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Agent Guardrails

Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. B...

Agent Guardrails

Mechanical enforcement for AI agent project standards. Rules in markdown are suggestions. Code hooks are laws.

Quick Start

cd your-project/
bash /path/to/agent-guardrails/scripts/install.sh

This installs the git pre-commit hook, creates a registry template, and copies check scripts into your project.

Enforcement Hierarchy

  1. Code hooks (git pre-commit, pre/post-creation checks) — 100% reliable
  2. Architectural constraints (registries, import enforcement) — 95% reliable
  3. Self-verification loops (agent checks own work) — 80% reliable
  4. Prompt rules (AGENTS.md, system prompts) — 60-70% reliable
  5. Markdown rules — 40-50% reliable, degrades with context length

Tools Provided

Scripts

| Script | When to Run | What It Does | |--------|------------|--------------| | install.sh | Once per project | Installs hooks and scaffolding | | pre-create-check.sh | Before creating new .py files | Lists existing modules/functions to prevent reimplementation | | post-create-validate.sh | After creating/editing .py files | Detects duplicates, missing imports, bypass patterns | | check-secrets.sh | Before commits / on demand | Scans for hardcoded tokens, keys, passwords | | create-deployment-check.sh | When setting up deployment verification | Creates .deployment-check.sh, checklist, and git hook template | | install-skill-feedback-loop.sh | When setting up skill update automation | Creates detection, auto-commit, and git hook for skill updates |

Assets

| Asset | Purpose | |-------|---------| | pre-commit-hook | Ready-to-install git hook blocking bypass patterns and secrets | | registry-template.py | Template __init__.py for project module registries |

References

| File | Contents | |------|----------| | enforcement-research.md | Research on why code > prompts for enforcement | | agents-md-template.md | Template AGENTS.md with mechanical enforcement rules | | deployment-verification-guide.md | Full guide on preventing deployment gaps | | skill-update-feedback.md | Meta-enforcement: automatic skill update feedback loop | | SKILL_CN.md | Chinese translation of this document |

Usage Workflow

Setting up a new project

bash scripts/install.sh /path/to/project

Before creating any new .py file

bash scripts/pre-create-check.sh /path/to/project

Review the output. If existing functions cover your needs, import them.

After creating/editing a .py file

bash scripts/post-create-validate.sh /path/to/new_file.py

Fix any warnings before proceeding.

Setting up deployment verification

bash scripts/create-deployment-check.sh /path/to/project

This creates:

  • .deployment-check.sh - Automated verification script
  • DEPLOYMENT-CHECKLIST.md - Full deployment workflow
  • .git-hooks/pre-commit-deployment - Git hook template

Then customize:

  1. Add tests to .deployment-check.sh for your integration points
  2. Document your flow in DEPLOYMENT-CHECKLIST.md
  3. Install the git hook

See references/deployment-verification-guide.md for full guide.

Adding to AGENTS.md

Copy the template from references/agents-md-template.md and adapt to your project.

中文文档 / Chinese Documentation

See references/SKILL_CN.md for the full Chinese translation of this skill.

Common Agent Failure Modes

1. Reimplementation (Bypass Pattern)

Symptom: Agent creates "quick version" instead of importing validated code. Enforcement: pre-create-check.sh + post-create-validate.sh + git hook

2. Hardcoded Secrets

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.