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    Code Contributor Track

    Complete this track if you create or modify code, scripts, notebooks, LaTeX, or documentation in a GitHub repository.

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    Complete this track if you create or modify code, scripts, notebooks, LaTeX, or documentation in a GitHub repository.

    Prerequisites#

    Competencies#

    You can:

    • authenticate without exposing credentials;
    • clone a repository and inspect its instructions;
    • create a branch and keep changes focused;
    • distinguish source, generated files, data, and secrets;
    • run the repository's tests and quality checks;
    • write a Conventional Commit such as fix(parser): handle empty input;
    • open a pull request that reports only verification actually performed;
    • distinguish the model, provider/gateway, agent harness, and interface;
    • constrain an agent's files, tools, data, side effects, and spending path;
    • review AI-generated diffs and reject unsupported changes;
    • recover from ordinary conflicts without destructive Git operations.

    Required Learning#

    1. Read Git and GitHub workflow.
    2. Read Python setup if the project uses Python.
    3. Read Agents and interfaces.
    4. Complete First safe pull request manually.
    5. Configure the no-cost VS Code and Copilot Student route.
    6. Complete Manual versus agent.
    7. Complete Reproducible Python environment when relevant.
    8. Complete Project handover.

    Fast Path#

    Experienced contributors may move quickly through explanations, but still complete the bounded Git practice PR and the same automatic checks.

    Evidence#

    • A focused pull request from a non-main branch.
    • At least one appropriate test or verification command.
    • A Conventional Commit.
    • A PR description with purpose, changes, affected interfaces/users, verification, risk, and AI assistance.
    • A manual/agent comparison naming personally run checks and one accepted and one rejected or revised suggestion.
    • No secrets, large data, or accidental generated files in the diff.

    Understand Before Accepting AI Output#

    • I can explain every changed behavior.
    • I know which test supports the change.
    • I checked the diff for secrets and unrelated files.
    • I did not let the agent invent verification results.
    • I know which service received context and which account would be billed.

    Pass Criteria#

    The trusted automatic checks pass, and the contributor can explain the change, the staged diff, and the verification they personally ran. Normal project PRs still follow that project's own human review policy.