Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· Developer Tools
Agent Guardrails
Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. B...
skill openclawclawhub Free
Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. B...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- CHANGELOG.md, CLAUDE_CODE_INSTALL.md, GITHUB_TOPICS_GUIDE.md, PUBLISHING.md, PUBLISH_NOW.sh, README.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- olmmlo-cmd
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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
Code hooks (git pre-commit, pre/post-creation checks) β 100% reliable Architectural constraints (registries, import enforcement) β 95% reliable Self-verification loops (agent checks own work) β 80% reliable Prompt rules (AGENTS.md, system prompts) β 60-70% reliable Markdown rules β 40-50% reliable, degrades with context length
Scripts
ScriptWhen to RunWhat It Doesinstall.shOnce per projectInstalls hooks and scaffoldingpre-create-check.shBefore creating new .py filesLists existing modules/functions to prevent reimplementationpost-create-validate.shAfter creating/editing .py filesDetects duplicates, missing imports, bypass patternscheck-secrets.shBefore commits / on demandScans for hardcoded tokens, keys, passwordscreate-deployment-check.shWhen setting up deployment verificationCreates .deployment-check.sh, checklist, and git hook templateinstall-skill-feedback-loop.shWhen setting up skill update automationCreates detection, auto-commit, and git hook for skill updates
Assets
AssetPurposepre-commit-hookReady-to-install git hook blocking bypass patterns and secretsregistry-template.pyTemplate __init__.py for project module registries
References
FileContentsenforcement-research.mdResearch on why code > prompts for enforcementagents-md-template.mdTemplate AGENTS.md with mechanical enforcement rulesdeployment-verification-guide.mdFull guide on preventing deployment gapsskill-update-feedback.mdMeta-enforcement: automatic skill update feedback loopSKILL_CN.mdChinese translation of this document
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: 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.
δΈζζζ‘£ / Chinese Documentation
See references/SKILL_CN.md for the full Chinese translation of this skill.
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 β 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 β write a hook that blocks it. Corollary: If an agent keeps forgetting integration, don't remind it β make it mechanically verify before commit.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
5 Docs1 Scripts
- CHANGELOG.md
- CLAUDE_CODE_INSTALL.md
- GITHUB_TOPICS_GUIDE.md
- PUBLISHING.md
- README.md
- PUBLISH_NOW.sh