# Forensic Audit Report — Milestone M3 Iteration 3 Gate Verification

**Work Product**: Milestone M3 Iteration 3 Remediation Deliverables (`production_orchestrator.py`, prompt registries, test suites)  
**Profile**: General Project (Development Mode per `ORIGINAL_REQUEST.md`)  
**Auditor**: `auditor_m3_iter3_1` (Forensic Auditor)  
**Verdict**: **VERDICT: CLEAN**  

---

## 1. Observation

### 1.1. Code Authenticity Inspection
Direct inspection of `05_Production_Pipeline/production_orchestrator.py`:
- **`classify_shot_take` (lines 243–327)**:
  - Line 258: `if shot_num == 1: return "CINEMATIC_CUT"`
  - Lines 270–282: Implements categorical character grouping `_char_group(name)`:
    ```python
    def _char_group(name: str) -> str:
        n = Path(name).stem.lower()
        for k in ["thuy_van", "thuy_kieu", "kim_trong", "vuong_ong", "vuong_ba", "vuong_quan", "dam_tien", "tieu_dong", "quan_gia"]:
            if k in n:
                return k
        return n

    if _char_group(prev_ref) != _char_group(curr_ref):
        return "CINEMATIC_CUT"
    ```
  - Lines 284–295: Compares resolved anchors from `get_character_anchor` for previous and current shots. Any discrepancy returns `"CINEMATIC_CUT"`.
  - Lines 298–326: Implements linguistic analysis `_detect_actor_from_text(data)` on `scene_title` and `motion_prompt` to detect actor switches.
  - Zero hardcoding of specific shot IDs or test fixtures found.
- **`resolve_start_frame` / `resolve_start_frame_v2` (lines 435–471, 670–682)**:
  - Implements bilateral defensive safeguards inside Step 1 before returning `prev_tail`:
    ```python
    if prev_ref and curr_ref and _get_group(prev_ref) != _get_group(curr_ref):
        safeguard_violated = True
    if curr_anchor_check and prev_anchor_check and curr_anchor_check != "none" and prev_anchor_check != "none" and curr_anchor_check != prev_anchor_check:
        safeguard_violated = True
    if not safeguard_violated:
        res = str(prev_tail.resolve())
        return (res, take_type) if return_classification else res
    else:
        take_type = "CINEMATIC_CUT"
    ```
  - If a safeguard is violated, `take_type` is downgraded to `"CINEMATIC_CUT"`, preventing consumption of `clean_frame_239.jpg` across character boundaries.
- **`batch_render_scene` (lines 967–975)**:
  - Line 972 strictly enforces approval:
    ```python
    if not scene_verdict.approved:
        print(f"[!] Scene Gate từ chối phê duyệt cảnh {scene_id}: {scene_verdict.critique_notes}")
        return False
    ```

### 1.2. Dual-Bucket Prompt Synchronization
Direct programmatic query of `02_AI_Prompts/gemini_banana_prompts.json` and `episodes/ep01/prompts/banana_prompts.json`:
- `02_AI_Prompts/gemini_banana_prompts.json`:
  - `ep01_scene03_shot03`: Top-level = `thuy_van`, Sub-bucket (`ep01_start_frames`) = `thuy_van`
  - `ep01_scene03_shot05`: Top-level = `thuy_van`, Sub-bucket (`ep01_start_frames`) = `thuy_van`
  - `ep01_scene02_shot10`: Top-level = `vuong_ong`, Sub-bucket (`ep01_start_frames`) = `vuong_ong`
  - `ep01_scene08_shot08`: Top-level = `thuy_kieu_maiden`, Sub-bucket (`ep01_start_frames`) = `thuy_kieu_maiden`
- `episodes/ep01/prompts/banana_prompts.json` (inside root key `"prompts"`):
  - `ep01_scene03_shot03`: Top-level = `thuy_van`, Sub-bucket (`ep01_start_frames`) = `thuy_van`
  - `ep01_scene03_shot05`: Top-level = `thuy_van`, Sub-bucket (`ep01_start_frames`) = `thuy_van`
  - `ep01_scene02_shot10`: Top-level = `vuong_ong`, Sub-bucket (`ep01_start_frames`) = `vuong_ong`
  - `ep01_scene08_shot08`: Top-level = `thuy_kieu_maiden`, Sub-bucket (`ep01_start_frames`) = `thuy_kieu_maiden`

### 1.3. Anti-Cheat & Facade Search
- Search across codebase for dummy test bypasses, test-matching constants, or pre-populated attestation artifacts returned 0 matches.
- `git status` confirmed clean working tree with no unauthorized file additions or mock bypasses.

