A language-agnostic blueprint for implementing automated quality enforcement that integrates with AI coding agents.
Habit Hooks simulates human habit forming by introducing deterministic reminders for predetermined short action plans. Just as humans develop good habits through consistent, repeated cues followed by small actions, this system trains AI agents to automatically respond to quality signals with specific, rehearsed fixes.
The key insight: habits form when a cue reliably triggers a practiced response. Habit Hooks provides the cue (the agent prompt marker) and the practiced response (the action guidance), creating a feedback loop that reinforces quality-focused behavior.