review-python（审查 Python）

Backend Code Review

Hard gates (sequence)

Advance only when each pass condition is objectively satisfied (prevents linter-owned false positives and ungrounded findings):

Arguments

• --parallel: Spawn specialized subagents per technology area
• Path: Target directory (default: current working directory)

Step 1: Identify Changed Files

Pass (G1): Capture the command output (or equivalent) as your authoritative changed-.py set before Steps 2–3.

git diff --name-only $(git merge-base HEAD main)..HEAD | grep -E '\.py$'

Step 2: Verify Linter Status

CRITICAL: Run project linters BEFORE flagging any style or type issues. Pass (G2): You may only proceed to Step 3 after each configured linter has been run on the changed files or you have recorded why it was skipped (missing config).

# Check if ruff config exists and run it
if [ -f "pyproject.toml" ] || [ -f "ruff.toml" ]; then
    ruff check <changed_files>
fi

# Check if mypy config exists and run it
if [ -f "pyproject.toml" ] || [ -f "mypy.ini" ]; then
    mypy <changed_files>
fi

Rules:

• If a linter passes for a specific rule (e.g., line length), DO NOT flag that issue manually
• Linter configuration is authoritative for style rules
• Only flag issues that linters cannot detect (semantic issues, architectural problems)

Why: Analysis of 24 review outcomes showed 4 false positives (17%) where reviewers flagged line-length violations that ruff check confirmed don't exist. The linter's configuration reflects intentional project decisions.

Step 3: Detect Technologies

# Detect Pydantic-AI
grep -r "pydantic_ai\|@agent\.tool\|RunContext" --include="*.py" -l | head -3

# Detect SQLAlchemy
grep -r "from sqlalchemy\|Session\|relationship" --include="*.py" -l | head -3

# Detect Postgres-specific
grep -r "psycopg\|asyncpg\|JSONB\|GIN" --include="*.py" -l | head -3

# Check for test files
git diff --name-only $(git merge-base HEAD main)..HEAD | grep -E 'test.*\.py$'

Step 4: Load Verification Protocol

Load beagle-python:review-verification-protocol skill and keep its checklist in mind throughout the review.

Step 5: Load Skills

Use the Skill tool to load each applicable skill (e.g., Skill(skill: "beagle-python:python-code-review")).

Always load:

• beagle-python:python-code-review
• beagle-python:fastapi-code-review

Conditionally load based on detection:

Step 6: Review

Sequential (default):

1. Load applicable skills
2. Review Python quality issues first
3. Review FastAPI patterns
4. Review detected technology areas
5. Consolidate findings

Parallel (--parallel flag):

1. Detect all technologies upfront
2. Spawn one subagent per technology area with Task tool
3. Each agent loads its skill and reviews its domain
4. Wait for all agents
5. Consolidate findings

Before Flagging Optimization or Pattern Issues

1. Check CLAUDE.md for documented intentional patterns
2. Check code comments around the flagged area for "intentional", "optimization", or "NOTE:"
3. Trace the code path before claiming missing coverage or inconsistent handling
4. Consider framework idioms - what looks wrong generically may be correct for the framework

Why: Analysis showed rejections where reviewers flagged "inconsistent error handling" that was intentional optimization, and "missing test coverage" for code paths that don't exist.

Step 7: Verify Findings

Pass (G4): No issue ships until all bullets below are true for that issue.

Before reporting any issue:

1. Re-read the actual code (not just diff context)
2. For "unused" claims - did you search all references?
3. For "missing" claims - did you check framework/parent handling?
4. For syntax issues - did you verify against current version docs?
5. Remove any findings that are style preferences, not actual issues

Step 8: Review Convergence

Pass (G5): Final markdown matches the Output Format template; verdict line reflects only Critical/Major blockers per scope rules below.

Single-Pass Completeness

You MUST report ALL issues across ALL categories (style, logic, types, tests, security, performance) in a single review pass. Do not hold back issues for later rounds.

Before submitting findings, ask yourself:

• "If all my recommended fixes are applied, will I find NEW issues in the fixed code?"
• "Am I requesting new code (tests, types, modules) that will itself need review?"

If yes to either: include those anticipated downstream issues NOW, in this review, so the author can address everything at once.

Scope Rules

• Review ONLY the code in the diff and directly related existing code
• Do NOT request new features, test infrastructure, or architectural changes that didn't exist before the diff
• If test coverage is missing, flag it as ONE Minor issue ("Missing test coverage for X, Y, Z") — do NOT specify implementation details like mock libraries, behaviour extraction, or dependency injection patterns that would introduce substantial new code
• Typespecs, documentation, and naming issues are Minor unless they affect public API contracts
• Do NOT request adding new dependencies (e.g. Mox, testing libraries, linter plugins)

Fix Complexity Budget

Fixes to existing code should be flagged at their real severity regardless of size.

However, requests for net-new code that didn't exist before the diff must be classified as Informational:

• Adding a new dependency (e.g. Mox, a linter plugin)
• Creating entirely new modules, files, or test suites
• Extracting new behaviours, protocols, or abstractions

These are improvement suggestions for the author to consider in future work, not review blockers.

Iteration Policy

If this is a re-review after fixes were applied:

• ONLY verify that previously flagged issues were addressed correctly
• Do NOT introduce new findings unrelated to the previous review's issues
• Accept Minor/Nice-to-Have issues that weren't fixed — do not re-flag them
• The goal of re-review is VERIFICATION, not discovery

Output Format

## Review Summary

[1-2 sentence overview of findings]

## Issues

### Critical (Blocking)

1. [FILE:LINE] ISSUE_TITLE
   - Issue: Description of what's wrong
   - Why: Why this matters (bug, type safety, security)
   - Fix: Specific recommended fix

### Major (Should Fix)

2. [FILE:LINE] ISSUE_TITLE
   - Issue: ...
   - Why: ...
   - Fix: ...

### Minor (Nice to Have)

N. [FILE:LINE] ISSUE_TITLE
   - Issue: ...
   - Why: ...
   - Fix: ...

### Informational (For Awareness)

N. [FILE:LINE] SUGGESTION_TITLE
   - Suggestion: ...
   - Rationale: ...

## Good Patterns

- [FILE:LINE] Pattern description (preserve this)

## Verdict

Ready: Yes | No | With fixes 1-N (Critical/Major only; Minor items are acceptable)
Rationale: [1-2 sentences]

Post-Fix Verification

After fixes are applied, run:

ruff check .
mypy .
pytest

All checks must pass before approval.

Rules

• Load skills BEFORE reviewing (not after)
• Number every issue sequentially (1, 2, 3...)
• Include FILE:LINE for each issue
• Separate Issue/Why/Fix clearly
• Categorize by actual severity
• Run verification after fixes
• Report ALL issues in a single pass — do not hold back findings for later iterations
• Re-reviews verify previous fixes ONLY — no new discovery
• Requests for net-new code (new modules, dependencies, test suites) are Informational, not blocking
• The Verdict ignores Minor and Informational items — only Critical and Major block approval