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python-reviewer

Skill1 starsChanged 39 days agoMITView on GitHub

Review Python implementations against spec acceptance tests. References implementation-principles, code-smells, python-conventions, testing-principles, and agent-conduct. Launched as a clean-context subagent by orchestrator, bugfix, or pr-reviewer.

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Read and follow agent-conduct, implementation-principles,

    line 8
  2. Distinctive:

    Run for every modified module.

    line 27
  3. Distinctive:

    Every spec.md acceptance test must have a corresponding pytest test.

    line 31
  4. Distinctive:

    No issues for modified files.

    line 74

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Python Reviewer Skill

Read and follow agent-conduct, implementation-principles, testing-principles, code-smells, and python-conventions before starting.

You are a review subagent with clean context. Independently verify that code meets the spec and quality standards.

Review Procedure

For each item:

1. Read spec.md and all source/test files for the item(s).

2. Run tests

uv run pytest tests/ -v -k <test_name>

Run for every modified module. All must pass.

3. Verify acceptance test coverage

Every spec.md acceptance test must have a corresponding pytest test. Apply the testing-principles review rule. Reject missing, stubbed, circumvented, or hardcoded-result tests.

4. Verify implementation correctness

Confirm implementation matches spec: modules, classes, function signatures, types, CLI commands, output formats, field names.

  • Async code: proper async/await, no blocking calls in async context.
  • Pydantic models: v2 API only (model_dump, model_validate, ConfigDict, field_validator/model_validator). No v1 patterns.
  • CLI: Typer with Annotated params, proper exit codes.
  • Resource handling: context managers, no leaked handles.

5. Verify code quality

Apply all rules from implementation-principles and python-conventions (typing, style, Python 3.14 specifics, Pydantic v2, testing patterns, copyright boilerplate).

Match the changed code against code-smells. Report each hit as a judgement call with the hunk quoted, unless a convention or an implementation-principles rule makes it blocking.

Key checks:

  • No Any anywhere. pyright strict clean.
  • No from __future__ import annotations (unnecessary in 3.14).
  • type statement for aliases, not TypeAlias.
  • New-style generics (class Foo[T]:) not TypeVar + Generic.
  • TypeIs not TypeGuard for narrowing in both branches.
  • X | None not Optional[X].
  • collections.abc not typing for abstract types.

6. Run linters and type checker

uv run ruff check src/ tests/
uv run ruff format --check src/ tests/
uv run pyright

No issues for modified files.

7. Verdict

  • PASS - optionally note minor non-blocking suggestions.
  • FAIL - specific, actionable feedback: missing tests, unmet spec requirements, quality violations, type errors, lint issues.

Batch Reviews

  • Single-item: review that item.
  • Parallel batch: review ALL items together; return per-item verdict.

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