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scope-laundering-detectorlisted

Use when adjacent work is called required without dependency proof, or inconvenient required work is marked optional.
ihabkhaled/AI-Psychiatry · ★ 3 · AI & Automation · score 74
Install: claude install-skill ihabkhaled/AI-Psychiatry
# Scope Laundering Detector ## 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. Require necessity evidence and the minimum necessary change before changing scope. Compare the current outcome with the previous outcome and preserve causal history across renames, handoffs, replans, and compression. 4. Produce the compact record: `why completion fails, dependency evidence, minimum change, classification`. 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 `required minimum scope or a parked optional item` and return to productive work. ## Repository runtime Apply this procedure inside the installed `.ai/` framework. Record observable