aiagentflow

# aiagentflow

A local-first CLI that orchestrates multi-agent AI workflows for software development. Give it a task — or feed it your specs, PRDs, and guidelines — and it coordinates specialized agents to architect, code, review, test, and ship automatically.

**No cloud dependency. Bring your own API keys. Your code stays on your machine.**

[![npm version](https://img.shields.io/npm/v/@aiagentflow/cli)](https://www.npmjs.com/package/@aiagentflow/cli)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)
[![Node.js](https://img.shields.io/badge/node-%3E%3D20-green)](https://nodejs.org)

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## How It Works

```
Task → Architect → Coder → Reviewer → Tester → Fixer → Ship
```

Each stage uses a specialized AI agent with tuned prompts and parameters. The loop repeats until quality thresholds pass — like a small AI engineering team running on your machine.

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## Install

```bash
npm install -g @aiagentflow/cli
```

Or with pnpm:

```bash
pnpm add -g @aiagentflow/cli
```

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## Quick Start

```bash
# 1. Initialize in your project
cd /path/to/your/project
aiagentflow init

# 2. Run a task
aiagentflow run "Add a login form with email/password validation"

# 3. Or run autonomously (no approval prompts)
aiagentflow run "Refactor the auth module" --auto

# 4. Feed context docs to agents
aiagentflow run "Add auth" --context docs/api-spec.md docs/security.md

# 5. Generate a task list from specs, then batch-run
aiagentflow plan docs/prd.md -o tasks.txt
aiagentflow run --batch tasks.txt --auto
```

The `init` wizard walks you through:
1. Auto-detect your project (language, framework, test framework, package manager)
2. Select your LLM providers (Anthropic, OpenAI, Groq, Gemini, OpenRouter, Ollama)
3. Enter API keys
4. Assign models per agent role
5. Choose a workflow mode (fast, balanced, strict)
6. Import existing docs (specs, requirements, guidelines) for auto-loading

Configuration is saved locally in `.aiagentflow/config.json`.

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## Featur