llm-gate
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.
Install / Use
npx skills add rohitg00/pro-workflow --skill llm-gateInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AI & Machine LearningSupported Platforms
Tags
Our assessment of llm-gate
llm-gate scores 90/100 on our quality scale, 322nd of 970 AI & Machine Learning skills we index (top 34%).
Its SKILL.md is 3.0 KB long, well organised into 10 sections with 5 code examples: a solid amount of guidance for an agent.
With 2,876 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 8 days ago, so llm-gate is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
llm-gate compared with similar skills
All 4 of these similar skills score higher than llm-gate; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| llm-gate (this skill)by rohitg00 | 90 | 2.9k | 8d ago | SKILL.md |
| claude-memby thedotmack | 100 | 95.2k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 85.0k | today | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.3k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.2k | today | CLAUDE.md |
Frequently asked questions
- How do I install llm-gate?
- Run
npx skills add rohitg00/pro-workflow --skill llm-gate. The install tabs above show the steps for each supported agent. - Which AI agents does llm-gate work with?
- It is written for Claude Code, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is llm-gate safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is llm-gate still maintained?
- The repository was last updated 8 days ago, so llm-gate is actively maintained.
Skill content
View source on GitHubname: llm-gate description: LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.
LLM Gate
Use Claude Code's type: "prompt" hooks to create intelligent quality gates that use AI to verify operations.
Trigger
Use when:
- Setting up commit message validation
- Enforcing code conventions beyond what linters catch
- Creating smart guardrails for specific operations
How Prompt Hooks Work
Claude Code supports hooks with type: "prompt" that run a small LLM (Haiku by default) to verify conditions:
{
"PreToolUse": [{
"matcher": "Bash",
"hooks": [{
"type": "prompt",
"if": "Bash(git commit*)",
"prompt": "Check if this git commit follows conventional commit format (<type>(<scope>): <summary>). The commit command is: $ARGUMENTS. Return {\"ok\": true} if valid, {\"ok\": false, \"reason\": \"...\"} if not.",
"model": "haiku",
"timeout": 15
}]
}]
}
The hook:
- Substitutes
$ARGUMENTSwith the JSON hook input - Sends to Haiku (fast, cheap)
- Expects
{"ok": true}or{"ok": false, "reason": "..."} - If not ok → blocks the tool call with the reason
Example Gates
Conventional Commit Validator
{
"type": "prompt",
"if": "Bash(git commit*)",
"prompt": "Verify this git commit follows conventional commits: type(scope): summary. Types: feat,fix,refactor,test,docs,chore,perf,ci. Summary under 72 chars. Input: $ARGUMENTS",
"model": "haiku"
}
Destructive Command Guard
{
"type": "prompt",
"if": "Bash(rm *)",
"prompt": "Check if this rm command is safe. Flag if it uses -rf on important directories (src/, node_modules/, .git/). Input: $ARGUMENTS",
"model": "haiku"
}
API Key Leak Prevention
{
"type": "prompt",
"matcher": "Write",
"prompt": "Check if this file write contains hardcoded API keys, secrets, passwords, or tokens. Input: $ARGUMENTS. Return ok:false if secrets found.",
"model": "haiku"
}
Agent Hooks
For complex verification, use type: "agent" (runs a full agent):
{
"type": "agent",
"if": "Bash(git push*)",
"prompt": "Review all staged changes for security issues before pushing. Check for: hardcoded secrets, SQL injection, XSS vulnerabilities, exposed internal URLs.",
"model": "haiku",
"timeout": 60
}
Setup Guide
- Choose which operations to gate
- Write the prompt (keep it focused, under 100 words)
- Pick the model (haiku for speed, sonnet for accuracy)
- Set timeout (15s for prompts, 60s for agents)
- Add to hooks.json under the appropriate event
Rules
- Use Haiku for simple checks (fast, cheap)
- Use Sonnet only for complex analysis
- Keep prompts under 100 words for reliability
- Always include
ifcondition to avoid running on every tool call - Set reasonable timeouts (15s prompt, 60s agent)
- Test hooks before deploying to avoid blocking workflows
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
