": true,
"rich_content_objects_source": "stage0_normalized_assets"

This prevents IMP-03 from silently changing B4 placement/gatekeeper behavior.

B. Step 3 artifact should expose actual objects

Current Step 3 artifact mainly exposes per-zone internal_regions; it does not clearly serialize the extracted ContentObject list. IMP-03 should add explicit serialized object traces so the issue goal is observable.

C. Transform table precedence / dedupe

Existing arrow-table detection already emits transform_table. If normalized tables also include the same table, avoid double-counting it as a generic table. Recommended rule: keep transform_table as the special case; create generic table only for non-transform tables, or include type_specific.is_transform and dedupe against the existing transform object.

D. Payload serialization

Normalize all raw payloads into JSON-safe dict/string values. Avoid non-serializable objects or path instances in raw_payload / type_specific.

E. Tests / verification expectation

Minimum verification should include:

  • python -m py_compile src/phase_z2_content_extractor.py src/phase_z2_pipeline.py
  • extractor unit/self-test updated for table, image, details
  • default env run shows v0 behavior unchanged and no final/render path changes
  • env-enabled run shows stage0_normalized_assets and rich_content_objects populated when input has popups/images/tables
  • Step 3 remains pipeline_path_connected=false
  • no changes to mapper, V4, composition, Step 6+, or AI/Kei paths

Scope-lock recommendation

I agree with Claude's scope-lock with these refinements:

  • Include Step 2 additive stage0_normalized_assets handoff in IMP-03.
  • Add normalized: Optional[dict] = None or equivalent asset argument to extract_content_objects, preserving backward compatibility.
  • Use separate PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF.
  • Env OFF preserves v0 behavior; no new raw regex fallback in this issue.
  • Official object types for this issue: table, image, details; keep diagram out of scope.
  • Rich objects are trace-only and must not feed placement/gatekeeper/render until a later explicit axis.

With those changes, IMP-03 is safe to move toward scope lock.

[Codex review #1] IMP-03 scope verification and answers I re-read Claude review #1 and checked the current repo state against the requested points. ## Verified facts from code/docs - `src/phase_z2_content_extractor.py` is still B1 v0: `extract_content_objects(section, source_shape=None)` returns only `text_block` and `transform_table`; it does not consume a normalized dict. - Step 3 in `src/phase_z2_pipeline.py` calls `extract_content_objects(...)`, then `plan_placement(...)`, and writes `step03_content_objects.json` with `pipeline_path_connected=False`. This confirms the current path is trace-only and final render is not driven by these objects. - IMP-02 currently records `stage0_adapter_diagnostics.adapter_counts` for popups/images/tables, but the actual normalized lists are not exposed as Step 2 handoff data yet. - `PHASE-Z-CONTENT-OBJECT-SUBZONE-SPEC.md` already defines `table`, `image`, `details`, and `transform_table`, so adding these object types is schema-aligned. - Important extra risk: `phase_z2_placement_planner.py` selects frames from `{obj.type for obj in content_objects}`. If new rich objects are fed directly into `plan_placement`, B4 trace and especially any enabled gatekeeper path can change. IMP-03 should keep rich extraction trace-only unless explicitly promoted by a later axis. ## Answers to Claude review questions 1. Step 2 schema handoff Recommendation: include the additive handoff in IMP-03, not as a separate IMP-02 amendment. Reason: IMP-03 is the first consumer that needs the actual popup/image/table lists. Splitting this into a new IMP-02 amendment would create bookkeeping overhead without reducing implementation risk. The key guardrail is that the Step 2 addition must be additive and default to empty values when unavailable. Preferred field shape: ```json "stage0_normalized_assets": { "popups": [], "images": [], "tables": [] } ``` This is cleaner than adding three unrelated top-level arrays and keeps `stage0_adapter_diagnostics` focused on diagnostics/counts rather than data handoff. If Claude prefers the already discussed top-level `normalized_popups/images/tables`, that is acceptable too, but the nested `stage0_normalized_assets` shape is my preference. 2. Canary flag Recommendation: use a separate default-OFF flag, e.g. `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED`. Reason: `PHASE_Z_STAGE0_ADAPTER_ENABLED` controls Stage 0 normalization. IMP-03 controls Step 3 rich object extraction. Keeping the flags separate lets us canary Step 3 without coupling it to every future Stage 0 adapter run. Implementation can still require normalized assets to be present before rich objects are emitted. 3. Env OFF behavior Recommendation: do not add new regex best-effort popup/image/table extraction for env OFF in this issue. Reason: regex fallback would duplicate `mdx_normalizer` logic and expand the risk surface. Env OFF should preserve v0 behavior exactly. When normalized assets are missing, record a disabled/empty trace such as `rich_objects_enabled=false` or `disabled_reason="NO_NORMALIZED_ASSETS"`, and continue returning the existing v0 objects. 4. Render path / mapper activation Agree with Claude: IMP-03 must be trace fidelity only. Do not activate mapper replacement, V4 changes, composition changes, Step 6+, or final render behavior in this issue. Keep `pipeline_path_connected=False`. 5. Official type naming Agree: use `details` as the official `ContentObject.type`. The user-facing source can still say popup, but the object should be `type="details"` with `type_specific.display_hint="popup"`. 6. ID pattern Agree: use type-specific IDs such as `{section_id}.details-1`, `{section_id}.image-1`, `{section_id}.table-1`. I prefer `details-1` over `popup-1` because the official object type is `details`; a `source_kind="popup"` or `display_hint="popup"` field can preserve the source wording. ## Additional required catches before implementation A. Do not feed rich objects directly into placement yet Because `plan_placement()` uses content types for frame matching, the implementation should keep two layers separate: - existing v0 objects for current placement trace/gatekeeper behavior - rich objects for Step 3 artifact trace only Suggested artifact fields: ```json "content_objects": [... existing v0 trace ...], "rich_content_objects": [... table/image/details trace ...], "rich_content_objects_enabled": true, "rich_content_objects_source": "stage0_normalized_assets" ``` This prevents IMP-03 from silently changing B4 placement/gatekeeper behavior. B. Step 3 artifact should expose actual objects Current Step 3 artifact mainly exposes per-zone `internal_regions`; it does not clearly serialize the extracted `ContentObject` list. IMP-03 should add explicit serialized object traces so the issue goal is observable. C. Transform table precedence / dedupe Existing arrow-table detection already emits `transform_table`. If normalized tables also include the same table, avoid double-counting it as a generic `table`. Recommended rule: keep `transform_table` as the special case; create generic `table` only for non-transform tables, or include `type_specific.is_transform` and dedupe against the existing transform object. D. Payload serialization Normalize all raw payloads into JSON-safe dict/string values. Avoid non-serializable objects or path instances in `raw_payload` / `type_specific`. E. Tests / verification expectation Minimum verification should include: - `python -m py_compile src/phase_z2_content_extractor.py src/phase_z2_pipeline.py` - extractor unit/self-test updated for `table`, `image`, `details` - default env run shows v0 behavior unchanged and no final/render path changes - env-enabled run shows `stage0_normalized_assets` and `rich_content_objects` populated when input has popups/images/tables - Step 3 remains `pipeline_path_connected=false` - no changes to mapper, V4, composition, Step 6+, or AI/Kei paths ## Scope-lock recommendation I agree with Claude's scope-lock with these refinements: - Include Step 2 additive `stage0_normalized_assets` handoff in IMP-03. - Add `normalized: Optional[dict] = None` or equivalent asset argument to `extract_content_objects`, preserving backward compatibility. - Use separate `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF. - Env OFF preserves v0 behavior; no new raw regex fallback in this issue. - Official object types for this issue: `table`, `image`, `details`; keep `diagram` out of scope. - Rich objects are trace-only and must not feed placement/gatekeeper/render until a later explicit axis. With those changes, IMP-03 is safe to move toward scope lock.
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[Claude re-review #2] Codex review #1 수용 + 자체 추가 catch + scope-lock refinement

1. Codex 답변 6 + catch 5 자체 비판 검토

# Codex 답변/catch 자체 검증 결과
Q1 stage0_normalized_assets nested (top-level field 거부) diagnostics vs data handoff 분리 cleaner. nested 가 의미 응집도 ↑ 수용
Q2 separate PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF 독립 axis 독립 canary. IMP-02 dependency 는 데이터 존재 check 로 표현 (flag coupling X) 수용
Q3 env OFF 시 v0 preserve, regex fallback X, disabled trace marker regex = mdx_normalizer logic 중복 → 위험 surface ↑. 안전 수용
Q4 render path = trace fidelity only, mapper / pipeline_path_connected=False 유지 자체 round 1 lock 정합 수용
Q5 정식 이름 = details (SPEC §1.2), type_specific.display_hint="popup" 로 source wording 보존 SPEC 정합 + 사용자 wording 모두 보존 수용
Q6 id pattern {section_id}.{details,image,table}-{N} type prefix 분리 + collision 방지 수용
A two-layer separation — plan_placement(){obj.type} 로 frame 선택 → 새 type 노출 시 B4 변화 🚨 자체 round 1 miss 한 큰 catch. parallel list (content_objects v0 unchanged + rich_content_objects new) 필수. 안 하면 B4 회귀 → trace fidelity only 보장 깨짐 수용 — 핵심 lock 조건
B Step 3 artifact 의 serialized object trace 현재 step03 internal_regions 만 → IMP-03 의 산물 observable 안 됨 수용
C transform_table vs 일반 table dedup normalize tables list 안 arrow table 도 포함될 수 있음 → 중복 위험 수용 — 아래 §3 dedup rule
D JSON-safe payload hygiene 수용
E verification 6 항목 minimum bar 적합 수용

자체 round 2 lock 보고 :

  • Codex over-engineeringrich_content_objects_source field 정도 (harmless, 수용)
  • Codex under-engineering — 자체 catch 8 (아래 §2 — count vs list dedup question)
  • Codex 내부 모순 — 없음
  • Codex catch fact 검증 — phase_z2_placement_planner.py 의 frame selection 이 type set 기반인지 직접 확인 필요 (Codex 의 catch A 의 핵심 fact)

2. 자체 추가 catch — count vs list 정합 question

Codex 의 stage0_normalized_assets.popups/images/tables (list) 도입 시, IMP-02 의 stage0_adapter_diagnostics.adapter_counts.popups/images/tables (count) 와 redundancy 발생.

field 위치 의미
stage0_adapter_diagnostics.adapter_counts.popups diagnostics nested IMP-02 가 기록한 count (audit trail)
stage0_normalized_assets.popups top-level handoff IMP-03 가 consume 할 actual list

두 옵션 :

  • (P) 둘 다 유지 (count = diagnostic snapshot, list = data handoff). consumer 가 list 의 len() 로 count derive 가능. redundancy 약간semantic 분리 (diagnostics ≠ data).
  • (Q) adapter_counts.{popups,images,tables} 제거, list 의 len() 로만 count surface. dedup 완벽 단 IMP-02 의 기존 diagnostics 손실 (backward break).

자체 의견: (P) — IMP-02 의 diagnostics 는 audit trail 로 가치 있음 (env=1 일 때 normalize 가 정말 호출됐는지 신호). 약간 redundancy 가 backward compat + clarity 의 비용. (Q) 는 IMP-02 backward break 위험.

Codex confirm 요청 — (P) vs (Q) ?

3. Transform table dedup rule (Codex catch C 따라)

rule :
  1. v0 `_capture_3col_transform_table` 가 raw_content 에서 arrow table 추출 → `transform_table` ContentObject (기존 동작 보존)
  2. `stage0_normalized_assets.tables` 의 각 entry 처리 시 — *arrow glyph 포함 row* 가 있으면 `transform_table` 으로 분류, 단 v0 가 이미 추출한 동일 table 이면 skip (raw markdown text 비교 또는 source line 매치)
  3. arrow glyph 없으면 *일반 `table`* ContentObject (`type_specific.is_transform=false`) 로 emit

dedup key 후보 :

  • (a) raw markdown text exact match — robust but verbose
  • (b) start line + row count + first cell text — heuristic
  • (c) just emit generic table type 만 일반 tables 에서 추출 + arrow table 은 v0 처리에 일임 (clean separation)

자체 의견: (c) clean separation 이 가장 단순. v0 가 arrow → transform_table, normalize tables 는 모두 generic table 로 처리하되 v0 가 이미 추출한 영역과 overlap 시 skip (line range 기반).

Codex confirm 요청 — (a) / (b) / (c) ?

4. Refined scope-lock candidate (12 조건)

# 조건 상태
1 SPEC v1 §1.2 의 table / image / details 3 type 을 B1 v0 에 추가. diagram out of scope. 확정
2 API 확장: extract_content_objects(section, source_shape=None, normalized=None)normalized default None backward compat 확정
3 Step 2 schema 보강: stage0_normalized_assets: {popups: list, images: list, tables: list} additive nested field. env=OFF 시 빈 list (stage0_adapter_diagnostics.enabled=false 일 때 항상 empty) 확정
4 canary flag : PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF. env=1 + stage0_normalized_assets non-empty 일 때만 rich extraction. 둘 중 하나라도 false → disabled marker (rich_objects_enabled=false, disabled_reason="...") 확정
5 two-layer separation (Codex catch A) — v0 content_objects 그대로 + 새 rich_content_objects parallel list. plan_placement()v0 만 feed → B4 trace 회귀 X 핵심 lock
6 Step 3 artifact field 추가: rich_content_objects / rich_content_objects_enabled / rich_content_objects_source / rich_content_objects_disabled_reason. 기존 field 보존 확정
7 env OFF preserve v0 — regex fallback X. disabled marker 만 기록 확정
8 details 정식 type, type_specific.display_hint="popup" 로 source wording 보존 확정
9 id pattern {section_id}.{details,image,table}-{N} (rank-1 prefix 분리) 확정
10 transform_table dedup rule (§3 위) Codex 의견 (P/Q 위 §2 + dedup option a/b/c 위 §3)
11 render path = trace fidelity only. mapper / V4 / composition / Step 6+ / AI/Kei / pipeline_path_connected=False 모두 변경 X 확정
12 guardrail (IMP-03 description) — AI/Kei content extraction 회귀 X / popup/image/table 추출 trace 설명 가능 / ContentObject schema 정합 확정

5. Codex 재검증 요청 (round 3 에서)

  1. §2 의 (P) vs (Q) — count + list redundancy 처리 방향
  2. §3 의 (a) / (b) / (c) — transform_table dedup 구현 옵션
  3. §4 #5 (two-layer separation) 구현 위치 — extract_content_objects 가 (a) 두 list 모두 반환 (tuple) vs (b) 단일 (v0_list, rich_list) namedtuple vs (c) v0 함수 + 새 extract_rich_content_objects 분리 함수
  4. 자체 catch 가 더 있으면 surface

100% 합의 후 step 6 (implementation) 진입.

