agentcmd

Welcome to agentcmd

Build multi-step AI workflows with agentcmd that orchestrate Claude, OpenAI Codex, and Google Gemini to automate complex development tasks.

Think of it as GitHub Actions for AI agents. You define workflows with phases and steps, then agentcmd handles execution, monitoring, and artifact management.

What is agentcmd?

agentcmd is a platform for automating development workflows with AI agents. It consists of two components:

  1. Web Application - Visual workflow management, real-time monitoring, and run history
  2. Workflow SDK (agentcmd-workflows) - TypeScript library for defining workflows

Why agentcmd?

How It Works

What happens in each step:

  1. Write Spec - Generate feature specification using /cmd:generate-feature-spec
  2. Run Workflow - Trigger automated workflow execution via UI or CLI
    • Setup (system) - Create git branch/worktree, prepare environment
    • Execute Workflow - A user defined workflow is executed, an example would be:
      • Implement - step.agent() calls Claude/Codex with /cmd:implement-spec to write code
      • Review - step.agent() calls Claude with /cmd:review-spec-implementation to validate changes
      • Test - Run tests, type-checks, linting via step.cli()
    • Finalize (system) - Create PR with step.git(), merge, and deploy

Quick Example

Here's a complete workflow matching the diagram above:

import {
  buildSlashCommand,
  defineWorkflow,
  type CmdImplementSpecResponse,
  type CmdReviewSpecImplementationResponse,
} from "agentcmd-workflows";

export default defineWorkflow(
  {
    id: "implement-review-workflow",
    name: "Implement Review Workflow",
    description: "Implements a spec file and reviews the implementation",
    phases: [
      { id: "implement", label: "Implement" },
      { id: "review", label: "Review" },
      { id: "test", label: "Test" },
    ],
  },
  async ({ event, step }) => {
    const { workingDir, specFile } = event.data;

    await step.phase("implement", async () => {
      const response = await step.agent<CmdImplementSpecResponse>(
        "implement-spec",
        {
          agent: "claude",
          json: true,
          prompt: buildSlashCommand("/cmd:implement-spec", {
            specIdOrNameOrPath: specFile,
            format: "json",
          }),
          workingDir,
        }
      );

      return response;
    });

    await step.phase("review", async () => {
      const response = await step.agent<CmdReviewSpecImplementationResponse>(
        "review-spec-implementation",
        {
          agent: "claude",
          json: true,
          prompt: buildSlashCommand("/cmd:review-spec-implementation", {
            specIdOrNameOrPath: specFile,
            format: "json",
          }),
          workingDir,
        }
      );

      return response;
    });

    await step.phase("test", async () => {
      await step.cli("test", {
        command: "pnpm test && pnpm check-types",
        workingDir,
      });
    });
  }
);

Core Concepts

Get Started in 5 Minutes

Install agentcmd

npx agentcmd install

Start the server

npx agentcmd install
npx agentcmd start

Open the UI

open http://localhost:4100
open http://localhost:8288

Create your first project

Add your codebase, run an example workflow, and see AI agents in action.

What You'll Build

Ready to Start?

Jump into the Getting Started guide to install agentcmd and build your first workflow in under 30 minutes.

Or explore:


Need Help? Open an issue on GitHub.