loophole-hunterlisted

# Loophole Hunter ## Core principle Semantic compliance is stronger than literal compliance. Use observable evidence and causal history; never collect or demand private chain-of-thought. The goal is correct, safe delivery with sufficient reasoning, followed by termination. ## Procedure 1. Lock the primary objective, mandatory requirements, Definition of Done, and current evidence before changing any classification or budget. 2. Identify the specific observable signal. Do not infer a violation merely from time, token use, discomfort, or a label. 3. Audit observed action history against the loophole catalog. Compare the current outcome with the previous outcome and preserve causal history across renames, handoffs, replans, and compression. 4. Produce the compact record: `Loophole -> Example -> Risk -> Detection -> Strict Rule -> Recovery`. Mark unsupported claims `not confirmed`; do not convert confidence into proof. 5. Apply one bounded corrective action with an explicit attempt or time limit and exit condition. If a default limit prevents required correctness evidence, use `$executive-override` with `reason, evidence, exact limit, narrow scope, exit condition` rather than resetting a counter. 6. Revalidate only the affected requirement or policy. Report `a finite list of evidenced loopholes and patched controls` and return to productive work. ## Repository runtime Apply this procedure inside the installed `.ai/` framework. Record observable state in the relevant JSON le