BitterPillEngineering

To audit Claude Code instruction files for over-prompting, you can run a comprehensive workflow that evaluates each rule against a smarter-model test and five diagnostics to classify rules for cutting, merging, or keeping.

Over-prompting in settings.json occurs when instruction rules add scaffolding, ambiguity, or redundancy that degrades model performance. Auditing identifies these unnecessary complexities and estimates token savings for sharper outputs.

Yes, you can run a QuickCheck workflow to perform a targeted fast evaluation of a single instruction file or rule block, applying the same smarter-model test without scanning the entire setup.

To resolve cross-file conflicts in an AI assistant instruction set, an audit reads settings.json to detect loaded instruction sources and classifies conflicting rules into RESOLVE or MERGE categories for actionable trimming.

The smarter-model test for prompt hygiene evaluates whether a specific instruction rule is necessary by checking if a more capable model would still need that scaffolding, helping classify rules to CUT or SHARPEN.

Yes, prompt auditing supports large AI setups by reading settings.json to identify all force-loaded files, detecting cross-file conflicts, and generating a categorized report with estimated line and token savings.