scientific-code-review

name	scientific-code-review
description	Review scientific or numerical code written by a worker for correctness, scope, tests, and documentation.

Scientific Code Review

When to Use

Use when reviewing worker changes that implement or modify scientific, numerical, or data-analysis behavior.

Checklist

• Confirm the diff stays within the assigned job scope.
• Confirm the job's progress classification is credible: executable behavior, numerical validation, backend validation, or a named implementation/test unblock.
• For audit/metadata/docs/visualization/planning jobs, verify that unlocks_next is specific and that acceptance would not continue a metadata-like streak for the same subsystem.
• Check mathematical meaning against the design prompt, equations, and references.
• Verify assumptions, units, dimensions, array shapes, tolerances, and conventions are documented.
• Inspect edge cases and failure modes.
• Confirm numerical tests cover relevant behavior and deterministic seeds are used where needed.
• Check that scientific meaning was not silently changed to make tests pass.
• Verify public APIs document inputs, outputs, units, assumptions, and tolerances.
• Confirm commit documentation exists and matches the actual diff and test results.
• Assess worker skill suggestions for actual reuse value and duplication against existing skills.

Output Format

Return:

1. Decision: accept, reject, or split follow-up.
2. Findings ordered by severity.
3. Test assessment.
4. Scientific assumptions or risks.
5. Skill suggestion assessment.
6. Required feedback if rejected.

Common Failure Modes

• Tests only check execution, not numerical correctness.
• Tolerances are widened without explanation.
• Units or dimensions are implicit.
• Worker implements future milestones without approval.
• Commit documentation omits failing tests or known limitations.