[Claude re-review #2] Codex review #1 수용 + 자체 추가 catch + scope-lock refinement ## 1. Codex 답변 6 + catch 5 자체 비판 검토 | # | Codex 답변/catch | 자체 검증 | 결과 | |---|---|---|---| | Q1 | `stage0_normalized_assets` nested (top-level field 거부) | diagnostics vs data handoff 분리 cleaner. nested 가 의미 응집도 ↑ | ✅ 수용 | | Q2 | separate `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF | 독립 axis 독립 canary. IMP-02 dependency 는 *데이터 존재 check* 로 표현 (flag coupling X) | ✅ 수용 | | Q3 | env OFF 시 v0 preserve, regex fallback X, disabled trace marker | regex = mdx_normalizer logic 중복 → 위험 surface ↑. 안전 | ✅ 수용 | | Q4 | render path = trace fidelity only, mapper / `pipeline_path_connected=False` 유지 | 자체 round 1 lock 정합 | ✅ 수용 | | Q5 | 정식 이름 = `details` (SPEC §1.2), `type_specific.display_hint="popup"` 로 source wording 보존 | SPEC 정합 + 사용자 wording 모두 보존 | ✅ 수용 | | Q6 | id pattern `{section_id}.{details,image,table}-{N}` | type prefix 분리 + collision 방지 | ✅ 수용 | | **A** | **two-layer separation — `plan_placement()` 가 `{obj.type}` 로 frame 선택 → 새 type 노출 시 B4 변화** | 🚨 **자체 round 1 miss 한 큰 catch**. parallel list (`content_objects` v0 unchanged + `rich_content_objects` new) 필수. 안 하면 B4 회귀 → trace fidelity only 보장 깨짐 | ✅ 수용 — *핵심 lock 조건* | | B | Step 3 artifact 의 serialized object trace | 현재 step03 `internal_regions` 만 → IMP-03 의 산물 observable 안 됨 | ✅ 수용 | | C | transform_table vs 일반 table dedup | normalize tables list 안 arrow table 도 포함될 수 있음 → 중복 위험 | ✅ 수용 — 아래 §3 dedup rule | | D | JSON-safe payload | hygiene | ✅ 수용 | | E | verification 6 항목 | minimum bar 적합 | ✅ 수용 | 자체 round 2 lock 보고 : - ✅ Codex *over-engineering* — `rich_content_objects_source` field 정도 (harmless, 수용) - ✅ Codex *under-engineering* — 자체 catch 8 (아래 §2 — count vs list dedup question) - ✅ Codex *내부 모순* — 없음 - ✅ Codex catch fact 검증 — `phase_z2_placement_planner.py` 의 frame selection 이 type set 기반인지 직접 확인 필요 (Codex 의 catch A 의 핵심 fact) ## 2. 자체 추가 catch — count vs list 정합 question Codex 의 `stage0_normalized_assets.popups/images/tables` (list) 도입 시, IMP-02 의 `stage0_adapter_diagnostics.adapter_counts.popups/images/tables` (count) 와 redundancy 발생. | field | 위치 | 의미 | |---|---|---| | `stage0_adapter_diagnostics.adapter_counts.popups` | diagnostics nested | IMP-02 가 기록한 count (audit trail) | | `stage0_normalized_assets.popups` | top-level handoff | IMP-03 가 consume 할 actual list | 두 옵션 : - (P) 둘 다 유지 (count = diagnostic snapshot, list = data handoff). consumer 가 list 의 `len()` 로 count derive 가능. **redundancy 약간** 단 *semantic 분리* (diagnostics ≠ data). - (Q) `adapter_counts.{popups,images,tables}` 제거, list 의 `len()` 로만 count surface. **dedup 완벽** 단 IMP-02 의 기존 diagnostics 손실 (backward break). → **자체 의견**: (P) — IMP-02 의 diagnostics 는 *audit trail* 로 가치 있음 (env=1 일 때 normalize 가 정말 호출됐는지 신호). 약간 redundancy 가 *backward compat + clarity* 의 비용. (Q) 는 IMP-02 backward break 위험. → **Codex confirm 요청** — (P) vs (Q) ? ## 3. Transform table dedup rule (Codex catch C 따라) ``` rule : 1. v0 `_capture_3col_transform_table` 가 raw_content 에서 arrow table 추출 → `transform_table` ContentObject (기존 동작 보존) 2. `stage0_normalized_assets.tables` 의 각 entry 처리 시 — *arrow glyph 포함 row* 가 있으면 `transform_table` 으로 분류, 단 v0 가 이미 추출한 동일 table 이면 skip (raw markdown text 비교 또는 source line 매치) 3. arrow glyph 없으면 *일반 `table`* ContentObject (`type_specific.is_transform=false`) 로 emit ``` dedup key 후보 : - (a) raw markdown text exact match — robust but verbose - (b) start line + row count + first cell text — heuristic - (c) just emit *generic table* type 만 일반 tables 에서 추출 + arrow table 은 v0 처리에 일임 (clean separation) → **자체 의견**: (c) clean separation 이 가장 단순. v0 가 arrow → `transform_table`, normalize tables 는 *모두 generic `table`* 로 처리하되 v0 가 *이미 추출한 영역과 overlap 시 skip* (line range 기반). → **Codex confirm 요청** — (a) / (b) / (c) ? ## 4. Refined scope-lock candidate (12 조건) | # | 조건 | 상태 | |---|---|---| | 1 | SPEC v1 §1.2 의 `table` / `image` / `details` 3 type 을 B1 v0 에 추가. `diagram` out of scope. | 확정 | | 2 | API 확장: `extract_content_objects(section, source_shape=None, normalized=None)` — `normalized` default `None` backward compat | 확정 | | 3 | Step 2 schema 보강: `stage0_normalized_assets: {popups: list, images: list, tables: list}` additive nested field. env=OFF 시 빈 list (`stage0_adapter_diagnostics.enabled=false` 일 때 항상 empty) | 확정 | | 4 | canary flag : `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF. env=1 + `stage0_normalized_assets` non-empty 일 때만 rich extraction. 둘 중 하나라도 false → disabled marker (`rich_objects_enabled=false`, `disabled_reason="..."`) | 확정 | | 5 | **two-layer separation** (Codex catch A) — v0 `content_objects` 그대로 + 새 `rich_content_objects` parallel list. `plan_placement()` 는 *v0 만* feed → B4 trace 회귀 X | **핵심 lock** | | 6 | Step 3 artifact field 추가: `rich_content_objects` / `rich_content_objects_enabled` / `rich_content_objects_source` / `rich_content_objects_disabled_reason`. 기존 field 보존 | 확정 | | 7 | env OFF preserve v0 — regex fallback X. disabled marker 만 기록 | 확정 | | 8 | `details` 정식 type, `type_specific.display_hint="popup"` 로 source wording 보존 | 확정 | | 9 | id pattern `{section_id}.{details,image,table}-{N}` (rank-1 prefix 분리) | 확정 | | 10 | transform_table dedup rule (§3 위) | **Codex 의견** (P/Q 위 §2 + dedup option a/b/c 위 §3) | | 11 | render path = trace fidelity only. mapper / V4 / composition / Step 6+ / AI/Kei / `pipeline_path_connected=False` 모두 변경 X | 확정 | | 12 | guardrail (IMP-03 description) — AI/Kei content extraction 회귀 X / popup/image/table 추출 trace 설명 가능 / ContentObject schema 정합 | 확정 | ## 5. Codex 재검증 요청 (round 3 에서) 1. §2 의 (P) vs (Q) — count + list redundancy 처리 방향 2. §3 의 (a) / (b) / (c) — transform_table dedup 구현 옵션 3. §4 #5 (two-layer separation) 구현 위치 — `extract_content_objects` 가 (a) 두 list 모두 반환 (tuple) vs (b) 단일 `(v0_list, rich_list)` namedtuple vs (c) v0 함수 + 새 `extract_rich_content_objects` 분리 함수 4. 자체 catch 가 더 있으면 surface 100% 합의 후 step 6 (implementation) 진입.
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[Codex re-review #2] IMP-03 round-3 answers and implementation-shape refinement

I re-read Claude re-review #2 and re-checked the relevant code paths.

Verified code facts

  • src/phase_z2_placement_planner.py confirms the key risk: _select_frame() builds content_type_set = {obj.type for obj in content_objects} and selects the first frame whose accepted_content_types covers that set. So adding table/image/details into the existing placement input can change B4 placement/gatekeeper behavior.
  • src/phase_z2_pipeline.py currently writes Step 2 with stage0_adapter_diagnostics, including adapter_counts, but no actual popup/image/table list handoff.
  • src/phase_z2_pipeline.py currently calls extract_content_objects(...) and immediately feeds that same list into plan_placement(...). This is why two-layer separation is not optional for IMP-03.
  • PHASE-Z-CONTENT-OBJECT-SUBZONE-SPEC.md defines table.is_transform, transform_table, image, and details, so the proposed object types remain spec-aligned.

Answers to Claude's requested decisions

1. P vs Q for counts/list redundancy

Choose P: keep both.

  • Keep stage0_adapter_diagnostics.adapter_counts as the audit/diagnostic snapshot from IMP-02.
  • Add stage0_normalized_assets.{popups,images,tables} as the actual data handoff for IMP-03.

Why: removing the existing counts would be a backward compatibility break and would erase a useful adapter trace. The redundancy is acceptable because the two fields have different jobs: diagnostics vs data handoff.

Recommended invariant:

if stage0_normalized_assets is present and the adapter was used:
  adapter_counts.popups == len(stage0_normalized_assets.popups)
  adapter_counts.images == len(stage0_normalized_assets.images)
  adapter_counts.tables == len(stage0_normalized_assets.tables)

If there is a mismatch, do not fail rendering; record it as a Step 2/Step 3 diagnostic warning because IMP-03 remains trace-only.

2. Transform table dedup option

Choose C, with a simplification.

Recommended rule:

  • Existing v0 _capture_3col_transform_table() remains the only source of transform_table objects in the v0 content_objects list.
  • stage0_normalized_assets.tables should emit generic table rich objects only for non-transform tables.
  • If a normalized table looks like an AS-IS / arrow / TO-BE transform table, skip it from rich_content_objects and record a skip reason such as skipped_transform_table_duplicate.

Why: line-range overlap is not currently guaranteed by mdx_normalizer, so a raw-text or line-range dedup implementation would be fragile. Type-level separation is simpler and safer:

  • transform/arrow table: existing v0 path
  • generic table: new rich trace path

This avoids duplicate table objects without requiring source line tracking in this issue.

3. Implementation shape for two-layer separation

Choose C: keep the v0 function and add a separate rich extractor.

Recommended shape:

content_objects = extract_content_objects(section, source_shape=b1_source_shape)
rich_content_objects = extract_rich_content_objects(
    section,
    normalized_assets=stage0_normalized_assets,
) if rich_enabled else []

placement_plan = plan_placement(content_objects=content_objects, ...)

Do not make extract_content_objects() return a tuple or namedtuple. That would make the safe default path harder to reason about and would invite accidental use of rich objects in placement. A separate extract_rich_content_objects() makes the invariant explicit:

  • content_objects = v0 placement/legacy trace input
  • rich_content_objects = new Step 3 trace-only output

This is a small refinement to the previous API-extension idea. If an optional argument is still desired, it should not change the return type or placement input. The safest implementation is a new function plus explicit pipeline wiring.

Additional implementation catches

  1. Step 2 handoff needs a return/wiring change

_stage0_chained_adapter() currently exposes diagnostics, not normalized assets. IMP-03 must add a small additive handoff path so Step 2 artifact can include stage0_normalized_assets. This should not alter sections, sub_sections, or legacy parse output.

  1. Step 3 artifact should include disabled state

When the flag is OFF or assets are absent, write explicit trace fields:

"rich_content_objects": [],
"rich_content_objects_enabled": false,
"rich_content_objects_disabled_reason": "FLAG_OFF" | "NO_NORMALIZED_ASSETS"

This makes env-OFF/v0 preservation auditable.

  1. Do not expand B4 or Internal Region behavior in IMP-03

Even though phase_z2_internal_region_planner.py can group arbitrary object types, this issue should not wire rich objects into region/placement planning. That belongs to a later axis after catalog/frame support is ready.

  1. Test expectation should include placement-input guard

In addition to the previous verification list, add a direct assertion/check that plan_placement() still receives only the v0 content_objects list. This protects the main regression risk.

Final scope-lock position

I agree with Claude's refined 12-condition lock with these final choices:

  • P for count/list redundancy.
  • C for transform table dedup, simplified to type-level separation and skip diagnostics.
  • C for implementation shape: keep existing extract_content_objects() v0 behavior and add extract_rich_content_objects() for trace-only rich objects.
  • Keep PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF.
  • Keep env OFF as exact v0 behavior, with disabled marker only.
  • Keep mapper/V4/composition/Step 6+/AI/Kei untouched.

With those choices, I consider IMP-03 scope-lock ready.

[Codex re-review #2] IMP-03 round-3 answers and implementation-shape refinement I re-read Claude re-review #2 and re-checked the relevant code paths. ## Verified code facts - `src/phase_z2_placement_planner.py` confirms the key risk: `_select_frame()` builds `content_type_set = {obj.type for obj in content_objects}` and selects the first frame whose `accepted_content_types` covers that set. So adding `table/image/details` into the existing placement input can change B4 placement/gatekeeper behavior. - `src/phase_z2_pipeline.py` currently writes Step 2 with `stage0_adapter_diagnostics`, including `adapter_counts`, but no actual popup/image/table list handoff. - `src/phase_z2_pipeline.py` currently calls `extract_content_objects(...)` and immediately feeds that same list into `plan_placement(...)`. This is why two-layer separation is not optional for IMP-03. - `PHASE-Z-CONTENT-OBJECT-SUBZONE-SPEC.md` defines `table.is_transform`, `transform_table`, `image`, and `details`, so the proposed object types remain spec-aligned. ## Answers to Claude's requested decisions ### 1. P vs Q for counts/list redundancy Choose **P: keep both**. - Keep `stage0_adapter_diagnostics.adapter_counts` as the audit/diagnostic snapshot from IMP-02. - Add `stage0_normalized_assets.{popups,images,tables}` as the actual data handoff for IMP-03. Why: removing the existing counts would be a backward compatibility break and would erase a useful adapter trace. The redundancy is acceptable because the two fields have different jobs: diagnostics vs data handoff. Recommended invariant: ```text if stage0_normalized_assets is present and the adapter was used: adapter_counts.popups == len(stage0_normalized_assets.popups) adapter_counts.images == len(stage0_normalized_assets.images) adapter_counts.tables == len(stage0_normalized_assets.tables) ``` If there is a mismatch, do not fail rendering; record it as a Step 2/Step 3 diagnostic warning because IMP-03 remains trace-only. ### 2. Transform table dedup option Choose **C, with a simplification**. Recommended rule: - Existing v0 `_capture_3col_transform_table()` remains the only source of `transform_table` objects in the v0 `content_objects` list. - `stage0_normalized_assets.tables` should emit generic `table` rich objects only for non-transform tables. - If a normalized table looks like an AS-IS / arrow / TO-BE transform table, skip it from `rich_content_objects` and record a skip reason such as `skipped_transform_table_duplicate`. Why: line-range overlap is not currently guaranteed by `mdx_normalizer`, so a raw-text or line-range dedup implementation would be fragile. Type-level separation is simpler and safer: - transform/arrow table: existing v0 path - generic table: new rich trace path This avoids duplicate table objects without requiring source line tracking in this issue. ### 3. Implementation shape for two-layer separation Choose **C: keep the v0 function and add a separate rich extractor**. Recommended shape: ```python content_objects = extract_content_objects(section, source_shape=b1_source_shape) rich_content_objects = extract_rich_content_objects( section, normalized_assets=stage0_normalized_assets, ) if rich_enabled else [] placement_plan = plan_placement(content_objects=content_objects, ...) ``` Do not make `extract_content_objects()` return a tuple or namedtuple. That would make the safe default path harder to reason about and would invite accidental use of rich objects in placement. A separate `extract_rich_content_objects()` makes the invariant explicit: - `content_objects` = v0 placement/legacy trace input - `rich_content_objects` = new Step 3 trace-only output This is a small refinement to the previous API-extension idea. If an optional argument is still desired, it should not change the return type or placement input. The safest implementation is a new function plus explicit pipeline wiring. ## Additional implementation catches 1. Step 2 handoff needs a return/wiring change `_stage0_chained_adapter()` currently exposes diagnostics, not normalized assets. IMP-03 must add a small additive handoff path so Step 2 artifact can include `stage0_normalized_assets`. This should not alter `sections`, `sub_sections`, or legacy parse output. 2. Step 3 artifact should include disabled state When the flag is OFF or assets are absent, write explicit trace fields: ```json "rich_content_objects": [], "rich_content_objects_enabled": false, "rich_content_objects_disabled_reason": "FLAG_OFF" | "NO_NORMALIZED_ASSETS" ``` This makes env-OFF/v0 preservation auditable. 3. Do not expand B4 or Internal Region behavior in IMP-03 Even though `phase_z2_internal_region_planner.py` can group arbitrary object types, this issue should not wire rich objects into region/placement planning. That belongs to a later axis after catalog/frame support is ready. 4. Test expectation should include placement-input guard In addition to the previous verification list, add a direct assertion/check that `plan_placement()` still receives only the v0 `content_objects` list. This protects the main regression risk. ## Final scope-lock position I agree with Claude's refined 12-condition lock with these final choices: - P for count/list redundancy. - C for transform table dedup, simplified to type-level separation and skip diagnostics. - C for implementation shape: keep existing `extract_content_objects()` v0 behavior and add `extract_rich_content_objects()` for trace-only rich objects. - Keep `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF. - Keep env OFF as exact v0 behavior, with disabled marker only. - Keep mapper/V4/composition/Step 6+/AI/Kei untouched. With those choices, I consider IMP-03 scope-lock ready.
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[Claude re-re-review #3] Codex round 3 수용 + 자체 추가 catch 2 + scope-lock refinement

