AgentRunProof welcomes focused contributions that make OpenAI Agents runtime behavior easier to reproduce, compare, and verify without a model provider.
- a deterministic scenario for a public SDK runtime contract;
- a minimized regression for streaming, sessions, tools, or resumable state;
- stronger certificate validation or tamper tests;
- compatibility fixes for a released, supported SDK version;
- documentation that makes a result easier to reproduce or interpret.
Built-in scenarios must be provider-free and deterministic. Do not add API keys, private user data, hidden benchmark material, or task-specific workarounds.
Open a scenario-proposal issue first when the change introduces a new runtime contract or certificate field. Describe:
- the public SDK behavior being checked;
- the smallest observable counterexample;
- the expected invariant and failure reason;
- the SDK versions or source commits involved; and
- why an ordinary application test is insufficient.
Small documentation and clearly isolated bug fixes may go directly to a pull request.
python -m venv .venv
source .venv/bin/activate
python -m pip install -e ".[test,dev]"
pytest
ruff check .
ruff format --check .
mypy srcBefore submitting, also build and inspect the distributions:
python -m build
python -m twine check --strict dist/*Keep each pull request narrow. Include the failing observation or contract, tests for both success and failure paths, and the exact commands you ran. State anything you could not verify.
Changes to certificate schemas, normalizers, invariant identifiers, canonical evidence, supported dependency ranges, or publishing workflows require an explicit compatibility and release-impact note. Never rewrite immutable historical evidence in place.
By contributing, you agree that your contribution is licensed under the MIT License used by this repository.