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.

!Claudiomiro Terminal

------

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

$3

``bash


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

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

- DeepSeek Setup
- GLM Setup

$3

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 |

`bash


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:

`markdown
@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.

$3

Work across backend and frontend repositories simultaneously:

`bash


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

$3

Claudiomiro handles complex multi-repository environments with legacy systems:

`bash


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.

$3

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

`bash


Enable local LLM co-pilot with Ollama


CLAUDIOMIRO_LOCAL_LLM=qwen2.5-coder:7b claudiomiro --prompt="Add authentication"
`

- Local LLM Setup Guide

$3

Manage persistent configuration interactively:

`bash


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