data-modeling
Design dimensional models, star/snowflake schemas, and data warehouse structures for analytics and reporting
Découvrez les skills Tests et sécurité, comparez leurs dépôts et consultez leurs instructions.
Design dimensional models, star/snowflake schemas, and data warehouse structures for analytics and reporting
Design and implement continuous integration and deployment pipelines with automated testing, builds, and deployments
Create well-structured user stories with clear acceptance criteria in 'As a/I want/So that' format for team communication
Measure and improve test coverage by identifying untested code paths and prioritizing high-risk areas for testing
Design AI agents with appropriate capabilities, tools, and personas for specific software development tasks
Design Kubernetes deployment patterns, configure service mesh, and implement container best practices
Design efficient database schemas, write optimized queries with proper indexes, and manage data operations following best practices
Identify code smells, prioritize refactoring opportunities, and assess technical debt impact
Extract complete, unambiguous requirements from specifications by identifying functional/non-functional requirements and clarifying ambiguities
Implement exponential backoff, token bucket algorithms, and API quota management
Design and execute load tests to validate performance under stress, identify scalability limits, and ensure SLA compliance
Break down features and requirements into actionable, implementable tasks with clear scope and acceptance criteria
Scan dependencies and code for known vulnerabilities using automated tools, triage security issues, and prioritize remediation
Define and manage infrastructure using code with tools like Terraform, CloudFormation, and Docker
Systematically reproduce, diagnose, and analyze bugs to determine root cause, assess severity, and plan fix strategy
Validate WCAG 2.1 AA/AAA standards, use accessibility testing tools, and implement remediation strategies
Create clear, accessible documentation for technical and non-technical audiences with practical examples and logical structure
Implement structured logging with appropriate levels, context, and correlation for effective debugging and monitoring
A process for making a quick single feature fix or improvement and deploying it to the production environment. Use anytime the user asks to for any improvements or fixes.
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Use when CI fails on Buildkite and you need to diagnose and fix failures - fetches build results for current branch, extracts errors from logs, and helps fix them
Opinionated constraints for building better interfaces with agents.
Create semantic git commits following Conventional Commits specification. Use when committing changes, making commits, or when asked to commit.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.