[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-cline-cosmosdb-best-practices":3,"mdc-kwir9q-key":39,"related-org-cline-cosmosdb-best-practices":1244,"related-repo-cline-cosmosdb-best-practices":1431},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":28,"repoUrl":29,"updatedAt":30,"license":31,"forks":32,"topics":33,"repo":34,"sourceUrl":37,"mdContent":38},"cosmosdb-best-practices","optimize Azure Cosmos DB performance","Azure Cosmos DB performance optimization and best practices guidelines for NoSQL,\npartitioning, queries, SDK usage, and vector search. 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Use when writing, reviewing,\n  or refactoring code that interacts with Azure Cosmos DB, designing data models,\n  optimizing queries, or implementing high-performance database operations.\nmetadata:\n  author: cosmosdb-agent-kit\n  version: \"1.0.0\"\n---\n\n# Azure Cosmos DB Best Practices\n\nComprehensive performance optimization guide for Azure Cosmos DB applications, containing\n73+ rules across 10 categories, prioritized by impact to guide automated\nrefactoring and code generation.\n\n73 individual rule files are in the [rules\u002F](.\u002Frules\u002F) directory, one file per rule,\nsynced from the [AzureCosmosDB\u002Fcosmosdb-agent-kit](https:\u002F\u002Fgithub.com\u002FAzureCosmosDB\u002Fcosmosdb-agent-kit).\nLoad only the relevant rule file(s) when answering a question — do NOT load all files at once.\n\n## When to Apply\n\nReference these guidelines when:\n- Designing data models for Cosmos DB\n- Choosing partition keys\n- Writing or optimizing queries\n- Implementing SDK patterns\n- Reviewing code for performance issues\n- Configuring throughput and scaling\n- Building globally distributed applications\n- Implementing vector search and RAG patterns\n\n## Rule Index\n\nRules are grouped by category prefix. For a given question, load files matching\nthe relevant prefix (e.g., `model-*.md` for data modeling, `sdk-*.md` for SDK usage).\nSee [rules\u002F_sections.md](rules\u002F_sections.md) for category descriptions.\n\n### 1. Data Modeling — CRITICAL (prefix: `model-`)\n\n- [model-embed-related.md](rules\u002Fmodel-embed-related.md) — Embed related data retrieved together\n- [model-reference-large.md](rules\u002Fmodel-reference-large.md) — Reference data when items grow large\n- [model-avoid-2mb-limit.md](rules\u002Fmodel-avoid-2mb-limit.md) — Keep items well under 2MB limit\n- [model-id-constraints.md](rules\u002Fmodel-id-constraints.md) — Follow ID value length and character constraints\n- [model-nesting-depth.md](rules\u002Fmodel-nesting-depth.md) — Stay within 128-level nesting depth limit\n- [model-numeric-precision.md](rules\u002Fmodel-numeric-precision.md) — Understand IEEE 754 numeric precision limits\n- [model-denormalize-reads.md](rules\u002Fmodel-denormalize-reads.md) — Denormalize for read-heavy workloads\n- [model-schema-versioning.md](rules\u002Fmodel-schema-versioning.md) — Version your document schemas\n- [model-type-discriminator.md](rules\u002Fmodel-type-discriminator.md) — Use type discriminators for polymorphic data\n- [model-json-serialization.md](rules\u002Fmodel-json-serialization.md) — Handle JSON serialization correctly\n- [model-relationship-references.md](rules\u002Fmodel-relationship-references.md) — Use ID references with transient hydration\n\n### 2. Partition Key Design — CRITICAL (prefix: `partition-`)\n\n- [partition-high-cardinality.md](rules\u002Fpartition-high-cardinality.md) — Choose high-cardinality partition keys\n- [partition-avoid-hotspots.md](rules\u002Fpartition-avoid-hotspots.md) — Distribute writes evenly\n- [partition-hierarchical.md](rules\u002Fpartition-hierarchical.md) — Use hierarchical