LibreAI / Dev Tools / little-coder
// devtools · itayinbarr/little-coder

little-coder

A coding-agent harness optimized for smaller local LLMs — small models, serious coding work

★ 2.7k stars⑂ 183 forksApache-2.0updated 2026-09
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

little-coder is an open-source dev tools project by itayinbarr (itayinbarr/little-coder on GitHub). It has 2,655 GitHub stars and 183 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 18 September 2026.

GitHub stars
2,655
Forks
183
License
Apache-2.0
Last updated on GitHub
18 September 2026
Category
Dev Tools
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide your model: a local llama.cpp/Ollama/LM Studio server for privacy and cost, or a cloud model through the same harness.

  2. Get little-coder

    Install with the one-line script or npm — no clone or workspace install needed.

  3. Install and configure

    If local, start your model server (the README gives full llama.cpp, Ollama and LM Studio recipes) and set the provider's API-key env var (local servers ignore the value but need one present).

  4. Run your first task

    cd into your project, run little-coder, and give it a task — or start in plan mode (ctrl+q) for bigger work.

// features

Why people love it

Tuned for small models

Extensions and skills are designed around scaffold–model fit, keeping cold-start context around 7k tokens so smaller models stay effective.

Plan Mode

Research with sub-coders, 1–3 clarifying questions with suggested answers, an approved plan saved to .pi/approved-plan.md, then /implement starts a fresh session seeded with the plan.

Deep Research

f2 / /deep-research fans out read-only research sub-coders and returns one cited markdown report.

Sub-coders and background jobs

Isolated read-only child sessions research without cluttering the main context; long commands run as background jobs that wake the model on events.

Per-phase models

Plan on a big model and implement on a small one with /plan-model and /action-model; sessions are named, resumable, and edits require reading the file first.

Built on pi, unobtrusively

pi stays a plain dependency — no fork — and everything little-coder-specific lives under .pi/extensions, skills and benchmarks.

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// run it

Run it yourself

  1. Clone the repo

    Clone little-coder only if you want to hack on it; installation is step 2.

    git clone https://github.com/itayinbarr/little-coder.git
    cd little-coder
  2. Install

    Use the one-line installer (Node.js 22.19+) or npm, as the README shows.

    curl -fsSL https://raw.githubusercontent.com/itayinbarr/little-coder/main/install.sh | bash
    # or: npm install -g little-coder
  3. Launch in your project

    Start your local model server first if using one, then run little-coder in the project directory.

    cd ~/your-project
    little-coder
    # or name a model: little-coder --model llamacpp/qwen3.6-35b-a3b
// use cases

What you can build

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// faq

Questions, answered

Who maintains little-coder?

itayinbarr maintains it, building on the open pi agent substrate (pi.dev).

Is it free?

Yes, Apache-2.0 licensed. Local models are free to run; cloud models use your own provider keys.

Does it need a paid API key?

No — its canonical setup is fully local (llama.cpp/Ollama/LM Studio). Local providers still need a dummy API-key env value set, as the README explains.

How does it compare to Claude Code or Aider with a frontier model?

Those assume a frontier model. little-coder's whole design — small context, skill cards, plan/implement split — exists to make much smaller local models reliable at coding tasks.

How do I get started?

Run the one-line install, serve a model with llama.cpp or Ollama, cd into a project and run little-coder.

// keep exploring

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// alternatives

Alternatives in Dev Tools

The most-starred other Dev Tools projects in the LibreAI catalogue — the realistic shortlist if little-coder is not the right fit.

Get little-coder

Free and open — grab the source, star the repo, and start creating.