Show HN: Mingbird – an agent harness that makes a 2B model finish real tasks

Category: ai-ml

Tags: agent, local-first, llm, harness, small-models, ollama, benchmarking

Score: 7.8/10 (Innovation: 7, Technical: 8, Documentation: 9, Utility: 7)

Mingbird is a local-first agent harness that enables small (2–9B) open models to complete real tasks on consumer laptops with integrated graphics. It addresses harness defects rather than model limitations, using techniques like auto-debugging, safe code editing, anti-loop guards, and context management to dramatically improve task completion rates. The project includes extensive benchmarking against other harnesses, showing substantial gains, especially on 2B models.

Target audience: AI enthusiasts, developers, and researchers working with local LLMs on consumer hardware

Repository: https://github.com/Mingbird/Mingbird-agent · Python · Apache-2.0 · 21 stars

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