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Agent Guardrails

Stop AI agents from secretly bypassing your rules.

Rating
4.7 (176 reviews)
Downloads
45,716 downloads
Version
1.0.0

Overview

Stop AI agents from secretly bypassing your rules.

Complete Documentation

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Agent Guardrails

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

Quick Start

bash
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

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

Tools Provided

Scripts

ScriptWhen to RunWhat It Does
install.shOnce per projectInstalls hooks and scaffolding
pre-create-check.shBefore creating new .py filesLists existing modules/functions to prevent reimplementation
post-create-validate.shAfter creating/editing .py filesDetects duplicates, missing imports, bypass patterns
check-secrets.shBefore commits / on demandScans for hardcoded tokens, keys, passwords
create-deployment-check.shWhen setting up deployment verificationCreates .deployment-check.sh, checklist, and git hook template
install-skill-feedback-loop.shWhen setting up skill update automationCreates detection, auto-commit, and git hook for skill updates

Assets

AssetPurpose
pre-commit-hookReady-to-install git hook blocking bypass patterns and secrets
registry-template.pyTemplate __init__.py for project module registries

References

FileContents
enforcement-research.mdResearch on why code > prompts for enforcement
agents-md-template.mdTemplate AGENTS.md with mechanical enforcement rules
deployment-verification-guide.mdFull guide on preventing deployment gaps
skill-update-feedback.mdMeta-enforcement: automatic skill update feedback loop
SKILL_CN.mdChinese translation of this document

Usage Workflow

Setting up a new project

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

Before creating any new .py file

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

Fix any warnings before proceeding.

Setting up deployment verification

bash
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:
  • Add tests to .deployment-check.sh for your integration points
  • Document your flow in DEPLOYMENT-CHECKLIST.md
  • 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.

Installation

Terminal bash 

openclaw install agent-guardrails
Copied!

💻Code Examples

bash /path/to/agent-guardrails/scripts/install.sh

bash-pathtoagent-guardrailsscriptsinstallsh.txt
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/pre-create-check.sh /path/to/project

bash-scriptspre-create-checksh-pathtoproject.txt
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

bash-scriptspost-create-validatesh-pathtonewfilepy.txt
Fix any warnings before proceeding.

### Setting up deployment verification

Tags

#coding_agents-and-ides

Quick Info

Category Development
Model Claude 3.5
Complexity Multi-Agent
Author olmmlo-cmd
Last Updated 3/10/2026
🚀
Optimized for
Claude 3.5
🧠

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