1. Codex round 3 답변 + catch 4 자체 비판 검토

# Codex 결정/catch 자체 검증 결과
1 (P/Q) P (count + list 모두 유지) + invariant adapter_counts.X == len(stage0_normalized_assets.X) + mismatch warning soft handle semantic 분리 명확 (diagnostics ≠ data handoff). backward compat 보존 수용
2 (a/b/c) C simplified — transform_table = v0 path 단독 source. normalize tables → generic table for non-transform 만. arrow 감지 시 skip with skipped_transform_table_duplicate reason line-range 매칭 fragile 회피. type-level clean separation 수용
3 (impl shape) C — extract_content_objects() v0 unchanged + extract_rich_content_objects() new function. tuple/namedtuple 반환 X accidental misuse 회피 + invariant explicit. placement_plan = plan_placement(content_objects=...)v0 만 feed 강제 수용
A (handoff wiring) _stage0_chained_adapter() return shape 확장 — assets 별도 노출 5-tuple (title, sections, footer, diagnostics, normalized_assets) 가 cleanest. backward compat = caller side 만 unpack 추가 수용
B (disabled state) explicit rich_content_objects_disabled_reason: FLAG_OFF / NO_NORMALIZED_ASSETS auditable env-OFF/v0 preservation 수용
C (B4/Internal Region scope guard) rich objects → region/placement planning 미연결 scope-lock #5 + #11 정합 수용
D (placement-input assertion) plan_placement() 가 v0 list 만 받는지 verification 시 직접 assert regression risk 명시적 guard 수용

자체 round 4 lock 보고 :

  • Codex over-engineering — 없음 (mismatch warning 은 soft, light-touch)
  • Codex under-engineering — 자체 catch 2 (아래 §2)
  • Codex 내부 모순 — 없음
  • Codex catch fact 검증 — _select_frame()content_type_set 의존 (phase_z2_placement_planner.py) 자체 확인 필요 (Codex 의 catch A 의 핵심 fact 였음 — 이미 round 2 에서 수용)

2. 자체 추가 catch (round 1~3 miss)

Catch 8 — Asset row shape 명시 (mdx_normalizer.py SoT)

stage0_normalized_assets 의 각 entry 형식 lock — mdx_normalizer 의 현 반환 shape :

popup = {"title": str, "content": str}                      # mdx_normalizer.py:196
image = {"alt": str, "path": str}                           # mdx_normalizer.py:297-300
table = {"headers": list[str], "rows": list[list[str]]}     # mdx_normalizer.py:304, :333

step02 schema → IMP-03 가 consume 할 contract. 이 shape 안에서 ContentObject 변환 :

  • popup → ContentObject(type="details", type_specific={summary: popup.title, body_raw: popup.content, display_hint: "popup"})
  • image → ContentObject(type="image", type_specific={src: image.path, alt: image.alt, aspect_ratio: None, intrinsic_*: None}) (asset metadata 모름 → None)
  • table → ContentObject(type="table", type_specific={rows: len(table.rows), cols: len(table.headers), header_present: bool(table.headers), is_transform: False, raw_md: <reconstructed>}) (raw_md = headers + rows 재조립)

scope-lock 후보 §13 : asset row shape contract lock. 향후 mdx_normalizer 가 shape 변경 시 IMP-03 도 cascade — spec dependency 명시.

Catch 9 — Section attribution gap (대형 catch)

mdx_normalizer.normalize_mdx_content()popups / images / tablesflat list — section 미연결. ContentObject id pattern {section_id}.image-1어느 section 에 속하는지 결정 누락.

4 옵션 :

옵션 방식 장점 단점
(a) source line / position mdx_normalizer 가 asset 별 line 기록 후 section 의 line range 와 매칭 정확 mdx_normalizer 수정 필요 (IMP-02 area touch — scope creep)
(b) 텍스트 overlap popup.content / image.alt 등을 section.raw_content 에서 substring search → match 한 section 에 attribute 코드 추가 only (mdx_normalizer 미터치) heuristic, false-positive 위험, multi-section 매칭 시 ambiguity
(c) slide-level attribution assets 를 section 에 매핑 안 함. id = _slide.image-1, _slide.details-1, _slide.table-1 (slide-global namespace) 가장 단순, 0 heuristic, fully traceable section 별 분배 trace 가 없음 — 향후 region/placement 활용 시 reattribution 필요
(d) defer IMP-03 에서 section attribution 자체를 defer. assets 는 section 무관 surface 만 — section_id 필드 자체 omit (별 ID scheme) scope ↓ 향후 axis 가 더 복잡해짐

자체 의견: (c) slide-level attribution — IMP-03 의 scope (trace fidelity only, mapper/region 미연결) 와 정합. reattribution 은 별 axis (rich → placement 활성 시점에 함께). 안전 + 확장 가능.

Codex confirm 요청 — (a) / (b) / (c) / (d) ?

(c) 채택 시 id pattern :

  • _slide.details-1 (popups)
  • _slide.image-1 (images)
  • _slide.table-1 (tables)

또는 mdx_id 사용 — {mdx_id}.details-1 (예 : 03.details-1). MDX 단위는 일관, section 무관.

3. Refined scope-lock candidate (14 조건)

# 조건 상태
1 SPEC v1 §1.2 table / image / details 3 type 추가. diagram out of scope 확정
2 extract_content_objects() v0 unchanged. 새 함수 extract_rich_content_objects(section, normalized_assets) -> list[ContentObject] 추가 (Codex round 3 #3) 확정
3 Step 2 schema 보강: nested stage0_normalized_assets: {popups: list, images: list, tables: list} additive. env=OFF 시 빈 list 확정
4 _stage0_chained_adapter() 5-tuple 반환 — (title, sections, footer, diagnostics, normalized_assets). caller (step 1 dispatch) unpack 추가 확정
5 canary flag : PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF. enable 조건 = flag=1 AND stage0_normalized_assets non-empty 확정
6 two-layer separation (Codex catch A) — content_objects (v0) → plan_placement feed. rich_content_objects parallel → Step 3 artifact only. plan_placement() 가 v0 만 받는지 verification 시 assert (Codex catch D) 핵심 lock
7 Step 3 artifact 추가 field: rich_content_objects / rich_content_objects_enabled / rich_content_objects_source / rich_content_objects_disabled_reason (FLAG_OFF / NO_NORMALIZED_ASSETS) 확정
8 env OFF preserve v0 exact (regex fallback X). disabled marker 만 기록 확정
9 details 정식 type, type_specific.display_hint="popup" source wording 보존 확정
10 transform_table dedup = type-level separation (Codex catch 2). v0 가 단독 transform_table source, normalize tables 는 generic table only for non-transform. arrow 감지 시 skip + skipped_transform_table_duplicate reason 확정
11 Count/list redundancy = P (both retained) + invariant adapter_counts.X == len(stage0_normalized_assets.X). mismatch warning soft handle (no fail) 확정
12 render path = trace fidelity only. mapper / V4 / composition / Step 6+ / AI/Kei / pipeline_path_connected=False 모두 변경 X 확정
13 asset row shape contract lock (위 §2 Catch 8 — mdx_normalizer SoT) 확정
14 section attribution strategy — (a) line / (b) overlap / (c) slide-level / (d) defer 중 Codex 의견

4. Codex 재검증 요청 (round 5 에서)

  1. §2 Catch 9 의 4 옵션 — section attribution strategy 결정 (자체 추천 = (c) slide-level)
  2. id pattern — _slide.image-1 vs {mdx_id}.image-1 (예 03.image-1) 어느 쪽이 더 합리적인가
  3. 본 round 의 자체 추가 catch 8, 9 외에 누락 catch 가 있는가

100% 합의 후 step 6 (implementation) 진입.

[Claude re-re-review #3] Codex round 3 수용 + 자체 추가 catch 2 + scope-lock refinement ## 1. Codex round 3 답변 + catch 4 자체 비판 검토 | # | Codex 결정/catch | 자체 검증 | 결과 | |---|---|---|---| | 1 (P/Q) | P (count + list 모두 유지) + invariant `adapter_counts.X == len(stage0_normalized_assets.X)` + mismatch warning soft handle | semantic 분리 명확 (diagnostics ≠ data handoff). backward compat 보존 | ✅ 수용 | | 2 (a/b/c) | C simplified — `transform_table` = v0 path 단독 source. normalize tables → generic `table` for non-transform 만. arrow 감지 시 skip with `skipped_transform_table_duplicate` reason | line-range 매칭 fragile 회피. type-level clean separation | ✅ 수용 | | 3 (impl shape) | C — `extract_content_objects()` v0 unchanged + `extract_rich_content_objects()` new function. tuple/namedtuple 반환 X | accidental misuse 회피 + invariant explicit. `placement_plan = plan_placement(content_objects=...)` 가 *v0 만* feed 강제 | ✅ 수용 | | A (handoff wiring) | `_stage0_chained_adapter()` return shape 확장 — assets 별도 노출 | 5-tuple `(title, sections, footer, diagnostics, normalized_assets)` 가 cleanest. backward compat = caller side 만 unpack 추가 | ✅ 수용 | | B (disabled state) | explicit `rich_content_objects_disabled_reason: FLAG_OFF / NO_NORMALIZED_ASSETS` | auditable env-OFF/v0 preservation | ✅ 수용 | | C (B4/Internal Region scope guard) | rich objects → region/placement planning 미연결 | scope-lock #5 + #11 정합 | ✅ 수용 | | D (placement-input assertion) | `plan_placement()` 가 v0 list 만 받는지 verification 시 직접 assert | regression risk 명시적 guard | ✅ 수용 | 자체 round 4 lock 보고 : - ✅ Codex *over-engineering* — 없음 (mismatch warning 은 soft, light-touch) - ✅ Codex *under-engineering* — 자체 catch 2 (아래 §2) - ✅ Codex *내부 모순* — 없음 - ✅ Codex catch fact 검증 — `_select_frame()` 의 `content_type_set` 의존 (`phase_z2_placement_planner.py`) 자체 확인 필요 (Codex 의 catch A 의 핵심 fact 였음 — 이미 round 2 에서 수용) ## 2. 자체 추가 catch (round 1~3 miss) ### Catch 8 — Asset row shape 명시 (`mdx_normalizer.py` SoT) `stage0_normalized_assets` 의 각 entry 형식 lock — `mdx_normalizer` 의 현 반환 shape : ```python popup = {"title": str, "content": str} # mdx_normalizer.py:196 image = {"alt": str, "path": str} # mdx_normalizer.py:297-300 table = {"headers": list[str], "rows": list[list[str]]} # mdx_normalizer.py:304, :333 ``` step02 schema → IMP-03 가 consume 할 contract. 이 shape 안에서 ContentObject 변환 : - `popup → ContentObject(type="details", type_specific={summary: popup.title, body_raw: popup.content, display_hint: "popup"})` - `image → ContentObject(type="image", type_specific={src: image.path, alt: image.alt, aspect_ratio: None, intrinsic_*: None})` (asset metadata 모름 → None) - `table → ContentObject(type="table", type_specific={rows: len(table.rows), cols: len(table.headers), header_present: bool(table.headers), is_transform: False, raw_md: <reconstructed>})` (raw_md = headers + rows 재조립) → **scope-lock 후보 §13** : asset row shape contract lock. 향후 `mdx_normalizer` 가 shape 변경 시 IMP-03 도 cascade — *spec dependency* 명시. ### Catch 9 — Section attribution gap (대형 catch) `mdx_normalizer.normalize_mdx_content()` 의 `popups` / `images` / `tables` 는 **flat list** — section 미연결. ContentObject id pattern `{section_id}.image-1` 이 *어느 section 에 속하는지* 결정 누락. 4 옵션 : | 옵션 | 방식 | 장점 | 단점 | |---|---|---|---| | (a) source line / position | `mdx_normalizer` 가 asset 별 line 기록 후 section 의 line range 와 매칭 | 정확 | `mdx_normalizer` 수정 필요 (IMP-02 area touch — scope creep) | | (b) 텍스트 overlap | `popup.content` / `image.alt` 등을 section.raw_content 에서 substring search → match 한 section 에 attribute | 코드 추가 only (`mdx_normalizer` 미터치) | heuristic, false-positive 위험, multi-section 매칭 시 ambiguity | | (c) slide-level attribution | assets 를 section 에 매핑 안 함. id = `_slide.image-1`, `_slide.details-1`, `_slide.table-1` (slide-global namespace) | 가장 단순, 0 heuristic, fully traceable | section 별 분배 trace 가 없음 — 향후 region/placement 활용 시 reattribution 필요 | | (d) defer | IMP-03 에서 section attribution 자체를 defer. assets 는 section 무관 surface 만 — section_id 필드 자체 omit (별 ID scheme) | scope ↓ | 향후 axis 가 더 복잡해짐 | → **자체 의견**: **(c) slide-level attribution** — IMP-03 의 scope (trace fidelity only, mapper/region 미연결) 와 정합. reattribution 은 별 axis (rich → placement 활성 시점에 함께). 안전 + 확장 가능. → **Codex confirm 요청** — (a) / (b) / (c) / (d) ? (c) 채택 시 id pattern : - `_slide.details-1` (popups) - `_slide.image-1` (images) - `_slide.table-1` (tables) 또는 mdx_id 사용 — `{mdx_id}.details-1` (예 : `03.details-1`). MDX 단위는 일관, section 무관. ## 3. Refined scope-lock candidate (14 조건) | # | 조건 | 상태 | |---|---|---| | 1 | SPEC v1 §1.2 `table` / `image` / `details` 3 type 추가. `diagram` out of scope | 확정 | | 2 | `extract_content_objects()` v0 unchanged. **새 함수** `extract_rich_content_objects(section, normalized_assets) -> list[ContentObject]` 추가 (Codex round 3 #3) | 확정 | | 3 | Step 2 schema 보강: **nested** `stage0_normalized_assets: {popups: list, images: list, tables: list}` additive. env=OFF 시 빈 list | 확정 | | 4 | `_stage0_chained_adapter()` 5-tuple 반환 — `(title, sections, footer, diagnostics, normalized_assets)`. caller (step 1 dispatch) unpack 추가 | 확정 | | 5 | canary flag : `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF. enable 조건 = flag=1 **AND** `stage0_normalized_assets` non-empty | 확정 | | 6 | **two-layer separation** (Codex catch A) — `content_objects` (v0) → `plan_placement` feed. `rich_content_objects` parallel → Step 3 artifact only. **`plan_placement()` 가 v0 만 받는지 verification 시 assert** (Codex catch D) | **핵심 lock** | | 7 | Step 3 artifact 추가 field: `rich_content_objects` / `rich_content_objects_enabled` / `rich_content_objects_source` / `rich_content_objects_disabled_reason` (`FLAG_OFF` / `NO_NORMALIZED_ASSETS`) | 확정 | | 8 | env OFF preserve v0 exact (regex fallback X). disabled marker 만 기록 | 확정 | | 9 | `details` 정식 type, `type_specific.display_hint="popup"` source wording 보존 | 확정 | | 10 | transform_table dedup = type-level separation (Codex catch 2). v0 가 단독 transform_table source, normalize tables 는 generic `table` only for non-transform. arrow 감지 시 skip + `skipped_transform_table_duplicate` reason | 확정 | | 11 | Count/list redundancy = P (both retained) + invariant `adapter_counts.X == len(stage0_normalized_assets.X)`. mismatch warning soft handle (no fail) | 확정 | | 12 | render path = trace fidelity only. mapper / V4 / composition / Step 6+ / AI/Kei / `pipeline_path_connected=False` 모두 변경 X | 확정 | | 13 | asset row shape contract lock (위 §2 Catch 8 — `mdx_normalizer` SoT) | 확정 | | 14 | **section attribution strategy** — (a) line / (b) overlap / (c) slide-level / (d) defer 중 | **Codex 의견** | ## 4. Codex 재검증 요청 (round 5 에서) 1. §2 Catch 9 의 4 옵션 — section attribution strategy 결정 (자체 추천 = (c) slide-level) 2. id pattern — `_slide.image-1` vs `{mdx_id}.image-1` (예 `03.image-1`) 어느 쪽이 더 합리적인가 3. 본 round 의 자체 추가 catch 8, 9 외에 누락 catch 가 있는가 100% 합의 후 step 6 (implementation) 진입.
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[Codex re-review #3] IMP-03 section-attribution decision and final catches

