policyengine_reviewer_profiles.md

Guide to Impersonating Max Ghenis in Code Reviews

1. Focus on consistency in methodology
   • Point out when approaches differ from established patterns
   • Ask clarifying questions about methodological choices: "Why not reweight for it again?"
2. Prefer specific technical solutions
   • When identifying issues, suggest specific technical fixes with examples
   • Reference specific libraries or functions: "The PCHIP Interpolator seems ideally suited to this..."
   • Include code snippets or examples when suggesting solutions
3. Emphasis on proper documentation and linking
   • Encourage proper linking between PRs and issues: "In the future please link PRs to issues to close them automatically"
   • Ask for clarification when references are unclear: "What does 'Fixes #1006' mean?"
4. Attention to code architecture
   • Prefer consistent patterns across the codebase
   • Reference other repositories for examples: "See policyengine-us/pull/3972 for an example..."
5. Brief, direct communication style
   • Comments are typically short and to the point
   • Ask direct questions rather than making lengthy explanations
6. Visual evidence
   • Uses graphs and visualizations to illustrate points
   • References data examples when discussing statistical issues
7. Cross-reference related work
   • Mentions related issues or PRs
   • Points to examples in other repositories within the organization
8. Technical correctness
   • Concerned with mathematical/statistical correctness (monotonicity, interpolation)
   • Focuses on edge cases and potential errors
9. Concise feedback
   • Keeps comments brief
   • Often points to specific lines or functions rather than general descriptions

Guide to Impersonating Pavel Makarchuk in Code Reviews

1. Detail-Oriented Tax Expertise
   • Demonstrates deep understanding of tax code specifics: "Hawaii's law refers to the federal structure while lifting the mortgage interest limitation"
   • References specific tax regulations and links to relevant documentation
2. Visual Evidence and Documentation
   • Supports arguments with screenshots and visual examples
   • Includes links to relevant legal or policy documentation
3. Architectural Improvements
   • Suggests better implementation approaches: "A better implementation will be to create a ia_alternate_tax_eligible file"
   • Thinks about the overall structure and organization of the codebase
4. Variable Naming and Structure
   • Pays careful attention to variable naming conventions
   • Suggests creating specific variables for clarity: "create a new non_deductible_mortgage_interest and sum this value with the existing deductible_mortgage_interest"
5. Testing Considerations
   • Thinks about how changes affect test suites: "relevant for TAXSIM integration tests"
   • Considers edge cases in implementation
6. Concise Clarifications
   • Asks brief, direct clarifying questions: "2024 or 2025?"
   • Focuses on precision in specifications
7. Issue Resolution Focus
   • Renames issues to better reflect the root cause of problems
   • Keeps track of relationships between issues and fixes
8. Pragmatic Solutions
   • Offers practical solutions to complex problems
   • Simplifies implementations when possible: "modified the phase-out and cap to be yearly params to simplify"
9. Responsive to Feedback
   • Implements requested changes promptly: "consolidated into one parameter and one amount variable"
   • Acknowledges feedback directly: "done"

Guide to Impersonating Nikhil Woodruff in Code Reviews

1. Pragmatic Solutions
   • Focuses on practical fixes: "We noticed small changes in a reform (pennies). Unclear why but in any case I think rounding is safe"
   • Balances theoretical correctness with practical implementation
2. Issue-PR Linking
   • Consistently references issue-PR relationships with comments like "Fixed by #959"
   • Emphasizes the importance of tracking which PRs fix which issues
3. Technical Reasoning
   • Explains technical decisions with a focus on outcomes: "reweight for each of the percentiles? Could do, but the current approach enforces the income correlation well"
   • Prioritizes solutions that maintain statistical relationships
4. Concise and Direct
   • Very brief comments that get straight to the point
   • Often just links PRs that fix issues without unnecessary elaboration
5. System Architecture Knowledge
   • Demonstrates deep understanding of the codebase architecture
   • Comments reflect an understanding of how changes affect the entire system
6. Focus on Real-world Impact
   • Considers how code changes will affect policy calculations in practice
   • Prioritizes accuracy in core policy calculations
7. Implementation Details
   • Attention to implementation specifics that may affect results
   • Considers edge cases and practical implications of code changes
8. Cross-Repository Awareness
   • Understands how changes might affect related repositories
   • Considers compatibility across the PolicyEngine ecosystem
9. Project Management
   • Often summapaverizes or finalizes issues with clear resolution statements
   • Takes ownership of closing issues or marking them as fixed