rasbt

rasbt / mini-coding-agent

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Minimal and readable coding agent harness implementation in Python to explain the core components of coding agents.

17
3
100% credibility
Found Apr 02, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A minimal local AI coding assistant that interacts with your project files, runs commands, and makes changes with user approval using a chat interface.

How It Works

1
🔍 Discover the coding helper

You find a simple tool on GitHub that acts like a smart buddy to help with your coding projects right on your own computer.

2
🧠 Prepare your local thinker

You download and set up a free local AI program on your machine so it can understand and generate code ideas.

3
📥 Get the agent files

You save the small program files to a folder on your computer, ready to use anywhere.

4
🚀 Launch in your project

You open the program in your coding folder and start a chat, seeing a fun welcome screen with your project details.

5
💬 Chat about your code

You tell it simple tasks like 'fix this bug' or 'add a new feature', and it reads files, runs checks, and suggests changes.

6
✅ Approve smart changes

When it wants to update files or run tests, you quickly say yes or no to keep everything safe and under your control.

🎉 Your project shines

Your code gets fixed, new parts added, tests pass, and you can save the chat to pick up later, all working locally.

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Star Growth

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AI-Generated Review

What is mini-coding-agent?

This minimal Python coding agent turns a local Ollama model into a CLI-powered assistant for your codebase. Point it at a workspace directory, issue tasks like "fix this bug" or "add tests," and it lists files, reads code, searches, runs shell commands, writes or patches files—all with approval gates for risky actions. It persists sessions, resumes work, and handles bounded delegation, solving the need for a dead-simple, local harness to explain core components of coding agents without cloud dependencies.

Why is it gaining traction?

Its zero-runtime-deps design (just Python stdlib + Ollama) and readable structure make it a perfect minimal GitHub repo for forking into custom agents, unlike bloated frameworks. Developers dig the CLI flags for tweaking models, approval modes (ask/auto/never), max steps, and interactive REPL commands like /memory or /reset. The stable prompt with workspace snapshots and tool parsing hooks users wanting a github minimal api for agent experiments.

Who should use this?

Python devs prototyping local AI coding helpers, like tweaking scripts in a repo or generating tests without leaving the terminal. Solo hackers exploring agent components for personal projects, or educators building minimal github readme demos around Ollama-powered tools. Avoid if you need production-scale robustness.

Verdict

Grab it if you're into minimal python agent implementations—17 stars and 1.0% credibility score scream early days, but solid docs and no-fluff CLI make it a low-risk fork for learning. Pair with a strong Ollama model like qwen3.5:9b for real wins.

(178 words)

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