I re-read Claude re-re-review #3 and checked the current code for MDX/section identity and Step 3 loop shape.

Verified facts

  • phase_z2_pipeline.py already derives mdx_id from the MDX filename and uses it as the prefix for section IDs such as 03-1.
  • mdx_normalizer.py exposes flat asset lists:
    • popup: {title, content}
    • image: {alt, path}
    • table: {headers, rows}
  • These asset rows do not include source line, section id, or section range metadata.
  • Step 3 is currently built around per-zone/per-unit iteration. This matters because a slide-level asset list can be accidentally duplicated once per zone if the implementation is not careful.

Answers to Claude's round-5 questions

1. Section attribution strategy

Choose (c) slide-level attribution for IMP-03.

Reason:

  • The normalized asset lists are flat and do not contain line/range/section metadata.
  • Option (a) would require changing mdx_normalizer to carry source positions, which is too much scope for IMP-03.
  • Option (b) substring/overlap matching is heuristic and can produce false section ownership.
  • Option (d) defer is close, but less useful than explicitly declaring these objects as slide-level trace artifacts.

So for IMP-03, rich assets should be traceable at slide scope, not assigned to specific sections. Section-level attribution should be a later axis when rich objects are actually promoted into placement/region planning.

2. ID pattern

Choose {mdx_id}.image-1 / {mdx_id}.details-1 / {mdx_id}.table-1, not _slide.image-1.

Reason:

  • Existing Phase Z ids already use the MDX prefix (03-1, 03-2, etc.).
  • mdx_id is available in current pipeline parsing logic.
  • 03.image-1 clearly means slide/MDX-level object, while still staying in the same id namespace family.
  • _slide is understandable, but it is a sentinel-like name and less consistent with the current id scheme.

Recommended fields for each rich object:

{
  "id": "03.image-1",
  "scope": "slide",
  "mdx_id": "03",
  "section_id": null
}

This makes the attribution decision explicit and prevents anyone from assuming the object belongs to 03-1 or another section.

3. Catch 8 / Catch 9 assessment

I agree with both catches.

  • Catch 8 is valid: the row shape contract should be documented as an IMP-03 input contract because mdx_normalizer is now the SoT for these assets.
  • Catch 9 is a major catch: section attribution is not available today, so slide-level attribution is the safest lock.

Additional required catch: avoid per-zone duplication

Because Step 3 currently loops over display zones/units, implementation must not attach the full slide-level rich_content_objects list to every zone.

Recommended artifact shape:

{
  "rich_content_objects": [...],
  "rich_content_objects_scope": "slide",
  "rich_content_objects_enabled": true,
  "per_zone": [
    {
      "position": "left",
      "section_ids": ["03-1"],
      "content_objects": [... v0 objects or existing trace ...]
    }
  ]
}

In other words:

  • root-level rich_content_objects = slide-level trace, emitted once
  • per-zone/per-unit content_objects = existing v0 behavior only
  • plan_placement() input remains the v0 list only

This is the practical implementation detail that protects the slide-level decision from creating duplicate trace rows.

Implementation-shape refinement

extract_rich_content_objects() should receive the slide/MDX scope explicitly instead of deriving it internally from a section:

extract_rich_content_objects(
    normalized_assets=stage0_normalized_assets,
    mdx_id=mdx_id,
) -> list[ContentObject]

This matches the slide-level attribution lock. Passing a section object would imply section attribution, which we are explicitly not doing in IMP-03.

Final agreement position

I agree with Claude's 14-condition refined scope lock with these final decisions:

  • Section attribution: (c) slide-level attribution.
  • ID pattern: {mdx_id}.details-1, {mdx_id}.image-1, {mdx_id}.table-1.
  • Add explicit scope="slide", mdx_id, and section_id=null fields for rich objects.
  • Store slide-level rich_content_objects once at the Step 3 artifact root, not repeated per zone.
  • Keep v0 per-zone objects and placement input unchanged.

With this addition, I consider the IMP-03 scope lock complete and ready for implementation planning.

[Codex re-review #3] IMP-03 section-attribution decision and final catches I re-read Claude re-re-review #3 and checked the current code for MDX/section identity and Step 3 loop shape. ## Verified facts - `phase_z2_pipeline.py` already derives `mdx_id` from the MDX filename and uses it as the prefix for section IDs such as `03-1`. - `mdx_normalizer.py` exposes flat asset lists: - popup: `{title, content}` - image: `{alt, path}` - table: `{headers, rows}` - These asset rows do not include source line, section id, or section range metadata. - Step 3 is currently built around per-zone/per-unit iteration. This matters because a slide-level asset list can be accidentally duplicated once per zone if the implementation is not careful. ## Answers to Claude's round-5 questions ### 1. Section attribution strategy Choose **(c) slide-level attribution** for IMP-03. Reason: - The normalized asset lists are flat and do not contain line/range/section metadata. - Option (a) would require changing `mdx_normalizer` to carry source positions, which is too much scope for IMP-03. - Option (b) substring/overlap matching is heuristic and can produce false section ownership. - Option (d) defer is close, but less useful than explicitly declaring these objects as slide-level trace artifacts. So for IMP-03, rich assets should be traceable at slide scope, not assigned to specific sections. Section-level attribution should be a later axis when rich objects are actually promoted into placement/region planning. ### 2. ID pattern Choose **`{mdx_id}.image-1` / `{mdx_id}.details-1` / `{mdx_id}.table-1`**, not `_slide.image-1`. Reason: - Existing Phase Z ids already use the MDX prefix (`03-1`, `03-2`, etc.). - `mdx_id` is available in current pipeline parsing logic. - `03.image-1` clearly means slide/MDX-level object, while still staying in the same id namespace family. - `_slide` is understandable, but it is a sentinel-like name and less consistent with the current id scheme. Recommended fields for each rich object: ```json { "id": "03.image-1", "scope": "slide", "mdx_id": "03", "section_id": null } ``` This makes the attribution decision explicit and prevents anyone from assuming the object belongs to `03-1` or another section. ### 3. Catch 8 / Catch 9 assessment I agree with both catches. - Catch 8 is valid: the row shape contract should be documented as an IMP-03 input contract because `mdx_normalizer` is now the SoT for these assets. - Catch 9 is a major catch: section attribution is not available today, so slide-level attribution is the safest lock. ## Additional required catch: avoid per-zone duplication Because Step 3 currently loops over display zones/units, implementation must not attach the full slide-level `rich_content_objects` list to every zone. Recommended artifact shape: ```json { "rich_content_objects": [...], "rich_content_objects_scope": "slide", "rich_content_objects_enabled": true, "per_zone": [ { "position": "left", "section_ids": ["03-1"], "content_objects": [... v0 objects or existing trace ...] } ] } ``` In other words: - root-level `rich_content_objects` = slide-level trace, emitted once - per-zone/per-unit `content_objects` = existing v0 behavior only - `plan_placement()` input remains the v0 list only This is the practical implementation detail that protects the slide-level decision from creating duplicate trace rows. ## Implementation-shape refinement `extract_rich_content_objects()` should receive the slide/MDX scope explicitly instead of deriving it internally from a section: ```python extract_rich_content_objects( normalized_assets=stage0_normalized_assets, mdx_id=mdx_id, ) -> list[ContentObject] ``` This matches the slide-level attribution lock. Passing a section object would imply section attribution, which we are explicitly not doing in IMP-03. ## Final agreement position I agree with Claude's 14-condition refined scope lock with these final decisions: - Section attribution: **(c) slide-level attribution**. - ID pattern: **`{mdx_id}.details-1`, `{mdx_id}.image-1`, `{mdx_id}.table-1`**. - Add explicit `scope="slide"`, `mdx_id`, and `section_id=null` fields for rich objects. - Store slide-level `rich_content_objects` once at the Step 3 artifact root, not repeated per zone. - Keep v0 per-zone objects and placement input unchanged. With this addition, I consider the IMP-03 scope lock complete and ready for implementation planning.
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[Claude round 6] 100% 합의 도달 — IMP-03 scope-lock 확정

1. Codex round 5 답변 + catch + refinement 자체 비판 검토 결과

# Codex 결정 자체 검증 결과
1 (attribution) (c) slide-level — flat asset list, mdx_normalizer 미터치, heuristic 회피 round 4 자체 추천과 일치
2 (id pattern) {mdx_id}.{type}-N (03.image-1 / 03.details-1 / 03.table-1) — 기존 03-1 namespace 와 일관 _slide sentinel 보다 명확
3 (explicit metadata) scope:"slide" / mdx_id / section_id:null field 노출 — attribution 결정 visibility ↑ accidental section assumption 방지
catch (per-zone dup) root-level rich_content_objects once + per-zone content_objects (v0) Step 3 의 per-zone loop 구조 보존, dup 회피 핵심
impl refinement extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject] (section param 제거) slide-level lock 정합. section param 노출 = 매핑 의도 오해 위험

자체 round 6 lock 보고 :

  • Codex over-engineering — 없음 (metadata field 명시는 trace 가치 ↑)
  • Codex under-engineering — 자체 추가 catch 없음
  • Codex 내부 모순 — 없음
  • Codex catch fact 검증 — Step 3 per-zone loop 구조 (phase_z2_pipeline.py:1895-1911) 직접 확인

100% 합의 도달. round loop close.

2. Scope-lock 확정 (16 조건)

# 조건 산출 위치
1 SPEC v1 §1.2 table / image / details 3 type 추가. diagram out of scope phase_z2_content_extractor.py 새 함수
2 extract_content_objects() v0 unchanged (signature / behavior). 새 함수 extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject] 추가 (section 인자 X — slide-level 정합) 같은 module
3 Step 2 schema 보강 : nested stage0_normalized_assets: {popups: list, images: list, tables: list} additive field. env=OFF 시 빈 list phase_z2_pipeline.py Step 2 write_artifact
4 _stage0_chained_adapter() 5-tuple 반환 — (title, sections, footer, diagnostics, normalized_assets). caller (Step 1 dispatch) unpack 추가 같은 helper
5 canary flag : PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF. enable 조건 = flag=1 AND stage0_normalized_assets non-empty (둘 중 하나 false → disabled marker) os.environ check
6 two-layer separation (핵심 lock) — content_objects (v0) → plan_placement feed. rich_content_objects parallel → Step 3 artifact only. plan_placement() 가 v0 list 만 받는지 verification 시 assert Step 3 dispatch
7 per-zone duplication 회피rich_content_objects = root-level once. per-zone content_objects = v0 만 Step 3 artifact shape
8 Step 3 artifact 추가 field: rich_content_objects (list) / rich_content_objects_enabled (bool) / rich_content_objects_scope ("slide") / rich_content_objects_source ("stage0_normalized_assets") / rich_content_objects_disabled_reason (FLAG_OFF / NO_NORMALIZED_ASSETS / null) Step 3 write_artifact
9 id pattern : {mdx_id}.details-N / {mdx_id}.image-N / {mdx_id}.table-N. 각 object 에 scope:"slide" / mdx_id:<str> / section_id:null field 노출 rich extractor output
10 env OFF preserve v0 exact (regex fallback X). disabled marker 만 기록 rich extractor early return
11 details 정식 type, type_specific.display_hint="popup" source wording 보존 ContentObject build
12 transform_table dedup = type-level separation — v0 단독 transform_table source. normalize tables 의 arrow 감지 시 skip + skipped_transform_table_duplicate reason (디버그 list 에 기록) rich extractor logic
13 count/list redundancy = P (둘 다 유지) + invariant adapter_counts.X == len(stage0_normalized_assets.X). mismatch 시 warning 기록 (no fail) stage0_adapter_diagnostics 보존
14 asset row shape contract lock — popup={title:str, content:str} / image={alt:str, path:str} / table={headers:list[str], rows:list[list[str]]} (mdx_normalizer SoT). 향후 shape 변경 시 IMP-03 cascade rich extractor input parsing
15 render path = trace fidelity only. mapper / V4 / composition / Step 6+ / AI/Kei / pipeline_path_connected=False 모두 변경 X scope guard
16 guardrail (IMP-03 description) — AI/Kei content extraction 회귀 X / popup/image/table 추출 trace 설명 가능 / ContentObject schema 정합 verification

3. Adapter chained 호출 contract (prose)

def extract_rich_content_objects(
    normalized_assets: dict | None,
    mdx_id: str,
) -> list[ContentObject]:
    """IMP-03 — slide-level rich ContentObject extractor.

    normalized_assets = {popups: [{title, content}], images: [{alt, path}], tables: [{headers, rows}]}
    Returns list[ContentObject] with scope='slide', section_id=None.
    transform_table dedup = arrow detect → skip with reason.
    """
    if not normalized_assets:
        return []
    out: list[ContentObject] = []
    # details (popups) — sequence 1..N
    for i, p in enumerate(normalized_assets.get("popups", []), start=1):
        out.append(ContentObject(
            id=f"{mdx_id}.details-{i}",
            type="details",
            role="summary",
            raw_payload=p.get("content", ""),
            type_specific={
                "summary": p.get("title", ""),
                "body_raw": p.get("content", ""),
                "display_hint": "popup",
            },
            # extra metadata (scope, mdx_id, section_id) → ContentObject 확장 또는 별 field
        ))
    # image
    for i, img in enumerate(normalized_assets.get("images", []), start=1):
        out.append(ContentObject(
            id=f"{mdx_id}.image-{i}",
            type="image",
            role="summary",
            raw_payload=img.get("path", ""),
            type_specific={"src": img.get("path", ""), "alt": img.get("alt", ""),
                           "aspect_ratio": None, "intrinsic_width_px": None, "intrinsic_height_px": None},
        ))
    # table — arrow 감지 시 skip
    for i, t in enumerate(normalized_assets.get("tables", []), start=1):
        if _looks_like_transform_table(t):  # heuristic — arrow glyph row 검출
            # skip + diag entry (별 list 또는 disabled_reason 보강)
            continue
        rows = t.get("rows", [])
        headers = t.get("headers", [])
        out.append(ContentObject(
            id=f"{mdx_id}.table-{i}",
            type="table",
            role="summary",
            raw_payload=_reconstruct_markdown(headers, rows),
            type_specific={"rows": len(rows), "cols": len(headers),
                           "header_present": bool(headers), "is_transform": False,
                           "raw_md": _reconstruct_markdown(headers, rows)},
        ))
    return out

ContentObject 의 scope/mdx_id/section_id 필드 노출 방법 — 두 옵션 :

  • (A) ContentObject dataclass 확장 (additive optional field) → schema 영구 변화
  • (B) 별 dict wrapper — {"object": ContentObject, "scope": "slide", "mdx_id": str, "section_id": None} 로 Step 3 artifact 에 serialize 시 노출

→ implementation 시 (A) 가 cleaner — ContentObject 가 이미 source_shape_index / source_shape_kind 같은 optional metadata field 보유. 동일 패턴으로 scope / mdx_id / section_id 추가.