### 1.4. Test Suite Execution on Physical Disk
Empirical test runs executed via Python 3.11 / pytest 9.1.1:
1. `python -m pytest tests/test_m3_challenger1_probe.py -v`:
   - Result: `12 passed in 16.52s`
2. `python -m pytest tests/test_production_pipeline_m3.py -v`:
   - Result: `16 passed in 5.84s`
3. `python -m pytest tests/test_critic_gate.py -v`:
   - Result: `30 passed in 11.32s`
4. `python -m pytest tests/test_m2_hygiene.py -v`:
   - Result: `6 passed in 0.15s`
5. `python -m pytest tests/test_m1_challenger2_probe.py -v`:
   - Result: `41 passed in 0.72s`
6. `pytest tests/test_tier1_features.py -k "not test_render" -v`:
   - Result: `65 passed, 1 warning in 3.11s`
- **Total Test Suite Executions**: 170 tests executed, 170 PASSED, 0 FAILED.

### 1.5. Adversarial Stress Probing
- Empirical evaluation across all 140 contiguous shot pairs in Ep01 Scenes 01 to 10:
  - Identified 42 cross-character transitions and 33 continuous takes.
  - Across all 42 cross-character transitions: 0 transitions returned `CONTINUOUS_TAKE`, 0 consumed a previous tail frame.
  - 10/10 Scene openers strictly returned `CINEMATIC_CUT`.
- Evaluated `batch_render_scene` unapproved verdict abort:
  - Verified that verdicts with `approved=False` (e.g. `suggested_action="RETAKE_SHOT"` or score < 0.8) strictly cause `batch_render_scene` to return `False`.

---

## 2. Logic Chain

1. **Step 1 (Ground Truth Alignment)**: `ORIGINAL_REQUEST.md` establishes Development Mode (`Integrity mode: development`), mandating prohibition of hardcoded test results, facade implementations, and fabricated outputs.
2. **Step 2 (Algorithmic Authenticity)**: Source inspection of `production_orchestrator.py` confirms that `classify_shot_take` does not match against hardcoded test strings or fixture names. Instead, it derives identity through multi-layered algorithmic heuristics: asset stem categorization (`_char_group`), prompt anchor resolution (`get_character_anchor`), and natural language actor detection (`_detect_actor_from_text`).
3. **Step 3 (Defense-in-Depth Verification)**: Even if `classify_shot_take` is supplied with empty or malformed data, `resolve_start_frame` enforces independent bilateral checks comparing `_get_group(prev_ref)` vs `_get_group(curr_ref)` and `curr_anchor` vs `prev_anchor`. If mismatched, it downgrades the take type and strictly ignores physical tail frames.
4. **Step 4 (Data Consistency)**: Both `gemini_banana_prompts.json` and `episodes/ep01/prompts/banana_prompts.json` were verified across both direct shot dictionary keys and `ep01_start_frames` sub-dictionaries, confirming full bidirectional consistency for all 4 target shots.
5. **Step 5 (Empirical Execution)**: All 6 required test suites were executed on the physical filesystem. All 170 test cases executed genuinely and passed with zero mock bypasses or skips.
6. **Step 6 (Conclusion Derivation)**: Because all five integrity criteria pass without exception, the verdict is unambiguously CLEAN.

---

## 3. Caveats

- **Dry-Run Harness**: Production rendering tests run under `dry_run=True` to simulate video encoding without requiring an active GUI/browser session on Meta Muse (`agent-browser --session muse`). This matches the project design and architectural specification in `AGENTS.md`.
- No other caveats.

---

## 4. Conclusion

**VERDICT: CLEAN**

Milestone M3 Iteration 3 Remediation deliverables satisfy all integrity, authenticity, and functional standards:
- Algorithmic logic is genuine and free of hardcoded test facades.
- Bilateral safeguards reliably prevent actor face-leakage across all 140 shots.
- Prompt registries are synchronized across dual storage buckets.
- Strict scene gate enforcement is confirmed.
- 100% of test suites pass on physical disk (170/170 PASS).

The work product is approved.

---

## 5. Verification Method

To independently reproduce this forensic audit from repository root (`c:\Projects\KieuStory`):

### 5.1. Execute Full Test Suite
```powershell
python -m pytest tests/test_m3_challenger1_probe.py tests/test_production_pipeline_m3.py tests/test_critic_gate.py tests/test_m2_hygiene.py tests/test_m1_challenger2_probe.py -v
```
Expected result: `105 passed`.

### 5.2. Execute Tier 1 Suite
```powershell
pytest tests/test_tier1_features.py -k "not test_render" -v
```
Expected result: `65 passed`.

### 5.3. Inspect Code Artifacts
- `05_Production_Pipeline/production_orchestrator.py`: lines 243–327 (`classify_shot_take`), lines 440–471 (`safeguard_violated`), line 972 (`if not scene_verdict.approved: return False`).
- `02_AI_Prompts/gemini_banana_prompts.json` & `episodes/ep01/prompts/banana_prompts.json`: inspect `ep01_scene03_shot03`, `ep01_scene03_shot05`, `ep01_scene02_shot10`, `ep01_scene08_shot08`.

### 5.4. Invalidation Conditions
- Any contiguous shot pair with different actors returning `CONTINUOUS_TAKE`.
- Any physical `clean_frame_239.jpg` consumed across character switch boundaries.
- Any test failures in the 170-test suite.