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What you can do with Open Work Proof

OpenWorkProof is an open protocol that records who authorized an AI agent's work, what the agent did, how it was verified, and who accepted or rejected it, packaged as signed evidence that third parties can check offline.

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dengyier/OpenWorkProof on GitHub

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What do you want to do?

5 use cases

  • Verify an agent work package offline without the vendor

    Check a signed Surface or Acceptance bundle with the owp CLI, no access to the original platform.

    View prompt
    Using the OpenWorkProof repo at https://github.com/dengyier/OpenWorkProof, install the openworkproof package with pip and run `owp acceptance-bundle-verify <DIRECTORY>` on the bundle at <DIRECTORY>. Report the result and the exit code, where ACCEPTED is 0 and REJECTED is 2. Verify that the command ran without reading any private key from the bundle folder.

  • Run the Human Agency example to see reserved actions

    Run the minimal Human Agency Profile script to see which agent actions are allowed and which need a human.

    View prompt
    Clone https://github.com/dengyier/OpenWorkProof, create a virtual environment, install it in editable mode, and run `python examples/human_agency_profile_v01.py`. Report whether the output shows 'profile verified : True' and that owp.apply_patch returns AGENCY_HUMAN_DECISION_REQUIRED. Verify that the script writes no application files or ledgers, as the README states.

  • Attach a four-question evidence report to pull requests

    Use the GitHub Action to report what was claimed, what evidence exists, what limits applied, and the conclusion.

    View prompt
    Review the GitHub Action definition at integrations/github/action.yml in https://github.com/dengyier/OpenWorkProof and add it to the pull request workflow of <TARGET_REPO>. Open a test pull request and report the conclusion in the four-question report. Verify that the report does not describe the change as accepted or paid.

  • Package an agent delivery case for payer review

    Initialize, inspect, verify, and export a Verified Agent Delivery case as a third-party review package.

    View prompt
    Using https://github.com/dengyier/OpenWorkProof, run `owp delivery-case init <CASE_DIR>`, then `owp delivery-case inspect <CASE_DIR>` and `owp delivery-case verify <CASE_DIR>`, and export with `owp delivery-case export <CASE_DIR> --output-directory <OUTPUT_DIR>`. Report the derived status. Verify that the status comes from the Surface, Acceptance, and Settlement evidence and not from a pre-written conclusion file.

  • Build an acceptance bundle for an outside human signer

    Generate an Acceptance Bundle from a ledger so an external Acceptor can sign without a private key entering the tool.

    View prompt
    Using https://github.com/dengyier/OpenWorkProof, run `owp acceptance-bundle-build <LEDGER> <SURFACE> --evidence-root <PATH> --output <DIRECTORY>` and then `owp acceptance-bundle-verify <DIRECTORY>`. Report the exit code and whether it is 0, 2, or 4. Verify that no private key or acceptance receipt was generated by the tool itself.

How to use Open Work Proof

  1. Check you have what it needs: A Python environment with pip; A terminal with git for source installs; An existing Surface Bundle or Acceptance Bundle to verify, for the offline verification case.
  2. Open dengyier/OpenWorkProof on GitHub and read the README and license.
  3. Install the package with python -m pip install openworkproof.
  4. Confirm the CLI is available with owp --help.
  5. For a Surface Bundle, run owp surface-verify PATH with PATH set to the bundle folder.
  6. For an Acceptance Bundle, run owp acceptance-bundle-verify DIRECTORY with DIRECTORY set to the bundle folder.

These steps come from our top use case, Verify an agent work package offline without the vendor, which also has a copy-paste agent prompt.

Open Work Proof alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forWritten for teams that delegate code or other work to AI agents and need proof of authorization, execution, and acceptance that a third party can check.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/dengyier/OpenWorkProof · Back to Hot repos

Requirements

  • A Python environment with pip
  • A terminal with git for source installs
  • An existing Surface Bundle or Acceptance Bundle to verify, for the offline verification case
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Questions about Open Work Proof

What is Open Work Proof?

OpenWorkProof is an open protocol that records who authorized an AI agent's work, what the agent did, how it was verified, and who accepted or rejected it, packaged as signed evidence that third parties can check offline. It is an open-source project on GitHub: https://github.com/dengyier/OpenWorkProof.

Who is Open Work Proof for?

Written for teams that delegate code or other work to AI agents and need proof of authorization, execution, and acceptance that a third party can check.

What can I do with Open Work Proof?

5 use cases so far, for example: Verify an agent work package offline without the vendor; Run the Human Agency example to see reserved actions; Attach a four-question evidence report to pull requests. Each has steps and a copy-paste agent prompt.

What do I need to run Open Work Proof?

A Python environment with pip; A terminal with git for source installs; An existing Surface Bundle or Acceptance Bundle to verify, for the offline verification case.

What are alternatives to Open Work Proof?

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

Is Open Work Proof 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.