E575: soft-score prompt semantic plans

[Tyler-R-Kendrick]

Outcome

• connect prompt-derived partial SemanticPlanV1 features to legal choice-codec scoring
• preserve candidate legality and keep the mechanism default-off
• record the clean matched 0/1/2 E575 ladder and persist every eval arm in the dashboard API

Evidence

• weight 1: meaningful-v1 0.00 -> 0.25, fidelity 0.3417 -> 0.4250, validity 0.6050 -> 0.6550, reward 0.7095 -> 0.7345
• weight 2 regresses fidelity, validity, and reward, so the scalar ladder is closed
• strict meaning-v2 and AgentV remain zero; no checkpoint promotion or sync

Verification

• implementation commit hook: 55 tests passed
• evidence commit hook: 93 tests passed
• focused E575 persistence test passed
• ruff, version stamps, repository policy, JSON validation, and diff check passed

All processes were hard-capped at 170 seconds.

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Project	Deployment	Actions	Updated (UTC)
slm-training	Ready	Preview, Comment	Jul 20, 2026 4:09am

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Review details

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro Plus

Run ID: 48a04aa7-fd3d-4534-82d0-f15527d9ff2b

📥 Commits

Reviewing files that changed from the base of the PR and between 0095ddb and e0f31b9.

📒 Files selected for processing (13)

• docs/design/iter-e575-prompt-semantic-plan-soft-20260720.json
• docs/design/iter-e575-prompt-semantic-plan-soft-20260720.md
• docs/design/quality-experiment-matrix.md
• scripts/evaluate_model.py
• src/slm_training/harnesses/model_build/config.py
• src/slm_training/harnesses/model_build/eval_runner.py
• src/slm_training/harnesses/model_build/factory.py
• src/slm_training/models/decode_stats.py
• src/slm_training/models/template_fill.py
• src/slm_training/models/twotower.py
• src/slm_training/resources/versions.json
• tests/test_models/test_compiler_decode.py
• tests/test_web/test_control_plane.py

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch agent/e575-prompt-plan-soft

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