Python Code Review

SkillFiles & storage

Reviews Python code for type safety, async patterns, error handling, and common mistakes. Use when reviewing .py files, checking type hints, async/await usage, or exception handling.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Python Code Review skill

What this skill tells your AI

The instructions your AI receives, as published by existential-birds/beagle in plugins/beagle-python/skills/python-code-review/SKILL.md and read by ahel’s review.

Quick Reference

Issue TypeReference
Indentation, line length, whitespace, namingreferences/pep8-style.md
Missing/wrong type hints, Any usagereferences/type-safety.md
Blocking calls in async, missing awaitreferences/async-patterns.md
Bare except, missing context, loggingreferences/error-handling.md
Mutable defaults, print statementsreferences/common-mistakes.md

Review Checklist

PEP8 Style

  • 4-space indentation (no tabs)
  • Line length ≤79 characters (≤72 for docstrings/comments)
  • Two blank lines around top-level definitions, one within classes
  • Imports grouped: stdlib → third-party → local (blank line between groups)
  • No whitespace inside brackets or before colons/commas
  • Naming: snake_case for functions/variables, CamelCase for classes, UPPER_CASE for constants
  • Inline comments separated by at least two spaces

Type Safety

  • Type hints on all function parameters and return types
  • No Any unless necessary (with comment explaining why)
  • Proper T | None syntax (Python 3.10+)

Async Patterns

  • No blocking calls (time.sleep, requests) in async functions
  • Proper await on all coroutines

Error Handling

  • No bare except: clauses
  • Specific exception types with context
  • raise ... from to preserve stack traces

Common Mistakes

  • No mutable default arguments
  • Using logger not print() for output
  • f-strings preferred over .format() or %

Valid Patterns (Do NOT Flag)

These patterns are intentional and correct - do not report as issues:

  • Type annotation vs type assertion - Annotations declare types but are not runtime assertions; don't confuse with missing validation
  • Using Any when interacting with untyped libraries - Required when external libraries lack type stubs
  • Empty __init__.py files - Valid for package structure, no code required
  • noqa comments - Valid when linter rule doesn't apply to specific case
  • Using cast() after runtime type check - Correct pattern to inform type checker of narrowed type

Context-Sensitive Rules

Only flag these issues when the specific conditions apply:

IssueFlag ONLY IF
Generic exception handlingSpecific exception types are available and meaningful
Unused variablesVariable lacks _ prefix AND isn't used in f-strings, logging, or debugging

Gates (reporting workflow)

Complete in order. Do not advance until each pass condition is met.

  1. ScopePass: You list every .py path (or explicit glob) you inspected this run.
  2. False-positive screenPass: For each issue you plan to report, you checked Valid Patterns and Context-Sensitive Rules above; you drop or narrow the finding if those sections say not to flag it.
  3. EvidencePass: Each remaining finding includes [FILE:LINE] (or a bounded line range). Symbols or short verbatim snippets may supplement the location anchor but do not replace it.
  4. Verification protocolPass: You load review-verification-protocol and complete its mandatory steps for each reported issue before the user-facing write-up.
  5. ShipPass: The user-visible output matches whatever structure that protocol requires (no issues-only dump that skips its checks).

When to Load References

  • Reviewing code formatting/style → pep8-style.md
  • Reviewing function signatures → type-safety.md
  • Reviewing async def functions → async-patterns.md
  • Reviewing try/except blocks → error-handling.md
  • General Python review → common-mistakes.md

Review Questions

  1. Does the code follow PEP8 formatting (indentation, line length, whitespace)?
  2. Are imports properly grouped (stdlib → third-party → local)?
  3. Do names follow conventions (snake_case, CamelCase, UPPER_CASE)?
  4. Are all function signatures fully typed?
  5. Are async functions truly non-blocking?
  6. Do exceptions include meaningful context?
  7. Are there any mutable default arguments?

Before reporting: complete Gates (reporting workflow) above (especially gate 4).

Signals

GitHub stars
81
Forks
8
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
python-code-review
Source
github.com/existential-birds/beagle