claudiomiro  by samuelfaj

Autonomous AI agent for full-cycle software development

Created 3 months ago
395 stars

Top 73.0% on SourcePulse

GitHubView on GitHub
Project Summary

Summary

Claudiomiro is an autonomous AI-powered development agent designed to automate complex software development tasks from prompt to production-ready commits. It targets developers seeking to overcome the "AI productivity paradox" where AI tools speed up initial coding but slow down the overall development lifecycle by requiring extensive manual review and debugging. Claudiomiro aims to deliver production-grade code quality through a fully automated process, breaking the cycle of AI-generated drafts needing significant human intervention.

How It Works

The agent tackles development tasks by decomposing them into smaller, parallelizable sub-tasks executed by AI agents. It simultaneously processes these tasks, reviews generated code, automatically runs tests, and fixes failures. This parallel, iterative approach aims to break the cycle of AI-generated drafts requiring significant human intervention, enabling a more streamlined and efficient development workflow.

Quick Start & Requirements

Installation is done via npm: npm install -g claudiomiro. Basic usage involves running claudiomiro --prompt="Your development task". For optimal results, projects should have linting (e.g., ESLint, Pylint) and unit tests to facilitate Claudiomiro's self-validation and fixing capabilities. Optional integration with local LLMs via Ollama (e.g., CLAUDIOMIRO_LOCAL_LLM=qwen2.5-coder:7b claudiomiro --prompt="Add authentication") can significantly reduce token costs and latency.

Highlighted Details

  • Autonomous decomposition of complex tasks into parallelizable sub-tasks.
  • Simultaneous execution of tasks by AI agents with automated code review and test execution.
  • Automatic fixing of test failures and iterative security vulnerability patching (--loop-fixes).
  • Support for multiple AI models including Anthropic Claude, OpenAI Codex, Google Gemini, DeepSeek, and GLM.
  • Optional local LLM co-pilot for cost and latency reduction.

Maintenance & Community

Information regarding maintainers, community channels (Discord/Slack), or roadmap is not detailed in the provided README.

Licensing & Compatibility

The license type and compatibility notes for commercial use are not specified in the provided README.

Limitations & Caveats

Development cycles per task are capped at a maximum of 20 by default (customizable with --limit=N). Users can prevent automatic pushing to remote repositories using --push=false to allow for pre-commit review. The effectiveness relies heavily on the presence and quality of project linting and unit tests.

Health Check
Last Commit

1 week ago

Responsiveness

Inactive

Pull Requests (30d)
0
Issues (30d)
0
Star History
24 stars in the last 30 days

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