Ray Carter

Turn a rough feature idea into clear requirements, scope boundaries, and testable acceptance criteria.

Get a prioritized report of repository traps that could cause AI coding agents to make the wrong changes.

Reorganize crowded repositories into clearly owned packages, with caller updates, cleanup, and behavior checks.

Get location-backed findings and practical fixes for Python library integration problems.

Get a prioritized Python backend review with file-specific risks, practical fixes, and suggested tests.

Turn a product spec into assignable engineering issues with clear completion checks and delivery order.

Find conflicting assumptions and unresolved edge cases in architecture plans using your repository's docs and code.

Get a grounded critique of technical plans and code, with clear risks and concrete next actions.

Get evidence-backed findings on framework and library integrations, with exact locations and testable fixes.

Save engineering decisions, evidence, and follow-up needs so future coding agents can recover the context.

Get coordinated repository changes with independent checks, recorded handoffs, and a clear completion report.

Get a prioritized report on database access risks, supporting evidence, and recommended fixes.

Get architecture findings and a phased refactor plan that clarify ownership and reduce the scope of future changes.

Get feature changes, bug fixes, and refactors backed by behavior-focused tests and clear validation results.

Find evidence-backed causes of bugs and slowdowns, with tested fixes or a clear plan to verify the diagnosis.