Micro Agent
Open-source test-first agent for focused code-generation tasks
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What this product helps you do
Micro Agent is Builder.io's focused open-source coding agent for small, well-defined implementation tasks. In interactive mode it asks for a request, generates a test, writes code, and uses the test result as a feedback loop. It can also edit a specified file against an existing test command, prompt file, and test file, and it offers an experimental screenshot-matching mode. The project deliberately does not position itself as an end-to-end developer and requires a separate OpenAI-compatible or Anthropic model key.
Problems it solves
- Generated functions often need repeated manual test and repair cycles
- General coding agents can make broad changes with compounding errors
- Developers need a bounded agent for one file or focused unit of logic
- Small code tasks benefit from explicit executable acceptance checks
Micro Agent is a small command-line coding agent that writes or uses tests, generates code for a bounded task, and iterates against the test result. It supports interactive prompts, specified test commands and files, configurable model providers, run limits, and an experimental visual mode.
The tool is MIT licensed and free to install. Users provide their own model keys or local endpoint and remain responsible for model and infrastructure costs.
Information
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Micro Agent
Open-source test-first agent for focused code-generation tasks
Micro Agent is a small command-line coding agent that writes or uses tests, generates code for a bounded task, and iterates against the test result. It supports interactive prompts, specified test commands and files, configurable model providers, run limits, and an experimental visual mode.
The tool is MIT licensed and free to install. Users provide their own model keys or local endpoint and remain responsible for model and infrastructure costs.
What this product helps you do
Micro Agent is Builder.io's focused open-source coding agent for small, well-defined implementation tasks. In interactive mode it asks for a request, generates a test, writes code, and uses the test result as a feedback loop. It can also edit a specified file against an existing test command, prompt file, and test file, and it offers an experimental screenshot-matching mode. The project deliberately does not position itself as an end-to-end developer and requires a separate OpenAI-compatible or Anthropic model key.
Problems it solves
- Generated functions often need repeated manual test and repair cycles
- General coding agents can make broad changes with compounding errors
- Developers need a bounded agent for one file or focused unit of logic
- Small code tasks benefit from explicit executable acceptance checks
Information
You are leaving botconomy for the provider’s website. Link verified 9/22/2026.
Related AI products
Fetch.ai
Fetch.ai combines a personal AI experience, verified brand agents, Agentverse hosting and discovery, and the open uAgents Python framework so people and developers can create, connect, and operate autonomous agents.
Daizy
Daizy provides AI agents designed to enhance marketing, sales, and research efforts within financial services, automating tasks such as content generation and client engagement to increase productivity.
CrewAI
CrewAI provides an open-source framework for coordinating role-based agents in stateful flows, plus visual building, deployment, tracing, testing, and governance through its managed platform.