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Found 344 Skills
Use Riverpod family providers to pass parameters and cache per parameter; FutureProvider.family, NotifierProvider.family, autoDispose with family, overriding in tests. Use when fetching data by ID, pagination, or any provider that depends on a parameter. Use this skill when the user asks about family, provider parameters, or caching by ID.
This skill should be used when the user asks to "write a pipeline", "add caching", "make this build faster", "show test failures in the build page", "add annotations", "only run tests when code changes", "set up dynamic pipelines", "add retry", "parallel steps", "matrix build", "add plugins", or "work with artifacts in pipeline YAML". Also use when the user mentions .buildkite/ directory, pipeline.yml, buildkite-agent pipeline upload, step types (command, wait, block, trigger, group, input), if_changed, notify, concurrency, or asks about Buildkite CI configuration.
Configure Redis for caching and data storage. Set up clustering, persistence, and Sentinel. Use when implementing Redis caching or queues.
SQL query optimization and database performance specialist. Use when optimizing slow queries, fixing N+1 problems, designing indexes, implementing caching, or improving database performance. Works with PostgreSQL, MySQL, and other databases.
Sets up comprehensive GitHub Actions CI/CD workflows for modern web applications. This skill should be used when configuring automated lint, test, build, and deploy pipelines, adding preview URL comments on pull requests, or optimizing workflow caching. Use when setting up continuous integration, deployment automation, GitHub Actions, CI/CD pipeline, preview deployments, or workflow optimization.
Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.
Deploy production recommendation systems with feature stores, caching, A/B testing. Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues.
When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
Optimize Groq API performance with caching, batching, and connection pooling. Use when experiencing slow API responses, implementing caching strategies, or optimizing request throughput for Groq integrations. Trigger with phrases like "groq performance", "optimize groq", "groq latency", "groq caching", "groq slow", "groq batch".
Implements Redis patterns for caching, sessions, rate limiting, pub/sub, and distributed locks with best practices. Use when users request "Redis caching", "session storage", "rate limiter", "pub/sub messaging", or "distributed locks".
Web Vitals, Lighthouse CI, bundle optimization, CDN, caching, and load testing
Apply when implementing caching logic, CDN configuration, or performance optimization for a headless VTEX storefront. Covers which VTEX APIs can be cached (Intelligent Search, Catalog) versus which must never be cached (Checkout, Profile, OMS), stale-while-revalidate patterns, cache invalidation, and BFF-level caching. Use for any headless project that needs TTL rules and caching strategy guidance.