Don't just review the agent's code — put it through the gauntlet.

Agent Gauntlet is a configurable “feedback loop” runner for AI-assisted development workflows.

You configure which paths in your repo should trigger which validations — shell commands like tests and linters, plus AI-powered local code reviews. When files change, Gauntlet automatically runs the relevant validations and reports results.

For AI reviews, it uses the CLI tool of your choice: Gemini, Codex, Claude Code, GitHub Copilot, or Cursor.

Features

• Agent validation loop: Keep your coding agent on track with automated feedback loops. Detect problems — deterministically and/or non-deterministically — and let your agent fix and Gauntlet verify.
• Local cross-agent code reviews: Enable one AI agent to automatically request code reviews from another. For example, if Claude made changes, Gauntlet can request a review from Codex — spreading token usage across your subscriptions instead of burning through one.
  • Multiple AI review adapters have been evaluated for quality and efficiency. Claude and Codex deliver optimal review quality with superior token efficiency. For detailed metrics, see Eval Results.
• Leverage existing subscriptions: Agent Gauntlet is free and tool-agnostic, leveraging the AI CLI tools you already have installed.
• Easy CI setup: Define your CI gates once, run them locally and in GitHub.

Common Workflows

Agent Gauntlet supports three workflows, ranging from simple CLI execution to fully autonomous agentic integration:

• CLI Mode — Run checks via command line; ideal for CI pipelines and scripts.
• Assistant Mode — AI assistant runs validation loop, fixing issues iteratively.
• Agentic Mode — Autonomous agent validates and fixes in real-time via stop hook (experimental).

Example Workflow

1. Claude implements a feature
2. Agent Gauntlet reports quality issues detected by static code analysis and Codex reviewer agent
3. Claude fixes issues
4. Agent Gauntlet verifies

Comparison vs Other Tools

AI Code Review Tools

Agent Gauntlet is not a replacement for tools that provide AI pull request code reviews. It provides real-time feedback loops for autonomous coding agents, combining deterministic static checks (build, lint, test) with multi-agent AI reviews in a single pipeline. This enables agents to iterate and self-correct until all checks and reviews pass, without human intervention.

Full comparison →

Spec-Driven Workflow Tools

It is recommended to use Agent Gauntlet in conjunction with other spec-driven development tools. We believe is the ideal implementation of the validation step in any Spec → Implement → Validate workflow.

Quick Start

For basic usage and configuration guide, see the Quick Start Guide.

Documentation

• Quick Start Guide — installation, basic usage, and config layout
• User Guide — full usage details
• Configuration Reference — all configuration fields + defaults
• Stop Hook Guide — integrate with Claude Code's stop hook (experimental).
• CLI Invocation Details — how we securely invoke AI CLIs
• Feature Comparison — how Agent Gauntlet compares to other tools
• Development Guide — how to build and develop this project