Geometry Certificate Audit Implementation Plan

For agentic workers: REQUIRED SUB-SKILL: Use superpowers:test-driven-development for every behavior change and superpowers:verification-before-completion before any success claim.

Goal: Build and run a zero-training, label-blind audit of geometry-certified context observations before changing or training the production scene-state model.

Architecture: A pure certificate builder consumes only context RGB and calibrated cameras. A separate post-hoc evaluator loads context depth after certificate serialization, scores geometric correctness, executes matched-coverage and shuffled controls, and writes immutable JSON plus a Chinese-first Markdown report.

Tech Stack: Python 3.11, PyTorch 2.11/CUDA 12.8, Kornia 0.8 LoFTR, NumPy, Pillow, pytest, Ruff, YAML, JSON.

Global Constraints

• Preserve V5, V6a, V6a.1, the fixed renderer, and every prior output.
• Never expose target or context depth to certificate construction or threshold selection.
• Use only development-train scenes; do not read diagnostic-test or final-holdout data.
• Freeze seed 17 and every threshold in the design before post-hoc label scoring.
• Refuse to overwrite an existing audit directory or certificate artifact.
• This directory has no Git repository; do not manufacture commit history.

Task 1: Geometry primitives and certificate contract

Files: - Create: src/mcss/geometry_certificates.py - Test: tests/test_geometry_certificates.py

• [ ] Write failing tests for DLT triangulation, cheirality, reprojection, reciprocal matches, cycle rejection, and immutable certificate serialization.
• [ ] Run the focused tests and confirm failure because the module is absent.
• [ ] Implement the smallest pure functions needed by the tests.
• [ ] Re-run the focused tests and require all to pass.

Task 2: Label-blind proposer and certificate builder

Files: - Modify: src/mcss/geometry_certificates.py - Test: tests/test_geometry_certificates.py

• [ ] Write failing tests that a translated synthetic camera triplet recovers known 3D points, view permutation preserves sorted 3D certificates, and shuffled cameras fail certification.
• [ ] Implement frozen LoFTR pair proposals, epipolar distance, reciprocal/cycle checks, and multi-view geometric certification without any label argument.
• [ ] Run focused tests and require all to pass.

Task 3: Post-hoc scorer, frozen runner, and report

Files: - Create: src/mcss/certificate_audit.py - Create: scripts/run_geometry_certificate_audit.py - Create: configs/hypersim_geometry_certificate_audit.yaml - Test: tests/test_certificate_audit.py

• [ ] Write failing tests for deterministic hash-window selection, label separation, decision rules, matched-coverage control, overwrite refusal, and Markdown rendering.
• [ ] Implement YAML parsing, manifest context loading, certificate-first serialization, depth-only-after-write evaluation, controls, aggregation, hashes, and terminal report.
• [ ] Run focused tests and require all to pass.

Task 4: Static and real-data execution

Files: - Runtime only: outputs/geometry_certificate_audit_v1/** - Create terminal report: outputs/geometry_certificate_audit_v1/REPORT.md

• [ ] Run full pytest, Ruff, and compileall.
• [ ] Run a small deterministic smoke on one train scene and inspect stage counts and controls.
• [ ] Run exactly 32 frozen train windows and write certificates before loading depth labels.
• [ ] Apply the frozen decision rule and stop or authorize state integration without tuning.
• [ ] Verify hashes, artifact completeness, and no final/diagnostic partition access.