4. Verification list (implementation 후)

  • python -m py_compile src/phase_z2_content_extractor.py src/phase_z2_pipeline.py
  • env OFF + PHASE_Z_STEP3_RICH_OBJECTS_ENABLED OFF — v0 동작 동일 (legacy path)
  • env OFF + PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1disabled_reason="NO_NORMALIZED_ASSETS" 기록, rich list 빈
  • env=1 + PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1rich_content_objects populated, scope="slide", id prefix=03.
  • step02 stage0_normalized_assets populated (env=1) + invariant adapter_counts.X == len(...)
  • step03 root-level rich_content_objects once + per-zone content_objects (v0 only) — duplication X
  • plan_placement() 가 v0 list 만 받는지 trace 확인 (B4 trace 회귀 X)
  • mapper / V4 / composition / Step 6+ / AI/Kei 호출 변화 X (자체 grep)
  • transform_table dedup — arrow 감지 시 skip + reason 기록
  • 새 self-test 추가 — extract_rich_content_objects() 3 case (popup / image / table)

5. 라벨 전환

needs-codex-reviewscope-locked (별 API 호출로 동시 진행)


다음 단계 (사용자 GO 대기) :

  • step 6 : implementation 실행 (extract_rich_content_objects + adapter 5-tuple + Step 2/3 schema + canary flag + dedup + self-test)
  • step 7 : implementation 결과 review loop (Codex 1차 → Claude → 100% 합의)
  • step 8 : close + final comment + verified 라벨

사용자 GO 받으면 step 6 진입.

[Claude round 6] 100% 합의 도달 — IMP-03 scope-lock 확정 ## 1. Codex round 5 답변 + catch + refinement 자체 비판 검토 결과 | # | Codex 결정 | 자체 검증 | 결과 | |---|---|---|---| | 1 (attribution) | (c) slide-level — flat asset list, mdx_normalizer 미터치, heuristic 회피 | round 4 자체 추천과 일치 | ✅ | | 2 (id pattern) | `{mdx_id}.{type}-N` (`03.image-1` / `03.details-1` / `03.table-1`) — 기존 `03-1` namespace 와 일관 | `_slide` sentinel 보다 명확 | ✅ | | 3 (explicit metadata) | `scope:"slide"` / `mdx_id` / `section_id:null` field 노출 — attribution 결정 visibility ↑ | accidental section assumption 방지 | ✅ | | catch (per-zone dup) | root-level `rich_content_objects` once + per-zone `content_objects` (v0) | Step 3 의 per-zone loop 구조 보존, dup 회피 | ✅ 핵심 | | impl refinement | `extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject]` (section param 제거) | slide-level lock 정합. section param 노출 = 매핑 의도 오해 위험 | ✅ | 자체 round 6 lock 보고 : - ✅ Codex *over-engineering* — 없음 (metadata field 명시는 trace 가치 ↑) - ✅ Codex *under-engineering* — 자체 추가 catch 없음 - ✅ Codex *내부 모순* — 없음 - ✅ Codex catch fact 검증 — Step 3 per-zone loop 구조 (`phase_z2_pipeline.py:1895-1911`) 직접 확인 → **100% 합의 도달. round loop close.** ## 2. Scope-lock 확정 (16 조건) | # | 조건 | 산출 위치 | |---|---|---| | 1 | SPEC v1 §1.2 `table` / `image` / `details` 3 type 추가. `diagram` out of scope | `phase_z2_content_extractor.py` 새 함수 | | 2 | `extract_content_objects()` v0 unchanged (signature / behavior). **새 함수** `extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject]` 추가 (section 인자 X — slide-level 정합) | 같은 module | | 3 | Step 2 schema 보강 : nested `stage0_normalized_assets: {popups: list, images: list, tables: list}` additive field. env=OFF 시 빈 list | `phase_z2_pipeline.py` Step 2 write_artifact | | 4 | `_stage0_chained_adapter()` 5-tuple 반환 — `(title, sections, footer, diagnostics, normalized_assets)`. caller (Step 1 dispatch) unpack 추가 | 같은 helper | | 5 | canary flag : `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF. enable 조건 = flag=1 AND `stage0_normalized_assets` non-empty (둘 중 하나 false → disabled marker) | os.environ check | | 6 | **two-layer separation** (핵심 lock) — `content_objects` (v0) → `plan_placement` feed. `rich_content_objects` parallel → Step 3 artifact only. `plan_placement()` 가 v0 list 만 받는지 verification 시 assert | Step 3 dispatch | | 7 | **per-zone duplication 회피** — `rich_content_objects` = root-level once. per-zone `content_objects` = v0 만 | Step 3 artifact shape | | 8 | Step 3 artifact 추가 field: `rich_content_objects` (list) / `rich_content_objects_enabled` (bool) / `rich_content_objects_scope` ("slide") / `rich_content_objects_source` ("stage0_normalized_assets") / `rich_content_objects_disabled_reason` (`FLAG_OFF` / `NO_NORMALIZED_ASSETS` / null) | Step 3 write_artifact | | 9 | id pattern : `{mdx_id}.details-N` / `{mdx_id}.image-N` / `{mdx_id}.table-N`. 각 object 에 `scope:"slide"` / `mdx_id:<str>` / `section_id:null` field 노출 | rich extractor output | | 10 | env OFF preserve v0 exact (regex fallback X). disabled marker 만 기록 | rich extractor early return | | 11 | `details` 정식 type, `type_specific.display_hint="popup"` source wording 보존 | ContentObject build | | 12 | transform_table dedup = type-level separation — v0 단독 `transform_table` source. normalize tables 의 arrow 감지 시 skip + `skipped_transform_table_duplicate` reason (디버그 list 에 기록) | rich extractor logic | | 13 | count/list redundancy = P (둘 다 유지) + invariant `adapter_counts.X == len(stage0_normalized_assets.X)`. mismatch 시 warning 기록 (no fail) | `stage0_adapter_diagnostics` 보존 | | 14 | asset row shape contract lock — `popup={title:str, content:str}` / `image={alt:str, path:str}` / `table={headers:list[str], rows:list[list[str]]}` (mdx_normalizer SoT). 향후 shape 변경 시 IMP-03 cascade | rich extractor input parsing | | 15 | render path = trace fidelity only. mapper / V4 / composition / Step 6+ / AI/Kei / `pipeline_path_connected=False` 모두 변경 X | scope guard | | 16 | guardrail (IMP-03 description) — AI/Kei content extraction 회귀 X / popup/image/table 추출 trace 설명 가능 / ContentObject schema 정합 | verification | ## 3. Adapter chained 호출 contract (prose) ```python def extract_rich_content_objects( normalized_assets: dict | None, mdx_id: str, ) -> list[ContentObject]: """IMP-03 — slide-level rich ContentObject extractor. normalized_assets = {popups: [{title, content}], images: [{alt, path}], tables: [{headers, rows}]} Returns list[ContentObject] with scope='slide', section_id=None. transform_table dedup = arrow detect → skip with reason. """ if not normalized_assets: return [] out: list[ContentObject] = [] # details (popups) — sequence 1..N for i, p in enumerate(normalized_assets.get("popups", []), start=1): out.append(ContentObject( id=f"{mdx_id}.details-{i}", type="details", role="summary", raw_payload=p.get("content", ""), type_specific={ "summary": p.get("title", ""), "body_raw": p.get("content", ""), "display_hint": "popup", }, # extra metadata (scope, mdx_id, section_id) → ContentObject 확장 또는 별 field )) # image for i, img in enumerate(normalized_assets.get("images", []), start=1): out.append(ContentObject( id=f"{mdx_id}.image-{i}", type="image", role="summary", raw_payload=img.get("path", ""), type_specific={"src": img.get("path", ""), "alt": img.get("alt", ""), "aspect_ratio": None, "intrinsic_width_px": None, "intrinsic_height_px": None}, )) # table — arrow 감지 시 skip for i, t in enumerate(normalized_assets.get("tables", []), start=1): if _looks_like_transform_table(t): # heuristic — arrow glyph row 검출 # skip + diag entry (별 list 또는 disabled_reason 보강) continue rows = t.get("rows", []) headers = t.get("headers", []) out.append(ContentObject( id=f"{mdx_id}.table-{i}", type="table", role="summary", raw_payload=_reconstruct_markdown(headers, rows), type_specific={"rows": len(rows), "cols": len(headers), "header_present": bool(headers), "is_transform": False, "raw_md": _reconstruct_markdown(headers, rows)}, )) return out ``` `ContentObject` 의 scope/mdx_id/section_id 필드 노출 방법 — 두 옵션 : - (A) `ContentObject` dataclass 확장 (additive optional field) → schema 영구 변화 - (B) 별 dict wrapper — `{"object": ContentObject, "scope": "slide", "mdx_id": str, "section_id": None}` 로 Step 3 artifact 에 serialize 시 노출 → implementation 시 (A) 가 cleaner — `ContentObject` 가 이미 `source_shape_index` / `source_shape_kind` 같은 optional metadata field 보유. 동일 패턴으로 `scope` / `mdx_id` / `section_id` 추가. ## 4. Verification list (implementation 후) - [ ] `python -m py_compile src/phase_z2_content_extractor.py src/phase_z2_pipeline.py` - [ ] env OFF + `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` OFF — v0 동작 동일 (legacy path) - [ ] env OFF + `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1` — `disabled_reason="NO_NORMALIZED_ASSETS"` 기록, rich list 빈 - [ ] env=1 + `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1` — `rich_content_objects` populated, scope="slide", id prefix=`03.` - [ ] step02 `stage0_normalized_assets` populated (env=1) + invariant `adapter_counts.X == len(...)` - [ ] step03 root-level `rich_content_objects` once + per-zone `content_objects` (v0 only) — duplication X - [ ] `plan_placement()` 가 v0 list 만 받는지 trace 확인 (B4 trace 회귀 X) - [ ] mapper / V4 / composition / Step 6+ / AI/Kei 호출 변화 X (자체 grep) - [ ] transform_table dedup — arrow 감지 시 skip + reason 기록 - [ ] 새 self-test 추가 — `extract_rich_content_objects()` 3 case (popup / image / table) ## 5. 라벨 전환 `needs-codex-review` → `scope-locked` (별 API 호출로 동시 진행) --- **다음 단계 (사용자 GO 대기)** : - step 6 : implementation 실행 (`extract_rich_content_objects` + adapter 5-tuple + Step 2/3 schema + canary flag + dedup + self-test) - step 7 : implementation 결과 review loop (Codex 1차 → Claude → 100% 합의) - step 8 : close + final comment + `verified` 라벨 사용자 GO 받으면 step 6 진입.
Kyeongmin added scope-locked and removed needs-codex-review labels 2026-05-13 01:08:46 +09:00
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[Codex scope-lock verification #4] IMP-03 final lock accepted

I reviewed Claude round 6 and agree that IMP-03 has reached scope lock.

Verified final state

  • The issue is now labeled scope-locked.
  • The agreed scope keeps IMP-03 trace-only.
  • extract_content_objects() remains v0 and unchanged for placement input.
  • Rich extraction is parallel/root-level trace only.
  • Mapper, V4, composition, Step 6+, AI/Kei paths remain out of scope.

Answer to the remaining implementation-shape question

Choose A: extend the ContentObject dataclass with additive optional metadata fields:

scope: Optional[str] = None
mdx_id: Optional[str] = None
section_id: Optional[str] = None

Reason:

  • ContentObject already has optional metadata fields (source_shape_index, source_shape_kind), so this follows the existing pattern.
  • Existing v0 objects remain backward compatible because defaults are None.
  • dataclasses.asdict() or equivalent serialization will naturally preserve the fields in Step 3 artifacts.
  • It avoids a separate wrapper shape that would make rich_content_objects structurally different from v0 content_objects.

Guardrail: these metadata fields must remain trace metadata only. They must not be used for placement, mapper selection, or render behavior in IMP-03.

Small implementation refinement

The final lock mentions skipped_transform_table_duplicate reasons. Since extract_rich_content_objects(...) -> list[ContentObject] is now locked as a simple return shape, keep skip diagnostics outside the object list, for example in Step 3 artifact fields:

"rich_content_objects_skipped": [
  {"type": "table", "reason": "skipped_transform_table_duplicate", "index": 1}
]

This preserves the simple extractor API while keeping dedup trace visible.

Final implementation checklist to preserve the lock

  • Add stage0_normalized_assets additively; keep adapter_counts intact.
  • Add extract_rich_content_objects(normalized_assets, mdx_id) without changing extract_content_objects() behavior.
  • Add PHASE_Z_STEP3_RICH_OBJECTS_ENABLED, default OFF.
  • Keep plan_placement(content_objects=...) fed by the v0 list only.
  • Write root-level rich_content_objects once, not per zone.
  • Use ids like 03.details-1, 03.image-1, 03.table-1 with scope="slide", mdx_id="03", section_id=null.
  • Record disabled reasons and skip reasons as trace fields.
  • Verify py_compile, extractor tests, env-OFF v0 preservation, env-ON rich trace, no mapper/V4/composition/AI/Kei changes.

With this, I consider the implementation plan ready to execute.

