gitwtfhub

wtf is tracekit?

haard18/tracekit — explained in plain English

Analysis updated 2026-05-18

2PythonAudience · developerComplexity · 4/5LicenseSetup · hard

TL;DR

A tool that turns your own coding agent history into a small, private language model that runs offline and handles simple routine coding tasks.

Mindmap

mindmap
  root((tracekit))
    What it does
      Reads coding agent logs
      Filters kept edits
      Trains a small model
      Runs it offline
    Tech stack
      Python
      QLoRA
      Ollama
    Use cases
      Personal commit model
      Offline routine tasks
      Reduce API cost
    Audience
      Developers

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

Why would anyone build with this?

REASON 1

Turn your Claude Code session history into a small local model

REASON 2

Run a personal fine-tuned model offline for commit messages and small edits

REASON 3

Reduce how many routine coding requests go through a paid API

REASON 4

Inspect what your coding agent logs actually captured about your work

What's in the stack?

PythonQLoRASQLiteOllama

How it stacks up

haard18/tracekit0-bingwu-0/live-interpreter010zx00x1/faresnipe
Stars222
LanguagePythonPythonPython
Setup difficultyhardmoderateeasy
Complexity4/52/52/5
Audiencedevelopergeneralgeneral

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · hard Time to first run · 1h+

Training needs a GPU for reasonable speed and pulls in torch via the optional ml extra.

Wtf does this do

tracekit is a command line tool that takes the logs your coding agent already creates, such as Claude Code's session history, and turns them into a small language model trained on your own habits. Every time you use a coding agent it writes detailed records of your edits and commit messages, and these records normally just sit unused on your computer. tracekit reads that history, keeps only the parts that were actually kept and committed, and fine tunes a small model on them. The resulting model is meant to run entirely on your own machine, for routine tasks like writing commit messages or making small edits, in a style that matches how you normally work. It is not meant to replace a large model like Claude for complex reasoning. Instead it aims to take over a portion of your simpler, repetitive requests so that fewer of them need to go through a paid API. The tool works as a pipeline of steps you can run individually or all together with one command. First it scans your machine for existing coding agent logs, then it parses them into a local database, filters out edits that were reverted or unused, builds a training dataset from what is left, fine tunes a small model using a technique called QLoRA, evaluates the result, and finally exports it to run with Ollama, a tool for running language models locally. Everything happens on your own computer. The README states there are no network calls in the core product and no telemetry. Secrets found in your logs are automatically filtered out before anything is stored, and file contents are never kept, only a short fingerprint of them is saved instead. Right now it supports reading logs from Claude Code, with support for other coding agents like Codex, Aider, and Cursor listed as planned but not yet available. Training requires Python 3.11 or later, and a GPU is recommended for the training step, though a slower CPU option exists for testing purposes.

Yoink these prompts

Prompt 1
Walk me through running tracekit go to build and train a personal model from my Claude Code logs.
Prompt 2
Help me install tracekit with the ml extra so I can train models.
Prompt 3
Explain what tracekit's curate step keeps versus discards from my coding history.
Prompt 4
Show me how to serve my trained tracekit model locally with an OpenAI-compatible endpoint.

Frequently asked questions

wtf is tracekit?

A tool that turns your own coding agent history into a small, private language model that runs offline and handles simple routine coding tasks.

What language is tracekit written in?

Mainly Python. The stack also includes Python, QLoRA, SQLite.

How hard is tracekit to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is tracekit for?

Mainly developer.

View the repo → Decode another repo

This repo across BitVibe Labs

Don't trust strangers blindly. Verify against the repo.