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Found 19 Skills
ADR format and methodology for documenting significant technical decisions with context, alternatives considered, and consequences. Use when making or documenting architectural decisions.
Test pyramid and testing strategy — unit, integration, and end-to-end test ratios, mocking strategies, test isolation, and what to test. Reference when planning test coverage or evaluating test quality.
Reference library of proven UI design patterns, component templates, and sector-specific conventions for high-quality design generation.
Error handling best practices across languages — error types, recovery strategies, user-facing messages, and logging. Reference when implementing error handling or designing error flows.
Branch naming conventions, Git Flow vs trunk-based development, feature branch lifecycle, and release strategies. Reference when creating branches, planning releases, or choosing a branching model.
REST and API design principles — resource naming, HTTP methods, status codes, pagination, versioning, and error responses. Reference when designing or reviewing APIs.
Incident response procedures — triage, communication, investigation, mitigation, and post-incident review. Use when handling production incidents or writing runbooks.
Database migration best practices — schema changes, zero-downtime migrations, rollback strategies, and data migration patterns. Reference when modifying database schemas.
Pull request authoring standards — structured descriptions, linking issues, providing test evidence, and writing good summaries. Reference when creating or describing pull requests.
Comprehensive code review criteria covering correctness, readability, maintainability, security, performance, and testing. Reference when reviewing code changes or preparing code for review.
Dependency management and auditing — evaluating new dependencies, security vulnerability scanning, update strategies, and license compliance. Use when adding or auditing dependencies.
Systematic debugging methodology — binary search isolation, hypothesis-driven debugging, reproducing issues, and root cause analysis. Use when debugging errors, unexpected behavior, or test failures.