By Codagent-AI
Run and debug AI coding agent validation checks locally — execute the agent-validate suite, detect failures, diagnose logs, and gate commits or PRs until checks pass.
Activates only for explicit checks-only validation requests such as "run validator checks", "checks only", "check without reviews", or validation without AI review. Runs checks without AI reviews.
Activates only for explicit validator-aware commit requests such as "commit with validator", "run validator then commit", "run checks before commit", or "skip validator and commit". Excludes plain commit requests.
Diagnoses and explains validator behavior from runtime evidence for requests such as "why did validator fail", "explain validator behavior", "diagnose validator logs", or "what went wrong in the validator run".
Files structured GitHub bug reports for agent-validator when users ask to file, report, or open an issue for a suspected defect
Activates only for explicit full-validator requests such as "run the validator", "run the gauntlet", "run validation", or validation before commit, push, or PR creation. Includes checks and reviews, and excludes checks-only requests.
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Don't just review the agent's code — put it through the gauntlet.
Agent Validator (formerly 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, Agent Validator 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.

Agent Validator is not a replacement for AI pull request review tools. 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.
It is recommended to use Agent Validator in conjunction with spec-driven development tools. We believe it is the ideal implementation of the validation step in any Spec → Implement → Validate workflow.
gemini, codex, claude, github-copilot, cursor). See CLI Invocation Details.npm install -g agent-validator
agent-validator init
init detects your installed AI CLIs, creates .validator/config.yml with a generated root entry point and recommended local AI reviews, and installs agent plugins and skills through agent-plugin. Use --agents claude codex to preselect development agents, or --yes to skip prompts and use defaults, including global/user install scope.
After init, run the validator-setup skill in your AI agent session to auto-discover your project's tooling and populate the config. See the Skills Guide for details.
Agent Validator uses three core concepts:
src/) that Agent Validator monitors for changes.When you run Agent Validator, it detects which entry points have changed files and runs the associated checks and reviews.
Checks and reviews are defined inline in config.yml. Here's a simplified real-world example:
base_branch: main
log_dir: validator_logs
allow_parallel: true
npx claudepluginhub codagent-ai/agent-validator --plugin agent-validatorA curated set of skills for each stage of development — propose, spec, design, plan, implement, ship.
Check how well your repo supports AI coding agents.
Verify CLAUDE.md/AGENTS.md references, compile typed specs, and test the agent harness
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