Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.
Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.
Symptom: Tokens/keys in code instead of env vars.
Enforcement:check-secrets.sh + git hook
3. Deployment Gap
Symptom: Built feature but forgot to wire it into production. Users don't receive benefit.
Example: Updated notify.py but cron still calls old version.
Enforcement:.deployment-check.sh + git hook
This is the hardest to catch because:
Code runs fine when tested manually
Agent marks task "done" after writing code
Problem only surfaces when user complains
Solution: Mechanical end-to-end verification before allowing "done."
4. Skill Update Gap (META - NEW)
Symptom: Built enforcement improvement in project but forgot to update the skill itself.
Example: Created deployment verification for Project A, but other projects don't benefit because skill wasn't updated.
Enforcement:install-skill-feedback-loop.sh → automatic detection + semi-automatic commit
This is a meta-failure mode because:
It's about enforcement improvements themselves
Without fix: improvements stay siloed
With fix: knowledge compounds automatically
Solution: Automatic detection of enforcement improvements with task creation and semi-automatic commits.
Key Principle
Don't add more markdown rules. Add mechanical enforcement.
If an agent keeps bypassing a standard, don't write a stronger rule — write a hook that blocks it.
Corollary: If an agent keeps forgetting integration, don't remind it — make it mechanically verify before commit.
