GetSmallAI

GetSmallAI / SmallHarness

Public

A harness for small llms

www.smallharness.com harness llms
32
0
100% credibility
Found Apr 27, 2026 at 32 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Rust
AI Summary

SmallHarness provides a text-based interface for using small local AI models as interactive coding assistants with safe file and shell tools on Apple Silicon Macs.

How It Works

1
🔍 Find your local coding buddy

You hear about Small Harness, a simple way to get a smart helper for coding right on your Mac without needing the internet.

2
📱 Set up a local thinker

Install a free app that runs small smart models on your Mac, like one that fits your Mac mini or Studio.

3
🚀 Launch the helper

Download and start Small Harness – it warms up and shows a welcoming screen ready for your questions.

4
💻 Pick your perfect match

Choose a setup for your Mac size, and it picks the best thinker model to assist with your code.

5
💬 Ask about your files

Type questions like 'what files are here?' or 'fix this bug' – it reads, searches, and suggests safely.

6
✅ Review changes

See previews of any file edits or commands, approve the safe ones, and watch it work.

🎉 Code magic happens

Your local helper fixes code, explores projects, and boosts your work – all private and speedy on your Mac.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 32 to 32 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is SmallHarness?

SmallHarness is a Rust TUI harness for small LLMs (7B-14B) running locally on Macs, turning them into interactive coding agents with filesystem and shell tools gated by approval prompts. It swaps seamlessly between backends like Ollama, LM Studio, MLX, llama.cpp, or OpenRouter via slash commands, with hardware profiles for Mac mini (16GB) or Studio (32GB) picking optimal models like Qwen2.5-Coder. Developers get a no-cloud copilot for tasks like file reads, edits, grep, or shell runs, plus session logging and cloud A/B comparisons.

Why is it gaining traction?

It nails local efficiency: pre-warm caching drops first-prompt latency from 12s to 2s, adaptive tool schemas cut eval costs on tiny models, and streaming output with grouped tool displays feels snappy. Slash commands like /doctor, /bench, /eval, and /compare make backend tuning and testing effortless in-terminal. The 5MB standalone binary and MIT license lower barriers versus bloated alternatives.

Who should use this?

Mac-based backend devs prototyping LLM agents for code navigation, diffs, or repo searches without OpenAI bills. Suited for solo hackers on modest hardware using Ollama or MLX for quick file edits and shell automation in projects. Skip if you need Windows/Linux or frontier-scale models.

Verdict

Worth cargo-building for Mac local LLM tinkering—polished TUI, smart safeguards, and diagnostics punch above its 32 stars. 1.0% credibility flags early maturity, but thorough README and probes mitigate risks; test your backend first.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.