sales-tax-calc

Review AI-generated code changes for unintended consequences, logic errors, UI inconsistencies, and context-specific issues. Use when: code has just been modified, flag potential bugs, verify UI consistency, check implementation correctness against project patterns.

Comprehensive research assistant that synthesizes information from multiple sources with citations. Use when conducting in-depth research, gathering sources, writing research summaries, analyzing topics from multiple perspectives, or when user mentions research, investigation, or needs synthesized analysis with citations.

Turn a feature request, issue, or rough spec into a safe implementation plan for an existing codebase. Use when: planning a new feature, scoping impacted files, evaluating trade-offs, or deciding rollout steps before coding.

Turn small ideas into fully-fledged projects through structured discovery, research, and specification. Use when: starting a new project from a rough idea, need to validate feasibility, want to create comprehensive project documentation, exploring feature requirements and design patterns. Conversational, adaptive workflow.

Find the actual cause of bugs, failures, flaky tests, and regressions before proposing a fix. Use when: debugging runtime errors, CI failures, broken features, inconsistent behavior, or production incidents.

Review code and architecture for security risks, then harden the implementation without unnecessary complexity. Use when: checking auth flows, input validation, secrets, dependency risk, unsafe file or network access, or preparing a project for release.

Design the smallest effective set of tests for a change, then generate them in the project's style. Use when: fixing bugs, adding features, preventing regressions, or improving weak test coverage across web, JVM, Python, and native codebases.