verify-decoder

# /verify-decoder ## When to use - An AutoQEC round produced `delta_ler > 0` and the user wants final sign-off. - User asks to "verify this checkpoint" or "audit this round". ## Inputs - `round_dir`: path to `runs/<id>/round_N/` (must contain `checkpoint.pt` + `config.yaml`) - `env_yaml`: env used by the round (defaults to `config.yaml`'s `env_name`) ## Behavior 1. Run `python -m cli.autoqec verify <round_dir> --env <env_yaml>`. 2. Read `verification_report.json` + `training.log`. 3. LLM-reason over: - If `verdict=VERIFIED`: write one paragraph noting key confidence intervals and whether delta is within ablation threshold. Output "APPROVED". - If `verdict=SUSPICIOUS`: read training.log, the DSL config, the history of previous rounds; diagnose whether this is (a) genuine small improvement, (b) overfitting, (c) reward-hacking. Recommend next action: accept, re-run with more shots, or reject. - If `verdict=FAILED`: produce a diagnostic report matching the failure pattern (seed leak, ablation failure, negative delta). Archive into `round_N/failure_diagnosis.md`. ## Tool-use rules - Read: training.log, config.yaml, verification_report.md, previous round metrics.json files. - Bash: `python -m cli.autoqec verify ...` only. No other commands. ## Output - Short decision block: APPROVED / SUSPICIOUS_KEEP / SUSPICIOUS_REJECT / FAILED_REJECT. - Diagnostic paragraph saved to `round_N/decision.md`.