Claudiomiro: Autonomous AI-Powered Development Agent

Turn complex development into a fully automated process without sacrificing production-grade code quality.

Send your prompt:

It decomposes, codes, reviews, builds, tests, and commits, autonomously, in parallel and while economizing tokens.

🔥 Use Ollama to cut token costs even further — up to 90% additional savings.

The AI Poductivity Paradox

Today’s AI coding assistants are powerful, but still fundamentally unfinished.

They generate promising first drafts, then hand the burden back to you — forcing manual review, debugging, and cleanup.

The result is a productivity paradox: tools that speed up typing but slow down everything else.

Claudiomiro breaks this cycle.

Give Claudiomiro a task and it will:

1. Break it into smaller, parallelizable tasks
2. Execute tasks simultaneously using AI agents
3. Review the code
4. Run tests and fix failures automatically
5. Create production-ready commits and pull request

Documentation

• Basic Usage Guide - Complete guide from installation to your first task
• Commands Reference - All available commands and options
• Model Configuration - AI model selection and cost optimization
• ACE - Agentic Context Engineering and Reflections in Claudiomiro

Examples

# Install
npm install -g claudiomiro

# Interactive mode
claudiomiro

# Basic usage with a prompt
claudiomiro --prompt="Add user authentication with JWT"

# Run in a specific directory
claudiomiro /path/to/project --prompt="Refactor payment processing"

# Fix failing tests automatically
claudiomiro --fix-command="npm test"

# Security audit with iterative fixes
claudiomiro --loop-fixes --prompt="Find and fix security vulnerabilities"

# Review and fix current branch before PR
claudiomiro --fix-branch

Supported AI Models

claudiomiro --claude      # Anthropic Claude
claudiomiro --codex       # OpenAI Codex
claudiomiro --gemini      # Google Gemini
claudiomiro --deep-seek   # DeepSeek
claudiomiro --glm         # GLM

• DeepSeek Setup
• GLM Setup

Smart Model Selection

Claudiomiro automatically selects the optimal model for each step to balance cost and performance:

| Model | Maps To | Use Case | |-------|---------|----------| | fast | Haiku | Simple tasks, commits, quick operations | | medium | Sonnet | Standard features, balanced performance | | hard | Opus | Complex reasoning, architectural decisions |

# Force a specific model for all steps
CLAUDIOMIRO_MODEL=fast claudiomiro --prompt="Simple README update"

# Override model for specific step
CLAUDIOMIRO_STEP5_MODEL=hard claudiomiro --prompt="Complex refactoring"

Tasks can declare their complexity with @difficulty tags in BLUEPRINT.md:

@difficulty fast    # Simple bug fix → uses Haiku
@difficulty medium  # Standard feature → uses Sonnet
@difficulty hard    # Architectural change → uses Opus

See Model Configuration Guide for details.

Multi-Repository Mode

Work across backend and frontend repositories simultaneously:

# Monorepo or separate repos - Claudiomiro auto-detects
claudiomiro --backend=./api --frontend=./web --prompt="Add user authentication with JWT"

Features:

• Automatic git configuration detection (monorepo vs separate repos)
• Scope-aware task decomposition (@scope backend|frontend|integration)
• Integration verification between codebases
• Coordinated commits across repositories

Legacy Systems Support

Claudiomiro handles complex multi-repository environments with legacy systems:

# Include legacy systems in your workflow
claudiomiro --backend=./api --legacy=./legacy-service --frontend=./web --prompt="Add feature across stack"

# Legacy backend with modern frontend
claudiomiro --legacy-backend=./legacy-api --frontend=./web --prompt="Modernize frontend integration"

# Legacy frontend with modern backend
claudiomiro --backend=./api --legacy-frontend=./legacy-ui --prompt="Update legacy UI components"

# Multiple legacy systems with migration path
claudiomiro --legacy-backend=./old-api --legacy-frontend=./old-ui --backend=./api --frontend=./web --prompt="Migrate features to new stack"

Capabilities for legacy codebases:

• Automatic legacy codebase detection and analysis
• Preservation of existing patterns and conventions
• Safe refactoring with minimal disruption
• Integration tests between modern and legacy systems
• Gradual migration support without breaking changes
• Parallel support for legacy and modern stacks

See Multi-Repository Mode Guide for details.

Local LLM Co-Pilot (Optional)

Reduce token consumption and latency by running a local LLM alongside the main AI:

# Enable local LLM co-pilot with Ollama
CLAUDIOMIRO_LOCAL_LLM=qwen2.5-coder:7b claudiomiro --prompt="Add authentication"

• Local LLM Setup Guide

Configuration

Manage persistent configuration interactively:

# Open interactive configuration manager
claudiomiro --config

# Quick set a value
claudiomiro --config CLAUDIOMIRO_LOCAL_LLM=qwen2.5-coder:7b

Configuration is stored globally and loaded automatically on startup.

Requirements

For best results, your project should have:

• Linting (ESLint, Pylint, etc.)
• Unit tests

These create a feedback loop that lets Claudiomiro validate and fix its own work.

Safety

• Max 20 cycles per task (customize with --limit=N)
• Critical bug detection before commit
• Use --push=false to review before pushing