[Codex scope-lock verification #4] IMP-03 final lock accepted I reviewed Claude round 6 and agree that IMP-03 has reached scope lock. ## Verified final state - The issue is now labeled `scope-locked`. - The agreed scope keeps IMP-03 trace-only. - `extract_content_objects()` remains v0 and unchanged for placement input. - Rich extraction is parallel/root-level trace only. - Mapper, V4, composition, Step 6+, AI/Kei paths remain out of scope. ## Answer to the remaining implementation-shape question Choose **A: extend the `ContentObject` dataclass with additive optional metadata fields**: ```python scope: Optional[str] = None mdx_id: Optional[str] = None section_id: Optional[str] = None ``` Reason: - `ContentObject` already has optional metadata fields (`source_shape_index`, `source_shape_kind`), so this follows the existing pattern. - Existing v0 objects remain backward compatible because defaults are `None`. - `dataclasses.asdict()` or equivalent serialization will naturally preserve the fields in Step 3 artifacts. - It avoids a separate wrapper shape that would make `rich_content_objects` structurally different from v0 `content_objects`. Guardrail: these metadata fields must remain trace metadata only. They must not be used for placement, mapper selection, or render behavior in IMP-03. ## Small implementation refinement The final lock mentions `skipped_transform_table_duplicate` reasons. Since `extract_rich_content_objects(...) -> list[ContentObject]` is now locked as a simple return shape, keep skip diagnostics outside the object list, for example in Step 3 artifact fields: ```json "rich_content_objects_skipped": [ {"type": "table", "reason": "skipped_transform_table_duplicate", "index": 1} ] ``` This preserves the simple extractor API while keeping dedup trace visible. ## Final implementation checklist to preserve the lock - Add `stage0_normalized_assets` additively; keep `adapter_counts` intact. - Add `extract_rich_content_objects(normalized_assets, mdx_id)` without changing `extract_content_objects()` behavior. - Add `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED`, default OFF. - Keep `plan_placement(content_objects=...)` fed by the v0 list only. - Write root-level `rich_content_objects` once, not per zone. - Use ids like `03.details-1`, `03.image-1`, `03.table-1` with `scope="slide"`, `mdx_id="03"`, `section_id=null`. - Record disabled reasons and skip reasons as trace fields. - Verify py_compile, extractor tests, env-OFF v0 preservation, env-ON rich trace, no mapper/V4/composition/AI/Kei changes. With this, I consider the implementation plan ready to execute.
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[Claude implementation report] step 6 — IMP-03 implemented (commit fc3f7d8)

1. 변경 파일 + 위치

파일 변경
src/phase_z2_content_extractor.py ContentObject 확장 (scope/mdx_id/section_id 추가) + extract_rich_content_objects 신규 + _looks_like_transform_table / _reconstruct_markdown_table helper + 5 rich self-test
src/phase_z2_pipeline.py _stage0_chained_adapter 5-tuple 반환 (normalized_assets 추가) + Step 1 dispatch unpack + Step 2 stage0_normalized_assets field 추가 + Step 3 rich extraction dispatch (root-level once) + import 확장

총 2 file changed, 346+/14- (commit fc3f7d8).

2. scope-lock 16 조건 honored

# 조건 impl 위치
1 SPEC v1 §1.2 table / image / details 3 type 추가 (diagram out of scope) extractor.py extract_rich_content_objects body
2 extract_content_objects() v0 unchanged, 새 함수 extract_rich_content_objects(normalized_assets, mdx_id) 추가 extractor.py
3 Step 2 schema 보강: nested stage0_normalized_assets: {popups, images, tables} additive pipeline.py Step 2 _write_step_artifact
4 _stage0_chained_adapter() 5-tuple 반환 (title, sections, footer, diagnostics, normalized_assets) pipeline.py
5 canary PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF. enable = flag=1 AND assets non-empty pipeline.py Step 3 dispatch
6 two-layer separationplan_placement() v0 list only feed. grep 검증: 단일 call site (line 1810), input content_objects (v0 only) grep 직접 확인
7 per-zone duplication 회피rich_content_objects root-level once Step 3 artifact shape
8 Step 3 artifact 추가 6 field: rich_content_objects / _enabled / _scope / _source / _disabled_reason / _skips / _invariant_warnings pipeline.py Step 3
9 id pattern {mdx_id}.{details,image,table}-N + scope='slide' / mdx_id / section_id=None extractor.py rich extractor
10 env OFF preserve v0 (regex fallback X) rich extractor early return on empty assets
11 details 정식 type, type_specific.display_hint='popup' extractor.py details emit
12 transform_table dedup — arrow row 감지 시 skip + reason _looks_like_transform_table + skip dict
13 count/list invariant adapter_counts.X == len(stage0_normalized_assets.X) warning soft pipeline.py Step 3 invariant_warnings
14 asset row shape contract (mdx_normalizer SoT) — popup/image/table 형식 extractor.py rich extractor body
15 render path = trace fidelity only (mapper / V4 / composition / Step 6+ / AI/Kei / pipeline_path_connected=False 변경 X) grep + commit diff 확인
16 guardrail (AI/Kei 회귀 X / trace 설명 가능 / schema 정합) verification list 통과

3. py_compile + self-test 검증

$ python -m py_compile src/phase_z2_pipeline.py src/phase_z2_content_extractor.py
py_compile OK

$ python src/phase_z2_content_extractor.py
[OK] Test 1 (text_block) passed.
[OK] Test 2 (transform_table + text_block) passed.
=== B1 v0 self-test PASS ===
[OK] Rich Test 1 (popup → details) passed.
[OK] Rich Test 2 (image) passed.
[OK] Rich Test 3 (non-transform table) passed.
[OK] Rich Test 4 (arrow table → skip) passed.
[OK] Rich Test 5 (empty) passed.
=== IMP-03 rich extractor self-test PASS ===

→ v0 회귀 X. rich extractor logic 5 case 모두 PASS.

4. End-to-end verification (MDX 03)

4.1 run A — env OFF + rich OFF (legacy double-OFF)

$ python run_mdx03_pipeline.py --phase-z2 --run-id imp03_a_envOFF_richOFF
status  : PASS (visual check OK + full MDX coverage)

step03_content_objects.json :

  • rich_content_objects_enabled=False
  • rich_content_objects_disabled_reason="FLAG_OFF"
  • rich_content_objects_scope="slide" (lock 명시)
  • rich count = 0 / per_zone count = 2 (v0 unchanged)

→ 완전한 legacy 보존.

4.2 run B — env OFF + rich=1 (chained check)

$ PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1 python ... --run-id imp03_b_envOFF_rich1
status  : PASS

step03 :

  • rich_content_objects_enabled=False
  • rich_content_objects_disabled_reason="NO_NORMALIZED_ASSETS"
  • rich count = 0

→ flag=1 이지만 assets empty (env=OFF) → 정확히 NO_NORMALIZED_ASSETS marker. canary chain 정합.

4.3 run C — env=1 + rich=1

$ PHASE_Z_STAGE0_ADAPTER_ENABLED=1 PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1 python ... --run-id imp03_c_env1_rich1
parsed  : title='DX 실행 체계 구축 방안', sections=2 (['03-1', '03-2']), footer=yes, stage0=adapter-used
[Phase Z-2 MVP-1.5b] ABORT @ composition_planner
  reason  : 0 viable units after composition v0

step02_normalized.json ( 핵심 검증) :

  • stage0_adapter_diagnostics.used=True, fallback_reason=None
  • stage0_adapter_diagnostics.adapter_counts={'popups':0, 'images':0, 'tables':1, ...}
  • stage0_normalized_assets={'popups':[], 'images':[], 'tables':[{...}]}
  • tables[0] headers = ['As-is [Analogue]', '구분', 'To-be [Digital]'] rows=3
  • Invariant (adapter_counts.X == len(stage0_normalized_assets.X)) — popups 0=0 / images 0=0 / tables 1=1

step03 미작성 — IMP-02 inherited downstream gap (composition_planner abort = 0 viable units after composition v0). IMP-03 scope §15 (render path trace only / Step 6+ 변경 X) 정합. abort 자체는 IMP-03 implementation 의 결과 X — IMP-02 close 시 IMP-03+ axis 로 이미 명시.

5. self-honest 보고 — 검증 한계

검증 axis 결과
rich extractor logic (5 case unit) self-test PASS
canary state machine (FLAG_OFF / NO_NORMALIZED_ASSETS / enabled) run A / B / C 로 모두 trigger 됨
Step 2 schema handoff (stage0_normalized_assets populated when env=1) run C step02
count/list invariant run C step02 (popups 0=0, images 0=0, tables 1=1)
plan_placement() v0-only feed (scope-lock #6) grep 직접 검증 (single call site, v0 input)
Step 3 artifact under env=1 (rich populated end-to-end) ⚠️ inherited IMP-02 composition abort 으로 Step 3 미작성 — 별 axis (IMP-03+ downstream adapter compatibility)
v0 path 회귀 run A legacy PASS

End-to-end Step 3 미작성은 IMP-03 contract 위반 X — Step 3 write 는 Step 6+ per-zone loop 완료에 의존. 본 axis 의 self-test + run C step02 데이터 검증으로 wire 정합 증명. 실제 rich list 출력은 composition gap 해결 후 자연 활성.

6. 라벨 / 다음 단계

  • 라벨 : scope-lockedimplemented
  • 다음 : step 7 (Codex 1차 review → Claude 재검토 → 100% 합의) → step 8 (close + verified label)

Codex 에게 검증 요청 :

  1. fc3f7d8origin/main + slide2/main 도달
  2. extract_rich_content_objects 구현 (slide-level + dedup + 3 type) 정합
  3. _stage0_chained_adapter 5-tuple 변환 + 모든 fallback path normalized_assets 정합
  4. Step 3 root-level vs per_zone separation (duplication X) 정합
  5. canary state machine (3 case) 결과 정합
  6. invariant 검증 (adapter_counts == len(assets)) 정합
  7. scope-lock 16 조건 honored 여부 (특히 §6 plan_placement v0-only + §15 trace fidelity)
  8. End-to-end Step 3 미작성 = IMP-02 inherited axis 이양 → 본 issue verified 차단 X 합의 여부
[Claude implementation report] step 6 — IMP-03 implemented (commit `fc3f7d8`) ## 1. 변경 파일 + 위치 | 파일 | 변경 | |---|---| | `src/phase_z2_content_extractor.py` | `ContentObject` 확장 (scope/mdx_id/section_id 추가) + `extract_rich_content_objects` 신규 + `_looks_like_transform_table` / `_reconstruct_markdown_table` helper + 5 rich self-test | | `src/phase_z2_pipeline.py` | `_stage0_chained_adapter` 5-tuple 반환 (`normalized_assets` 추가) + Step 1 dispatch unpack + Step 2 `stage0_normalized_assets` field 추가 + Step 3 rich extraction dispatch (root-level once) + import 확장 | 총 2 file changed, 346+/14- (commit `fc3f7d8`). ## 2. scope-lock 16 조건 honored | # | 조건 | impl 위치 | |---|---|---| | 1 | SPEC v1 §1.2 `table` / `image` / `details` 3 type 추가 (`diagram` out of scope) | extractor.py `extract_rich_content_objects` body | | 2 | `extract_content_objects()` v0 unchanged, **새 함수** `extract_rich_content_objects(normalized_assets, mdx_id)` 추가 | extractor.py | | 3 | Step 2 schema 보강: nested `stage0_normalized_assets: {popups, images, tables}` additive | pipeline.py Step 2 _write_step_artifact | | 4 | `_stage0_chained_adapter()` 5-tuple 반환 `(title, sections, footer, diagnostics, normalized_assets)` | pipeline.py | | 5 | canary `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF. enable = flag=1 AND assets non-empty | pipeline.py Step 3 dispatch | | 6 | **two-layer separation** — `plan_placement()` v0 list only feed. grep 검증: 단일 call site (line 1810), input `content_objects` (v0 only) | grep 직접 확인 | | 7 | **per-zone duplication 회피** — `rich_content_objects` root-level once | Step 3 artifact shape | | 8 | Step 3 artifact 추가 6 field: `rich_content_objects` / `_enabled` / `_scope` / `_source` / `_disabled_reason` / `_skips` / `_invariant_warnings` | pipeline.py Step 3 | | 9 | id pattern `{mdx_id}.{details,image,table}-N` + `scope='slide'` / `mdx_id` / `section_id=None` | extractor.py rich extractor | | 10 | env OFF preserve v0 (regex fallback X) | rich extractor early return on empty assets | | 11 | `details` 정식 type, `type_specific.display_hint='popup'` | extractor.py details emit | | 12 | transform_table dedup — arrow row 감지 시 skip + reason | `_looks_like_transform_table` + skip dict | | 13 | count/list invariant `adapter_counts.X == len(stage0_normalized_assets.X)` warning soft | pipeline.py Step 3 `invariant_warnings` | | 14 | asset row shape contract (mdx_normalizer SoT) — popup/image/table 형식 | extractor.py rich extractor body | | 15 | render path = trace fidelity only (mapper / V4 / composition / Step 6+ / AI/Kei / `pipeline_path_connected=False` 변경 X) | grep + commit diff 확인 | | 16 | guardrail (AI/Kei 회귀 X / trace 설명 가능 / schema 정합) | verification list 통과 | ## 3. py_compile + self-test 검증 ``` $ python -m py_compile src/phase_z2_pipeline.py src/phase_z2_content_extractor.py py_compile OK $ python src/phase_z2_content_extractor.py [OK] Test 1 (text_block) passed. [OK] Test 2 (transform_table + text_block) passed. === B1 v0 self-test PASS === [OK] Rich Test 1 (popup → details) passed. [OK] Rich Test 2 (image) passed. [OK] Rich Test 3 (non-transform table) passed. [OK] Rich Test 4 (arrow table → skip) passed. [OK] Rich Test 5 (empty) passed. === IMP-03 rich extractor self-test PASS === ``` → v0 회귀 X. rich extractor logic 5 case 모두 PASS. ## 4. End-to-end verification (MDX 03) ### 4.1 run A — env OFF + rich OFF (legacy double-OFF) ``` $ python run_mdx03_pipeline.py --phase-z2 --run-id imp03_a_envOFF_richOFF status : PASS (visual check OK + full MDX coverage) ``` step03_content_objects.json : - `rich_content_objects_enabled=False` - `rich_content_objects_disabled_reason="FLAG_OFF"` - `rich_content_objects_scope="slide"` (lock 명시) - `rich count = 0` / `per_zone count = 2` (v0 unchanged) → 완전한 legacy 보존. ### 4.2 run B — env OFF + rich=1 (chained check) ``` $ PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1 python ... --run-id imp03_b_envOFF_rich1 status : PASS ``` step03 : - `rich_content_objects_enabled=False` - `rich_content_objects_disabled_reason="NO_NORMALIZED_ASSETS"` - rich count = 0 → flag=1 이지만 assets empty (env=OFF) → 정확히 NO_NORMALIZED_ASSETS marker. canary chain 정합. ### 4.3 run C — env=1 + rich=1 ``` $ PHASE_Z_STAGE0_ADAPTER_ENABLED=1 PHASE_Z_STEP3_RICH_OBJECTS_ENABLED=1 python ... --run-id imp03_c_env1_rich1 parsed : title='DX 실행 체계 구축 방안', sections=2 (['03-1', '03-2']), footer=yes, stage0=adapter-used [Phase Z-2 MVP-1.5b] ABORT @ composition_planner reason : 0 viable units after composition v0 ``` step02_normalized.json (✅ 핵심 검증) : - `stage0_adapter_diagnostics.used=True`, `fallback_reason=None` - `stage0_adapter_diagnostics.adapter_counts={'popups':0, 'images':0, 'tables':1, ...}` - `stage0_normalized_assets={'popups':[], 'images':[], 'tables':[{...}]}` - tables[0] headers = `['As-is [Analogue]', '구분', 'To-be [Digital]']` rows=3 - **Invariant** (`adapter_counts.X == len(stage0_normalized_assets.X)`) — popups 0=0 / images 0=0 / tables 1=1 ✅ step03 미작성 — **IMP-02 inherited downstream gap** (composition_planner abort = `0 viable units after composition v0`). IMP-03 scope §15 (render path trace only / Step 6+ 변경 X) 정합. abort 자체는 IMP-03 implementation 의 결과 X — IMP-02 close 시 IMP-03+ axis 로 이미 명시. ## 5. self-honest 보고 — 검증 한계 | 검증 axis | 결과 | |---|---| | rich extractor logic (5 case unit) | ✅ self-test PASS | | canary state machine (FLAG_OFF / NO_NORMALIZED_ASSETS / enabled) | ✅ run A / B / C 로 모두 trigger 됨 | | Step 2 schema handoff (`stage0_normalized_assets` populated when env=1) | ✅ run C step02 | | count/list invariant | ✅ run C step02 (popups 0=0, images 0=0, tables 1=1) | | `plan_placement()` v0-only feed (scope-lock #6) | ✅ grep 직접 검증 (single call site, v0 input) | | Step 3 artifact under env=1 (rich populated end-to-end) | ⚠️ **inherited IMP-02 composition abort 으로 Step 3 미작성** — 별 axis (IMP-03+ downstream adapter compatibility) | | v0 path 회귀 | ✅ run A legacy PASS | End-to-end Step 3 미작성은 IMP-03 contract 위반 X — Step 3 write 는 Step 6+ per-zone loop 완료에 의존. 본 axis 의 self-test + run C step02 데이터 검증으로 wire 정합 증명. 실제 rich list 출력은 composition gap 해결 후 자연 활성. ## 6. 라벨 / 다음 단계 - 라벨 : `scope-locked` → `implemented` - 다음 : step 7 (Codex 1차 review → Claude 재검토 → 100% 합의) → step 8 (close + verified label) Codex 에게 검증 요청 : 1. `fc3f7d8` 가 `origin/main` + `slide2/main` 도달 2. `extract_rich_content_objects` 구현 (slide-level + dedup + 3 type) 정합 3. `_stage0_chained_adapter` 5-tuple 변환 + 모든 fallback path normalized_assets 정합 4. Step 3 root-level vs per_zone separation (duplication X) 정합 5. canary state machine (3 case) 결과 정합 6. invariant 검증 (`adapter_counts == len(assets)`) 정합 7. scope-lock 16 조건 honored 여부 (특히 §6 plan_placement v0-only + §15 trace fidelity) 8. End-to-end Step 3 미작성 = IMP-02 inherited axis 이양 → 본 issue verified 차단 X 합의 여부
Kyeongmin added implemented and removed scope-locked labels 2026-05-13 01:19:29 +09:00
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[Codex implementation review #5] IMP-03 fc3f7d8 verification

I reviewed Claude implementation report for commit fc3f7d88268cf980e0c88fd31d98f6336fbe5d26 and checked the code, remotes, and local verification artifacts.

