全部 Agent Skills
41,263 个结果
- Qdrant Performance OptimizationGitHub官方Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want to improve the speed and efficiency of your Qdrant deployment.
- Qdrant ScalingGitHub官方Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', or 'need to add capacity'.
- Qdrant Scaling Data VolumeGitHub官方Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or 'data growth exceeds capacity'.
- Qdrant Scaling QpsGitHub官方Guides Qdrant query throughput (QPS) scaling. Use when someone asks 'how to increase QPS', 'need more throughput', 'queries per second too low', 'batch search', 'read replicas', or 'how to handle more concurrent queries'.
- Qdrant Scaling Query VolumeGitHub官方Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.
- Qdrant Search QualityGitHub官方Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?'.
- Qdrant Search Quality DiagnosisGitHub官方Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', or 'quality dropped after quantization'. Also use when search quality degrades without obvious changes.
- Qdrant Search Speed OptimizationGitHub官方Diagnoses and fixes slow Qdrant search. Use when someone reports 'search is slow', 'high latency', 'queries take too long', 'low QPS', 'throughput too low', 'filtered search is slow', or 'search was fast but now it's slow'. Also use when search performance degrades after config changes or data growth.
- Qdrant Search StrategiesGitHub官方Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'BM25 or sparse vectors?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're there', 'retrieval quality is not good enough', 'results too similar', 'need diversity', 'MMR', 'relevance feedback', 'recommendation API', 'discovery API', 'ColBERT…
- Qdrant Sliding Time WindowGitHub官方Guides sliding time window scaling in Qdrant. Use when someone asks 'only recent data matters', 'how to expire old vectors', 'time-based data rotation', 'delete old data efficiently', 'social media feed search', 'news search', 'log search with retention', or 'how to keep only last N months of data'.
- Qdrant Tenant ScalingGitHub官方Guides Qdrant multi-tenant scaling. Use when someone asks 'how to scale tenants', 'one collection per tenant?', 'tenant isolation', 'dedicated shards', or reports tenant performance issues. Also use when multi-tenant workloads outgrow shared infrastructure.
- Qdrant Version UpgradeGitHub官方Guidance on how to upgrade your Qdrant version without interrupting the availability of your application and ensuring data integrity.
- Qdrant Vertical ScalingGitHub官方Guides Qdrant vertical scaling decisions. Use when someone asks 'how to scale up a node', 'need more RAM', 'upgrade node size', 'vertical scaling', 'resize cluster', 'scale up vs scale out', or when memory/CPU is insufficient on current nodes. Also use when someone wants to avoid the complexity of horizontal scaling.
- Quality PlaybookGitHub官方Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch.
- Quarkus Application DevelopmentGitHub官方Write Quarkus application code: REST with Quarkus REST, validation, exception mappers, OpenAPI, configuration, CDI (ArC), Hibernate ORM with Panache, Mutiny and virtual threads, Reactive Messaging with Kafka, OIDC security, health, metrics, OpenTelemetry, fault tolerance, REST Client, scheduler and cache. Use when implementing or changing features in an existing Quarkus project.
- Quarkus Dev Services And TestingGitHub官方Quarkus Dev Services and testing: zero-config containers, @QuarkusTest, @QuarkusIntegrationTest, test resources, RestAssured, @InjectMock, profiles and continuous testing. Use when writing or fixing tests in a Quarkus project.
- Quarkus Native And ContainerGitHub官方Build Quarkus native executables (Mandrel/GraalVM), fix native failures with reflection registration, test the native binary, and produce container images and Kubernetes/OpenShift manifests. Use for native, Docker, Jib or Kubernetes work in a Quarkus project.
- Quasi CoderGitHub官方Expert 10x engineer skill for interpreting and implementing code from shorthand, quasi-code, and natural language descriptions. Use when collaborators provide incomplete code snippets, pseudo-code, or descriptions with potential typos or incorrect terminology. Excels at translating non-technical or semi-technical descriptions into production-quality code.
- React Audit Grep PatternsGitHub官方Provides the complete, verified grep scan command library for auditing React codebases before a React 18.3.1 or React 19 upgrade. Use this skill whenever running a migration audit - for both the react18-auditor and react19-auditor agents.
- React Container Presentation ComponentGitHub官方Create a React component using the Container/Presentation pattern in src/components by asking for the component name and type (ui or features), then scaffold files that follow this repository's TypeScript, Storybook, and SCSS conventions. Use when the user explicitly asks for a Container/Presentation-based component or runs /react-container-presentation-component.
- React18 Batching PatternsGitHub官方Provides exact patterns for diagnosing and fixing automatic batching regressions in React 18 class components. Use this skill whenever a class component has multiple setState calls in an async method, inside setTimeout, inside a Promise .then() or .catch(), or in a native event handler. Use it before writing any flushSync call - the decision tree here prevents unnecessary flushSync overuse.
- React18 Dep CompatibilityGitHub官方React 18.3.1 and React 19 dependency compatibility matrix.
- React18 Enzyme To RtlGitHub官方Provides exact Enzyme → React Testing Library migration patterns for React 18 upgrades. Use this skill whenever Enzyme tests need to be rewritten - shallow, mount, wrapper.find(), wrapper.simulate(), wrapper.prop(), wrapper.state(), wrapper.instance(), Enzyme configure/Adapter calls, or any test file that imports from enzyme.
- React18 Legacy ContextGitHub官方Provides the complete migration pattern for React legacy context API (contextTypes, childContextTypes, getChildContext) to the modern createContext API. Use this skill whenever migrating legacy context in class components - this is always a cross-file migration requiring the provider AND all consumers to be updated together.