Llm Gate logo

Llm Gate

CommunityPopular
rohitg00
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.

Overview

Publisherrohitg00
Repositorypro-workflow
Skill namellm-gate
Stars
2.9K
Forks
286
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Llm Gate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rohitg00/pro-workflow.git /tmp/pro-workflow
mkdir -p .claude/skills
cp -r /tmp/pro-workflow/skills/llm-gate .claude/skills/llm-gate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Llm Gate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Llm Gate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Llm Gate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

json
{
  "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

json
{
  "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

json
{
  "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

json
{
  "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):

json
{
  "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

Frequently asked questions

What does the Llm Gate AI skill do?

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.

Why use Llm Gate on TypingMind?

Because you install it once and use it with any model. Llm Gate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Llm Gate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/pro-workflow/tree/main/skills/llm-gate. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Llm Gate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Llm Gate?

As many as you like. As long as a model supports skills, you can use Llm Gate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Llm Gate AI skill free?

It is published on GitHub by rohitg00. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