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llm-gate

llm-gate

github.com/rohitg00Testing & quality2.9k142 installsUpdated 4w ago
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About llm-gate

llm-gate is a Claude Code skill for adding LLM-based checks to tool operations. It uses prompt or agent hooks to validate actions and block calls that fail configured criteria.

Key features

  1. 01Prompt-hook quality checks
  2. 02Agent-based complex reviews
  3. 03Conditional operation matching
  4. 04Configurable models and timeouts
  5. 05Failure reasons block tool calls

Use cases

  1. 01Validate conventional commit messages
  2. 02Flag risky destructive commands
  3. 03Check file writes for exposed secrets

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/rohitg00/pro-workflow --skill llm-gate

After installing, type/llm-gatein Claude Code to confirm it loaded.

Details

From the project README

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

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