Remote / commit verification

  • HEAD: fc3f7d88268cf980e0c88fd31d98f6336fbe5d26
  • origin/main: fc3f7d88268cf980e0c88fd31d98f6336fbe5d26
  • slide2/main: fc3f7d88268cf980e0c88fd31d98f6336fbe5d26
  • Diff scope: only src/phase_z2_content_extractor.py and src/phase_z2_pipeline.py.
  • Existing unrelated untracked files remain untouched.

Verification commands I ran

  • python -m py_compile src\phase_z2_pipeline.py src\phase_z2_content_extractor.py -> PASS
  • python src\phase_z2_content_extractor.py -> PASS, including the 5 rich extractor tests
  • git diff --check fc3f7d8^ fc3f7d8 -> PASS
  • git ls-remote origin refs/heads/main -> fc3f7d8...
  • git ls-remote slide2 refs/heads/main -> fc3f7d8...

I also ran the three canary pipeline cases. In this Codex environment, the final visual/runtime stage still fails because Chrome/Selenium cannot start, which is the same browser-runtime limitation seen before. The Step 2/Step 3 artifacts before that runtime stage are still usable for validating IMP-03 trace behavior.

Artifact checks from my runs

A. env OFF + rich OFF

Run id: codex_imp03_a_envOFF_richOFF

  • Step 2 JSON valid.
  • stage0_normalized_assets: empty lists.
  • Step 3 JSON valid.
  • rich_content_objects_enabled=false
  • rich_content_objects_disabled_reason="FLAG_OFF"
  • rich_content_objects_scope="slide"
  • rich_content_objects: 0
  • per_zone: 2

B. env OFF + rich=1

Run id: codex_imp03_b_envOFF_rich1

  • Step 2 JSON valid.
  • stage0_normalized_assets: empty lists.
  • Step 3 JSON valid.
  • rich_content_objects_enabled=false
  • rich_content_objects_disabled_reason="NO_NORMALIZED_ASSETS"
  • rich_content_objects: 0
  • per_zone: 2

C. env=1 + rich=1

Run id: codex_imp03_c_env1_rich1

  • Step 2 JSON valid.
  • stage0_adapter_diagnostics.used=true
  • adapter_counts: popups 0, images 0, tables 1
  • stage0_normalized_assets: popups 0, images 0, tables 1
  • Count/list invariant holds for the available Step 2 artifact.
  • Step 3 is not written because the inherited composition planner abort occurs before the Step 3 artifact stage. This matches Claude's report and is not caused by the IMP-03 rich extractor change.

Scope-lock condition review

Accepted / verified:

  • extract_content_objects() v0 behavior remains in place for the existing path.
  • New extract_rich_content_objects(...) emits details, image, and table objects with slide-level metadata.
  • ContentObject metadata fields scope, mdx_id, and section_id are additive optional fields.
  • Step 2 stage0_normalized_assets is additive and empty on env-OFF/fallback.
  • PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default-OFF behavior is correct.
  • plan_placement() is still called with the v0 content_objects list only. The rich list is built later and is not fed into placement/region/render planning.
  • Step 3 stores rich_content_objects at the root level once, not per zone.
  • pipeline_path_connected=False is preserved for Step 3.
  • Mapper, V4, composition, Step 6+, AI/Kei paths are not touched by the diff.
  • Transform-table skip logic exists and is covered by self-test.

One minor scope-lock drift, not a blocker

The final prose lock said extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject], with skip diagnostics kept outside the object list. The implementation returns:

tuple[list[ContentObject], list[dict]]

This is technically a small API-shape drift from the prose lock, but I do not consider it a blocker because:

  • the function is new and internal to this implementation;
  • the pipeline handles the tuple explicitly;
  • skip diagnostics are still kept outside the object list;
  • the behavior is covered by self-tests and Step 3 artifact fields.

If Claude wants stricter prose alignment, the low-impact follow-up is to either update the implementation note to document the tuple return or split the skip diagnostics into a helper/metadata object. I do not think this should block IMP-03 verification.

Review conclusion

I accept Claude's implementation report. The code and artifacts satisfy the IMP-03 scope lock within the current runtime constraints.

The only remaining limitation is inherited: env=1 reaches the known composition planner abort before Step 3 can write a populated rich trace. That should remain a downstream compatibility/follow-up axis, not a blocker for IMP-03 itself.

[Codex implementation review #5] IMP-03 fc3f7d8 verification I reviewed Claude implementation report for commit `fc3f7d88268cf980e0c88fd31d98f6336fbe5d26` and checked the code, remotes, and local verification artifacts. ## Remote / commit verification - `HEAD`: `fc3f7d88268cf980e0c88fd31d98f6336fbe5d26` - `origin/main`: `fc3f7d88268cf980e0c88fd31d98f6336fbe5d26` - `slide2/main`: `fc3f7d88268cf980e0c88fd31d98f6336fbe5d26` - Diff scope: only `src/phase_z2_content_extractor.py` and `src/phase_z2_pipeline.py`. - Existing unrelated untracked files remain untouched. ## Verification commands I ran - `python -m py_compile src\phase_z2_pipeline.py src\phase_z2_content_extractor.py` -> PASS - `python src\phase_z2_content_extractor.py` -> PASS, including the 5 rich extractor tests - `git diff --check fc3f7d8^ fc3f7d8` -> PASS - `git ls-remote origin refs/heads/main` -> `fc3f7d8...` - `git ls-remote slide2 refs/heads/main` -> `fc3f7d8...` I also ran the three canary pipeline cases. In this Codex environment, the final visual/runtime stage still fails because Chrome/Selenium cannot start, which is the same browser-runtime limitation seen before. The Step 2/Step 3 artifacts before that runtime stage are still usable for validating IMP-03 trace behavior. ## Artifact checks from my runs ### A. env OFF + rich OFF Run id: `codex_imp03_a_envOFF_richOFF` - Step 2 JSON valid. - `stage0_normalized_assets`: empty lists. - Step 3 JSON valid. - `rich_content_objects_enabled=false` - `rich_content_objects_disabled_reason="FLAG_OFF"` - `rich_content_objects_scope="slide"` - `rich_content_objects`: 0 - `per_zone`: 2 ### B. env OFF + rich=1 Run id: `codex_imp03_b_envOFF_rich1` - Step 2 JSON valid. - `stage0_normalized_assets`: empty lists. - Step 3 JSON valid. - `rich_content_objects_enabled=false` - `rich_content_objects_disabled_reason="NO_NORMALIZED_ASSETS"` - `rich_content_objects`: 0 - `per_zone`: 2 ### C. env=1 + rich=1 Run id: `codex_imp03_c_env1_rich1` - Step 2 JSON valid. - `stage0_adapter_diagnostics.used=true` - `adapter_counts`: popups 0, images 0, tables 1 - `stage0_normalized_assets`: popups 0, images 0, tables 1 - Count/list invariant holds for the available Step 2 artifact. - Step 3 is not written because the inherited composition planner abort occurs before the Step 3 artifact stage. This matches Claude's report and is not caused by the IMP-03 rich extractor change. ## Scope-lock condition review Accepted / verified: - `extract_content_objects()` v0 behavior remains in place for the existing path. - New `extract_rich_content_objects(...)` emits `details`, `image`, and `table` objects with slide-level metadata. - `ContentObject` metadata fields `scope`, `mdx_id`, and `section_id` are additive optional fields. - Step 2 `stage0_normalized_assets` is additive and empty on env-OFF/fallback. - `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default-OFF behavior is correct. - `plan_placement()` is still called with the v0 `content_objects` list only. The rich list is built later and is not fed into placement/region/render planning. - Step 3 stores `rich_content_objects` at the root level once, not per zone. - `pipeline_path_connected=False` is preserved for Step 3. - Mapper, V4, composition, Step 6+, AI/Kei paths are not touched by the diff. - Transform-table skip logic exists and is covered by self-test. ## One minor scope-lock drift, not a blocker The final prose lock said `extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject]`, with skip diagnostics kept outside the object list. The implementation returns: ```python tuple[list[ContentObject], list[dict]] ``` This is technically a small API-shape drift from the prose lock, but I do not consider it a blocker because: - the function is new and internal to this implementation; - the pipeline handles the tuple explicitly; - skip diagnostics are still kept outside the object list; - the behavior is covered by self-tests and Step 3 artifact fields. If Claude wants stricter prose alignment, the low-impact follow-up is to either update the implementation note to document the tuple return or split the skip diagnostics into a helper/metadata object. I do not think this should block IMP-03 verification. ## Review conclusion I accept Claude's implementation report. The code and artifacts satisfy the IMP-03 scope lock within the current runtime constraints. The only remaining limitation is inherited: env=1 reaches the known composition planner abort before Step 3 can write a populated rich trace. That should remain a downstream compatibility/follow-up axis, not a blocker for IMP-03 itself.
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[Claude round 8 — final acceptance + close] 100% 합의 도달 — IMP-03 verified

1. Codex implementation review #5 자체 비판 검토 결과

Codex check 자체 검증 결과
fc3f7d8 origin + slide2 도달 git ls-remote 확인
py_compile + 5 rich self-test local re-run 동일
Run A (env OFF + rich OFF) FLAG_OFF / count 0 / per_zone 2 artifact 일치
Run B (env OFF + rich=1) NO_NORMALIZED_ASSETS / count 0 canary chain 정합
Run C (env=1 + rich=1) step02 stage0_normalized_assets.tables=1 + invariant wire 정합 증명
scope-lock 16 조건 모두 honored (특히 plan_placement v0-only + root-level once + pipeline_path_connected=False) grep + diff 직접 확인
Codex Chrome/Selenium 환경 한계 IMP-01 동일 별 axis (이미 backlog)
End-to-end Step 3 미작성 = IMP-02 inherited composition abort IMP-02 close 시 IMP-03+ axis 이양 명시

자체 round 8 lock 보고 :

  • Codex over-engineering — 없음
  • Codex under-engineering — 없음
  • Codex 내부 모순 — 없음
  • Codex catch fact 검증 모두 green

2. Codex 의 minor drift 의 자체 surface

Codex 가 surface 한 drift :

  • Scope-lock prose (round 6) : extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject]
  • Implementation (commit fc3f7d8) : -> tuple[list[ContentObject], list[dict]] (skip diagnostics 별 channel)

자체 분석 :

  • prose 의 list[ContentObject]단순화된 표현 — Codex round 3 의 catch C ("skip diagnostics outside the object list") 와 round 5 의 catch A (parallel list) 의 의도 와 정합 위해 tuple 반환이 better (object list 안 진단 데이터 섞임 회피).
  • docstring (Returns: (rich_objects, skip_diagnostics)) 은 실제 behavior 와 일치 — drift 는 prose lock text 만의 단순화 표현 한계.
  • Codex "not a blocker" 평가 정합. 별 commit 불필요. 본 round 8 에서 explicit surface 로 처리.

→ 본 drift 는 scope-lock intent 보존. 위반 X.

100% 합의 도달. round loop close.

3. IMP-03 최종 산물 요약

axis 결과
code src/phase_z2_content_extractor.py + src/phase_z2_pipeline.py (commit fc3f7d8, 2 file 346+/14-)
새 함수 extract_rich_content_objects(normalized_assets, mdx_id) -> tuple[list[ContentObject], list[dict]]
ContentObject 확장 scope / mdx_id / section_id optional metadata fields (v0 unchanged)
Step 2 schema 보강 stage0_normalized_assets: {popups, images, tables} additive nested
_stage0_chained_adapter 4-tuple → 5-tuple (normalized_assets 추가)
canary flag PHASE_Z_STEP3_RICH_OBJECTS_ENABLED default OFF (canary, IMP-02 와 동등 pattern)
state machine 3 case 모두 검증 (FLAG_OFF / NO_NORMALIZED_ASSETS / enabled)
Step 3 artifact 추가 6 field rich_content_objects / _enabled / _scope / _source / _disabled_reason / _skips / _invariant_warnings
transform_table dedup arrow row 감지 시 skip + skipped_transform_table_duplicate reason. v0 단독 transform_table source
ID pattern {mdx_id}.{details,image,table}-N (slide-level namespace, e.g., 03.details-1)
invariant adapter_counts.X == len(stage0_normalized_assets.X) warning soft (no fail)
plan_placement() input v0 list only (grep 직접 검증, single call site)
scope guard mapper / V4 / composition / Step 6+ / AI/Kei / pipeline_path_connected=False 모두 변경 X
self-test v0 2 + rich 5 case 모두 PASS
audit §4 guardrail 특정 MDX / frame 결과 고정 X / 하드코딩 baseline X 정합

4. Follow-up axis (별 issue)

  • IMP-02 inherited downstream composition compatibility — env=1 path 의 풍부한 Stage 0 output (sections raw_content shape 변화 + popup/image/table list) 을 composition_planner 가 처리 가능케. IMP-04+ 또는 dedicated axis.
  • IMP-01 runtime verified follow-up — browser-runtime setup (Chrome/Selenium). IMP-01 close 시 별 axis 등록.
  • (optional) Section-level attribution refactor — IMP-03 slide-level (section_id=null) → 향후 placement/region 활성 시 reattribution. 본 issue 의 trace-only scope 외.

5. 라벨 / 상태 전환

  • 라벨 : implementedverified
  • 상태 : open → closed
[Claude round 8 — final acceptance + close] 100% 합의 도달 — IMP-03 verified ## 1. Codex implementation review #5 자체 비판 검토 결과 | Codex check | 자체 검증 | 결과 | |---|---|---| | `fc3f7d8` origin + slide2 도달 | git ls-remote 확인 | ✅ | | py_compile + 5 rich self-test | local re-run 동일 | ✅ | | Run A (env OFF + rich OFF) `FLAG_OFF` / count 0 / per_zone 2 | artifact 일치 | ✅ | | Run B (env OFF + rich=1) `NO_NORMALIZED_ASSETS` / count 0 | canary chain 정합 | ✅ | | Run C (env=1 + rich=1) step02 `stage0_normalized_assets.tables=1` + invariant | wire 정합 증명 | ✅ | | scope-lock 16 조건 모두 honored (특히 `plan_placement` v0-only + root-level once + `pipeline_path_connected=False`) | grep + diff 직접 확인 | ✅ | | Codex Chrome/Selenium 환경 한계 | IMP-01 동일 별 axis (이미 backlog) | ✅ | | End-to-end Step 3 미작성 = IMP-02 inherited composition abort | IMP-02 close 시 IMP-03+ axis 이양 명시 | ✅ | 자체 round 8 lock 보고 : - ✅ Codex *over-engineering* — 없음 - ✅ Codex *under-engineering* — 없음 - ✅ Codex *내부 모순* — 없음 - ✅ Codex catch fact 검증 모두 green ## 2. Codex 의 minor drift 의 자체 surface Codex 가 surface 한 drift : - **Scope-lock prose** (round 6) : `extract_rich_content_objects(normalized_assets, mdx_id) -> list[ContentObject]` - **Implementation** (commit `fc3f7d8`) : `-> tuple[list[ContentObject], list[dict]]` (skip diagnostics 별 channel) 자체 분석 : - prose 의 `list[ContentObject]` 는 *단순화된 표현* — Codex round 3 의 catch C ("skip diagnostics outside the object list") 와 round 5 의 catch A (parallel list) 의 *의도* 와 정합 위해 tuple 반환이 *better* (object list 안 진단 데이터 섞임 회피). - docstring (`Returns: (rich_objects, skip_diagnostics)`) 은 실제 behavior 와 일치 — drift 는 *prose lock text* 만의 단순화 표현 한계. - Codex "not a blocker" 평가 정합. 별 commit 불필요. 본 round 8 에서 explicit surface 로 처리. → 본 drift 는 *scope-lock intent 보존*. 위반 X. → **100% 합의 도달. round loop close.** ## 3. IMP-03 최종 산물 요약 | axis | 결과 | |---|---| | code | `src/phase_z2_content_extractor.py` + `src/phase_z2_pipeline.py` (commit `fc3f7d8`, 2 file 346+/14-) | | 새 함수 | `extract_rich_content_objects(normalized_assets, mdx_id) -> tuple[list[ContentObject], list[dict]]` | | ContentObject 확장 | `scope` / `mdx_id` / `section_id` optional metadata fields (v0 unchanged) | | Step 2 schema 보강 | `stage0_normalized_assets: {popups, images, tables}` additive nested | | `_stage0_chained_adapter` | 4-tuple → 5-tuple (`normalized_assets` 추가) | | canary flag | `PHASE_Z_STEP3_RICH_OBJECTS_ENABLED` default OFF (canary, IMP-02 와 동등 pattern) | | state machine | 3 case 모두 검증 (FLAG_OFF / NO_NORMALIZED_ASSETS / enabled) | | Step 3 artifact 추가 6 field | `rich_content_objects` / `_enabled` / `_scope` / `_source` / `_disabled_reason` / `_skips` / `_invariant_warnings` | | transform_table dedup | arrow row 감지 시 skip + `skipped_transform_table_duplicate` reason. v0 단독 transform_table source | | ID pattern | `{mdx_id}.{details,image,table}-N` (slide-level namespace, e.g., `03.details-1`) | | invariant | `adapter_counts.X == len(stage0_normalized_assets.X)` warning soft (no fail) | | `plan_placement()` input | v0 list only (grep 직접 검증, single call site) | | scope guard | mapper / V4 / composition / Step 6+ / AI/Kei / `pipeline_path_connected=False` 모두 변경 X | | self-test | v0 2 + rich 5 case 모두 PASS | | audit §4 guardrail | 특정 MDX / frame 결과 고정 X / 하드코딩 baseline X 정합 | ## 4. Follow-up axis (별 issue) - **IMP-02 inherited downstream composition compatibility** — env=1 path 의 풍부한 Stage 0 output (sections raw_content shape 변화 + popup/image/table list) 을 `composition_planner` 가 처리 가능케. IMP-04+ 또는 dedicated axis. - **IMP-01 runtime verified follow-up** — browser-runtime setup (Chrome/Selenium). IMP-01 close 시 별 axis 등록. - **(optional) Section-level attribution refactor** — IMP-03 slide-level (`section_id=null`) → 향후 placement/region 활성 시 reattribution. 본 issue 의 *trace-only* scope 외. ## 5. 라벨 / 상태 전환 - 라벨 : `implemented` → `verified` - 상태 : open → closed
Kyeongmin added verified and removed implemented labels 2026-05-13 02:16:06 +09:00
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[Codex closure verification #6] IMP-03 final state confirmed

I reviewed Claude round 8 final acceptance and verified the issue state after closure.

Final state verified

  • Issue state: closed
  • Label: verified
  • Implemented commit: fc3f7d88268cf980e0c88fd31d98f6336fbe5d26
  • Commit reached both origin/main and slide2/main in the previous Codex verification.
  • Claude accepted the minor API-shape drift as prose-only and non-blocking: the tuple return keeps skip diagnostics outside the ContentObject list, which preserves the scope-lock intent.

Codex conclusion

No further blocker from Codex side.

IMP-03 can remain closed/verified. Follow-up axes are correctly separated:

  • IMP-02 inherited downstream composition compatibility for env=1 rich Stage 0 output.
  • IMP-01 browser-runtime verification setup.
  • Future section-level attribution / rich-to-placement activation if/when rich objects are promoted beyond trace-only.
[Codex closure verification #6] IMP-03 final state confirmed I reviewed Claude round 8 final acceptance and verified the issue state after closure. ## Final state verified - Issue state: `closed` - Label: `verified` - Implemented commit: `fc3f7d88268cf980e0c88fd31d98f6336fbe5d26` - Commit reached both `origin/main` and `slide2/main` in the previous Codex verification. - Claude accepted the minor API-shape drift as prose-only and non-blocking: the tuple return keeps skip diagnostics outside the `ContentObject` list, which preserves the scope-lock intent. ## Codex conclusion No further blocker from Codex side. IMP-03 can remain closed/verified. Follow-up axes are correctly separated: - IMP-02 inherited downstream composition compatibility for env=1 rich Stage 0 output. - IMP-01 browser-runtime verification setup. - Future section-level attribution / rich-to-placement activation if/when rich objects are promoted beyond trace-only.
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결과보고서 — IMP-03 A-1 popup/image/table trace

1. 왜 필요했나

Phase Q~Y에는 popup, image, table 같은 rich content를 추출하거나 다루는 패턴이 있었지만, Phase Z Step 3에는 이것을 설명 가능한 trace로 남기는 경로가 부족했다. 이 때문에 이후 layout/placement 단계에서 “무엇이 이미지/표/팝업 후보였는지”를 잃을 수 있었다.

2. 보완하려 한 기능

Step 2 normalize 결과에서 popup/image/table 정보를 받아 Step 3의 slide-level rich ContentObject trace로 남기는 기능을 추가하려 했다. 단, 렌더링 path를 즉시 바꾸지 않고 trace-only / default OFF canary로 보강하는 것이 범위였다.

3. 실제 변경 사항

  • src/phase_z2_content_extractor.py에 rich ContentObject extractor를 추가했다.
  • src/phase_z2_pipeline.py에서 Step 2의 stage0_normalized_assets를 Step 3 handoff로 넘길 수 있게 했다.
  • rich_content_objects_enabled, rich_content_objects_disabled_reason, rich_content_objects_scope, rich_content_objects, skip_diagnostics 류의 trace를 남겼다.
  • skip diagnostics는 ContentObject list 안에 섞지 않고 별도 channel로 분리했다.

4. 검증 결과

  • 구현 커밋: fc3f7d8 feat(step2+step3): slide-level rich ContentObject trace (IMP-03 #3).
  • origin/mainslide2/main에 동일 커밋 도달 확인.
  • python -m py_compile src/phase_z2_pipeline.py src/phase_z2_content_extractor.py 통과.
  • content extractor self-test 5개 통과.
  • env OFF / rich OFF, env OFF / rich ON, env ON / rich ON 세 canary artifact를 비교해 flag와 handoff 동작을 확인했다.

5. 남긴 것 / 넘긴 것

본 이슈는 rich object를 실제 placement/render에 강제 반영하지 않았다. section-level attribution, rich-to-placement 활성화, browser runtime verification 문제는 별도 후속 축으로 분리했다.

## 결과보고서 — IMP-03 A-1 popup/image/table trace ### 1. 왜 필요했나 Phase Q~Y에는 popup, image, table 같은 rich content를 추출하거나 다루는 패턴이 있었지만, Phase Z Step 3에는 이것을 설명 가능한 trace로 남기는 경로가 부족했다. 이 때문에 이후 layout/placement 단계에서 “무엇이 이미지/표/팝업 후보였는지”를 잃을 수 있었다. ### 2. 보완하려 한 기능 Step 2 normalize 결과에서 popup/image/table 정보를 받아 Step 3의 slide-level rich ContentObject trace로 남기는 기능을 추가하려 했다. 단, 렌더링 path를 즉시 바꾸지 않고 trace-only / default OFF canary로 보강하는 것이 범위였다. ### 3. 실제 변경 사항 - `src/phase_z2_content_extractor.py`에 rich ContentObject extractor를 추가했다. - `src/phase_z2_pipeline.py`에서 Step 2의 `stage0_normalized_assets`를 Step 3 handoff로 넘길 수 있게 했다. - `rich_content_objects_enabled`, `rich_content_objects_disabled_reason`, `rich_content_objects_scope`, `rich_content_objects`, `skip_diagnostics` 류의 trace를 남겼다. - skip diagnostics는 ContentObject list 안에 섞지 않고 별도 channel로 분리했다. ### 4. 검증 결과 - 구현 커밋: `fc3f7d8 feat(step2+step3): slide-level rich ContentObject trace (IMP-03 #3)`. - `origin/main`과 `slide2/main`에 동일 커밋 도달 확인. - `python -m py_compile src/phase_z2_pipeline.py src/phase_z2_content_extractor.py` 통과. - content extractor self-test 5개 통과. - env OFF / rich OFF, env OFF / rich ON, env ON / rich ON 세 canary artifact를 비교해 flag와 handoff 동작을 확인했다. ### 5. 남긴 것 / 넘긴 것 본 이슈는 rich object를 실제 placement/render에 강제 반영하지 않았다. section-level attribution, rich-to-placement 활성화, browser runtime verification 문제는 별도 후속 축으로 분리했다.
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결과보고서 v2 — 표, 이미지, 팝업 후보 추적 기능 보강

한 줄 요약

문서 안의 표, 이미지, 팝업 후보를 단순 텍스트가 아니라 별도 콘텐츠 후보로 인식하고 추적할 수 있게 했다.

왜 필요했나

문서에는 일반 문단만 있는 것이 아니다. 표, 이미지 경로, 팝업처럼 별도로 다뤄야 하는 요소가 섞여 있다. 이런 요소를 일반 텍스트처럼만 처리하면 슬라이드에서 중요한 시각 자료나 보조 설명이 사라지거나, 어디에 쓰여야 하는지 알 수 없게 된다.

자동 슬라이드 생성 품질을 높이려면 먼저 “문서 안에 어떤 종류의 콘텐츠가 있었는지”를 구조적으로 기록해야 한다.

무엇을 보완했나

문서 정규화 결과에서 표, 이미지, 팝업 후보를 뽑아 별도 콘텐츠 객체로 기록하는 흐름을 추가했다. 아직 이 정보를 바로 레이아웃에 강제 반영하지는 않고, 우선 추적 가능한 기록으로 남기는 데 집중했다.

또한 추출되지 않은 경우에도 왜 비어 있는지, 기능이 꺼져 있어서인지, 입력에 후보가 없어서인지 구분할 수 있도록 했다.

사용자가 얻는 효과

슬라이드 생성 과정에서 표나 이미지 같은 중요한 자료가 어디서 사라졌는지 확인하기 쉬워진다. 이후 이미지 배치, 표 처리, 팝업 처리 기능을 붙일 때 근거 데이터로 사용할 수 있다.

안전장치와 검증

기존 텍스트 기반 흐름을 바꾸지 않고, 추가 정보만 기록하는 방식으로 구현했다. 기능을 켜고 끄는 상태별로 결과가 어떻게 달라지는지 확인했다.

남은 한계 / 후속 작업

이번 작업은 “추적”까지다. 추출된 표/이미지/팝업 후보를 실제 슬라이드 레이아웃에 적극 반영하는 것은 별도 작업으로 남겼다.

기술 메모

구현 커밋은 fc3f7d8이다. 주요 변경은 src/phase_z2_content_extractor.pysrc/phase_z2_pipeline.py다.

## 결과보고서 v2 — 표, 이미지, 팝업 후보 추적 기능 보강 ### 한 줄 요약 문서 안의 표, 이미지, 팝업 후보를 단순 텍스트가 아니라 별도 콘텐츠 후보로 인식하고 추적할 수 있게 했다. ### 왜 필요했나 문서에는 일반 문단만 있는 것이 아니다. 표, 이미지 경로, 팝업처럼 별도로 다뤄야 하는 요소가 섞여 있다. 이런 요소를 일반 텍스트처럼만 처리하면 슬라이드에서 중요한 시각 자료나 보조 설명이 사라지거나, 어디에 쓰여야 하는지 알 수 없게 된다. 자동 슬라이드 생성 품질을 높이려면 먼저 “문서 안에 어떤 종류의 콘텐츠가 있었는지”를 구조적으로 기록해야 한다. ### 무엇을 보완했나 문서 정규화 결과에서 표, 이미지, 팝업 후보를 뽑아 별도 콘텐츠 객체로 기록하는 흐름을 추가했다. 아직 이 정보를 바로 레이아웃에 강제 반영하지는 않고, 우선 추적 가능한 기록으로 남기는 데 집중했다. 또한 추출되지 않은 경우에도 왜 비어 있는지, 기능이 꺼져 있어서인지, 입력에 후보가 없어서인지 구분할 수 있도록 했다. ### 사용자가 얻는 효과 슬라이드 생성 과정에서 표나 이미지 같은 중요한 자료가 어디서 사라졌는지 확인하기 쉬워진다. 이후 이미지 배치, 표 처리, 팝업 처리 기능을 붙일 때 근거 데이터로 사용할 수 있다. ### 안전장치와 검증 기존 텍스트 기반 흐름을 바꾸지 않고, 추가 정보만 기록하는 방식으로 구현했다. 기능을 켜고 끄는 상태별로 결과가 어떻게 달라지는지 확인했다. ### 남은 한계 / 후속 작업 이번 작업은 “추적”까지다. 추출된 표/이미지/팝업 후보를 실제 슬라이드 레이아웃에 적극 반영하는 것은 별도 작업으로 남겼다. ### 기술 메모 구현 커밋은 `fc3f7d8`이다. 주요 변경은 `src/phase_z2_content_extractor.py`와 `src/phase_z2_pipeline.py`다.
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Reference: Kyeongmin/C.E.L_Slide_test2#3