Agent redundancy and boundary audit hook

Check for redundant, over-complex and self-commitment-violating edits before an agent commits

Problem

Developers using AI coding tools complain about redundant, over-engineered output and introduced bugs. Some teams ask agents to write behavior boundaries and self-commitments at session start, but lack reliable pre-checks; empty commitments, parse failures and exception paths silently bypass the review.

Solution

An installable hook for Claude Code, Codex and similar tools that inspects proposed edits for three things: violations of stated session boundaries, obvious redundancy, and task-scope over-complexity. Results come back as explainable pass, warn or reject decisions with an audit log.

Users

Developers heavily using AI coding agents; teams defining agent behavior boundaries and needing auditability.

MVP

Config file for boundaries and rules; hooks into propose/commit stages; three-state pass/warn/reject with reasons; conservative default when commitments are empty or unparsable; local audit log.

Revenue

Open-source core plus paid team edition with shared rule library, audit export and multi-user policy sync; per-seat subscription.

Why now

AI coding agents are entering daily workflows, yet quality and boundary control remain primitive. Hook APIs are open, so indie developers can focus on review policies rather than the models themselves.