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What you can do with Evo Trace

EvoTrace is a local-first compiler that turns real Claude Code and Codex sessions into evidence-backed training data, replayable coding tasks, and verified execution rewards, built on DeepSeek Harness.

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jinzijian/EvoTrace on GitHub

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What do you want to do?

4 use cases

  • Find the worth-keeping sessions in your coding history

    Import local Claude Code and Codex history and rank the sessions that hold useful task evidence.

    View prompt
    Using the EvoTrace repo at https://github.com/jinzijian/EvoTrace, install it and run /init then /candidates in the DeepSeek Harness app on my local Claude Code and Codex history. Return the top 5 candidates with task intent, repository, and missing evidence for each. Verify that the candidate list loads with no model provider configured.

  • Compile a session into a Docker-validated coding task

    Review a candidate, build an executable bundle, and run two-state Docker validation on it.

    View prompt
    Using the EvoTrace repo at https://github.com/jinzijian/EvoTrace, run /review 1, /build 1, and /validate 1 in the DeepSeek Harness app for the candidate <candidate-number>. Report the asset status and the Docker validation result from /runs. Verify that the asset is marked Verified only if the base was rejected and the reference was accepted.

  • Make a verified task harder and measure its difficulty

    Derive a harder child task from a verified one, then measure it with fresh solver attempts.

    View prompt
    Using the EvoTrace repo at https://github.com/jinzijian/EvoTrace, run /harden 1 and then /calibrate on the resulting child asset in the DeepSeek Harness app. Report the calibration pass count out of attempts and the added behavior. Verify that the child task adds testable behavior, compatibility, edge cases, or failure constraints rather than only a longer patch.

  • Test whether compressed experience transfers to a new task

    Compress execution experience from one task and score it on an independent held-out task.

    View prompt
    Using the EvoTrace repo at https://github.com/jinzijian/EvoTrace, build two independent verified assets from the same repository, then run /evolve <source-asset> <held-out-asset> in the DeepSeek Harness app. Report baseline and conditioned Docker reward results from /runs. Verify that the held-out asset was built independently and that a run with only one asset is treated as a wiring smoke test, not transfer evidence.

How to use Evo Trace

  1. Check you have what it needs: Existing Claude Code or Codex session history on the local machine; Git, and Node.js 22.19+ or 24+ for the DeepSeek Harness app; A model provider configured in Harness Settings for review, hardening, calibration, and evolution.
  2. Open jinzijian/EvoTrace on GitHub and read the README and license.
  3. Run curl -LsSf https://raw.githubusercontent.com/jinzijian/EvoTrace/main/install.sh | sh on macOS, Linux, or WSL.
  4. Run evotrace to open the DeepSeek Harness Web app.
  5. In the app, run /init to import existing Claude Code and Codex history.
  6. Run /candidates to show the strongest evidence-backed sessions.

These steps come from our top use case, Find the worth-keeping sessions in your coding history, which also has a copy-paste agent prompt.

Evo Trace alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forBuilt for ML engineers and developers who have Claude Code or Codex history on their machine and want to turn it into post-training or evaluation assets.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/jinzijian/EvoTrace · Back to Hot repos

Requirements

  • Existing Claude Code or Codex session history on the local machine
  • Git, and Node.js 22.19+ or 24+ for the DeepSeek Harness app
  • A model provider configured in Harness Settings for review, hardening, calibration, and evolution
  • Docker, only when building or validating executable environments
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Questions about Evo Trace

What is Evo Trace?

EvoTrace is a local-first compiler that turns real Claude Code and Codex sessions into evidence-backed training data, replayable coding tasks, and verified execution rewards, built on DeepSeek Harness. It is an open-source project on GitHub: https://github.com/jinzijian/EvoTrace.

Who is Evo Trace for?

Built for ML engineers and developers who have Claude Code or Codex history on their machine and want to turn it into post-training or evaluation assets.

What can I do with Evo Trace?

4 use cases so far, for example: Find the worth-keeping sessions in your coding history; Compile a session into a Docker-validated coding task; Make a verified task harder and measure its difficulty. Each has steps and a copy-paste agent prompt.

What do I need to run Evo Trace?

Existing Claude Code or Codex session history on the local machine; Git, and Node.js 22.19+ or 24+ for the DeepSeek Harness app; A model provider configured in Harness Settings for review, hardening, calibration, and evolution; Docker, only when building or validating executable environments.

What are alternatives to Evo Trace?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Evo Trace safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.