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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-gate

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

90/100

Supported Platforms

Claude Code

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.

Substance
26/30
Structure
20/20
Description
15/15
Adoption
15/20
Freshness
15/15

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.

SkillScoreStarsUpdatedFormat
llm-gate (this skill)by rohitg00902.9k8d agoSKILL.md
claude-memby thedotmack10095.2ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10085.0ktodayCLAUDE.md
headroomby headroomlabs-ai10074.3ktodayCLAUDE.md
CowAgentby zhayujie10047.2ktodayCLAUDE.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.

name: 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:

  1. Substitutes $ARGUMENTS with the JSON hook input
  2. Sends to Haiku (fast, cheap)
  3. Expects {"ok": true} or {"ok": false, "reason": "..."}
  4. 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

  1. Choose which operations to gate
  2. Write the prompt (keep it focused, under 100 words)
  3. Pick the model (haiku for speed, sonnet for accuracy)
  4. Set timeout (15s for prompts, 60s for agents)
  5. 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 if condition to avoid running on every tool call
  • Set reasonable timeouts (15s prompt, 60s agent)
  • Test hooks before deploying to avoid blocking workflows

Related Skills

View on GitHub
GitHub Stars2.9k
CategoryAI
Updated8d ago
Forks289

Languages

JavaScript

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium