gh-olino3-forge-forge-plugin/skills/python-code-review/templates/report_template.md

Code Review Report: [Project Name]

Date: [YYYY-MM-DD] Reviewer: Claude Code Scope: [Brief description of what was reviewed]

---

Executive Summary

Overall Assessment: [Excellent | Good | Fair | Needs Improvement | Critical Issues Found]

Key Findings:

• Critical Issues: [N]
• Important Issues: [N]
• Performance Concerns: [N]
• Security Vulnerabilities: [N]

Recommendation: [Summary recommendation - e.g., "Address critical security issues before deployment" or "Code is production-ready with minor improvements recommended"]

---

Critical Issues

1. [Issue Title]

Severity: Critical Category: [Security | Data Corruption | Production Failure] Location: file.py:123

Description: [Detailed description of the issue]

Impact: [What could go wrong if not fixed]

Recommendation:

# Before (vulnerable)
[problematic code]

# After (fixed)
[corrected code]

References:

• CWE-XXX or OWASP if applicable

---

2. [Next Critical Issue]

...

---

Important Issues

Performance Bottleneck: [Description]

Location: file.py:456 Impact: [e.g., "O(n²) complexity causes slowdown with large datasets"]

Analysis: [Explanation of the performance issue]

Recommendation:

# Current implementation (slow)
[current code]

# Optimized implementation
[improved code]

Expected Improvement: [e.g., "100x faster for 10,000 items"]

---

Security Concern: [Description]

Location: file.py:789 Severity: Important

Details: [Description of security concern]

Fix:

[corrected code]

---

Architecture and Design

Concerns

1. Tight Coupling: [Description]

   • Location: [files]
   • Recommendation: [architectural improvement]

2. Missing Abstractions: [Description]

   • Impact: [code duplication, hard to test, etc.]
   • Recommendation: [refactoring suggestion]

Positive Patterns

• [Well-implemented pattern 1]
• [Good design choice 2]

---

Performance Analysis

CPU Profiling Results

Top Hotspots:

1. function_name() in file.py: [X]ms cumulative ([Y]% of total)
2. [Next hotspot]

Memory Usage

Peak Memory: [X] MB Concerns:

• [Memory leak in function X]
• [Inefficient data structure in Y]

Recommendations

1. [Specific performance improvement 1]
2. [Specific performance improvement 2]

---

Code Quality

Complexity Analysis

High Complexity Functions:

• function_name() (file.py:123): Complexity 25 (Rank C)
  • Recommendation: Refactor into smaller functions

Dead Code

Unused Code Found:

• unused_function() in utils.py
• Variable UNUSED_CONSTANT in config.py

Recommendation: Remove to improve maintainability

---

Testing

Coverage Analysis

Current Coverage: [X]%

Missing Critical Tests:

1. Edge case: [description]
2. Error path: [description]
3. Integration test: [description]

Test Quality Issues

• [Issue with existing tests]
• [Recommendation for improvement]

---

Dependencies

Vulnerable Dependencies

Package	Current	Vulnerability	Fix
package-name	1.0.0	CVE-XXXX-XXXX	Upgrade to 1.1.0

Outdated Dependencies

• [List of significantly outdated packages]

---

Minor Issues and Suggestions

Style and Conventions

Note: These should be handled by automated tools (ruff, isort, basedpyright) in CI/CD.

• [Only list if blocking automated tool adoption]

Documentation

• Missing docstrings: [list key functions]
• Unclear variable names: [examples]

---

Positive Highlights

Well-Implemented Features:

1. [Good pattern or implementation 1]
2. [Good practice observed 2]
3. [Security measure properly implemented]

---

Recommendations Priority Matrix

Immediate (Before Deployment)

1. Fix SQL injection vulnerability (file.py:123)
2. Address race condition in payment processing (payment.py:456)
3. Fix memory leak in upload handler (upload.py:789)

High Priority (This Sprint)

1. Optimize N+1 query in user list (views.py:234)
2. Add missing authentication check (api.py:567)
3. Implement error handling in critical path (processor.py:890)

Medium Priority (Next Sprint)

1. Refactor high complexity functions
2. Add integration tests for payment flow
3. Update vulnerable dependencies

Low Priority (Backlog)

1. Remove dead code
2. Improve documentation
3. Consider architectural refactoring for module X

---

Automated Tool Results Summary

• Ruff: [N] issues found
• Basedpyright: [N] type errors
• Bandit: [N] security issues
• Safety: [N] vulnerable dependencies
• Performance Profiler: [Summary of findings]

Detailed reports: See review_results/ directory

---

Conclusion

[Overall assessment paragraph summarizing the review, key takeaways, and next steps]

Approval Status: [Approved | Approved with Conditions | Requires Changes | Blocked]

Next Steps:

1. [Action item 1]
2. [Action item 2]
3. [Action item 3]

---

Review Conducted By: Claude Code Python Review Skill Tools Used: ruff, basedpyright, isort, bandit, safety, performance_profiler