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RegRadar static demo: cited answers, impact reports, evaluation
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Impact pipeline against the gap key

Model claude-haiku-5-5; 12 circulars, every one named in company/GAP_KEY.md. Generated by python -m regradar.evaluate_impact score from eval/impact/*.json. API cost of the run: $0.65.

Measure Result
Planted gaps found, strict: the flag states the rule's key fact 11/12 = 92% [65, 99] (Wilson 95%)
Planted gaps found, lenient: a flag cites the right policy section 12/12 = 100% [76, 100]
Traps flagged as gaps (N1-N3; lower is better), strict / lenient 2/3 / 2/3
Gap or partial flags in all (share of applicable obligations) 328 (29%)
Flags matching no key row (need a person) 234
Obligations extracted / rated not applicable / not covered 1492 / 369 / 660
Items in the review queue 72
Reports failing a code check 0

Per key row (Y = found or, for N rows, flagged):

Match G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 N1 N2 N3
strict Y Y Y Y Y - Y Y Y Y Y Y Y - Y
lenient Y Y Y Y Y Y Y Y Y Y Y Y Y - Y

Matching: a gap or partial rating from the key's circular that cites the key's policy in the same section (heading number); strict also requires the finding or action to state the rule's key fact (KEY_FACT in regradar/evaluate_impact.py, taken from the key's rule text). Recall is not the whole story: the pipeline flags many obligations, and precision is not measured. The key lists what was planted, not every shortfall, so unkeyed flags are neither right nor wrong until a person reviews them; they are listed in impact_<model>.json.