What problem does it solve? AI instruction setups (CLAUDE.md, settings.json load lists, system prompts) accumulate bloated rules over time — duplicates, contradictions, one-off incident patches, and vague directives that dilute model attention and degrade output quality. This Skill systematically identifies which rules earn their tokens and which are dead weight. ## Core Features & Use Cases - Five Questions scoring: Evaluates each rule against five checks (already default behavior, contradictory, duplicate, one-off patch, vague) plus a procedure-vs-outcome screen for methodology bloat. - Verdict system: Assigns each rule a verdict of CUT, RESOLVE, MERGE, EVALUATE, SHARPEN, MOVE, or KEEP, with estimated line and token savings. - Two workflows: Audit performs a full pass over every force-loaded file mapped in settings.json; QuickCheck gives a rapid verdict on a single file or pasted rule block. - Use Case: After months of appending guardrails to a CLAUDE.md, run the Audit workflow to find rules that merely echo built-in model behavior, then produce cleaned copies with the dead weight removed. ## Quick Start Ask the agent to run a BitterPillEngineering audit on your setup to score every instruction rule and report which ones to cut, merge, or keep.