partition keys for flexibility\n- [partition-query-patterns.md](rules\u002Fpartition-query-patterns.md) — Align partition key with query patterns\n- [partition-synthetic-keys.md](rules\u002Fpartition-synthetic-keys.md) — Create synthetic keys when needed\n- [partition-key-length.md](rules\u002Fpartition-key-length.md) — Respect partition key value length limits\n- [partition-20gb-limit.md](rules\u002Fpartition-20gb-limit.md) — Plan for 20GB logical partition limit\n\n### 3. Query Optimization — HIGH (prefix: `query-`)\n\n- [query-avoid-cross-partition.md](rules\u002Fquery-avoid-cross-partition.md) — Minimize cross-partition queries\n- [query-use-projections.md](rules\u002Fquery-use-projections.md) — Project only needed fields\n- [query-pagination.md](rules\u002Fquery-pagination.md) — Use continuation tokens for pagination\n- [query-avoid-scans.md](rules\u002Fquery-avoid-scans.md) — Avoid full container scans\n- [query-parameterize.md](rules\u002Fquery-parameterize.md) — Use parameterized queries\n- [query-order-filters.md](rules\u002Fquery-order-filters.md) — Order filters by selectivity\n\n### 4. SDK Best Practices — HIGH (prefix: `sdk-`)\n\n- [sdk-singleton-client.md](rules\u002Fsdk-singleton-client.md) — Reuse CosmosClient as singleton\n- [sdk-async-api.md](rules\u002Fsdk-async-api.md) — Use async APIs for throughput\n- [sdk-retry-429.md](rules\u002Fsdk-retry-429.md) — Handle 429s with retry-after\n- [sdk-connection-mode.md](rules\u002Fsdk-connection-mode.md) — Use Direct mode for production\n- [sdk-preferred-regions.md](rules\u002Fsdk-preferred-regions.md) — Configure preferred regions\n- [sdk-excluded-regions.md](rules\u002Fsdk-excluded-regions.md) — Exclude regions experiencing issues\n- [sdk-availability-strategy.md](rules\u002Fsdk-availability-strategy.md) — Configure availability strategy for resilience\n- [sdk-circuit-breaker.md](rules\u002Fsdk-circuit-breaker.md) — Use circuit breaker for fault tolerance\n- [sdk-diagnostics.md](rules\u002Fsdk-diagnostics.md) — Log diagnostics for troubleshooting\n- [sdk-serialization-enums.md](rules\u002Fsdk-serialization-enums.md) — Serialize enums as strings not integers\n- [sdk-emulator-ssl.md](rules\u002Fsdk-emulator-ssl.md) — Configure SSL and connection mode for Cosmos DB Emulator\n- [sdk-etag-concurrency.md](rules\u002Fsdk-etag-concurrency.md) — Use ETags for optimistic concurrency\n- [sdk-java-content-response.md](rules\u002Fsdk-java-content-response.md) — Enable content response on write operations (Java)\n- [sdk-java-cosmos-config.md](rules\u002Fsdk-java-cosmos-config.md) — Configure Cosmos DB in Spring Boot with dependent beans\n- [sdk-java-spring-boot-versions.md](rules\u002Fsdk-java-spring-boot-versions.md) — Match Java version to Spring Boot requirements\n- [sdk-local-dev-config.md](rules\u002Fsdk-local-dev-config.md) — Configure local development to avoid cloud conflicts\n- [sdk-newtonsoft-dependency.md](rules\u002Fsdk-newtonsoft-dependency.md) — Explicitly reference Newtonsoft.Json package (.NET)\n- [sdk-spring-data-annotations.md](rules\u002Fsdk-spring-data-annotations.md) — Annotate entities for Spring Data Cosmos\n- [sdk-spring-data-repository.md](rules\u002Fsdk-spring-data-repository.md) — Use CosmosRepository correctly\n\n### 5. Indexing Strategies — MEDIUM-HIGH (prefix: `index-`)\n\n- [index-exclude-unused.md](rules\u002Findex-exclude-unused.md) — Exclude paths never queried\n- [index-composite.md](rules\u002Findex-composite.md) — Use composite indexes for ORDER BY\n- [index-spatial.md](rules\u002Findex-spatial.md) — Add spatial indexes for geo queries\n- [index-range-vs-hash.md](rules\u002Findex-range-vs-hash.md) — Choose appropriate index types\n- [index-lazy-consistent.md](rules\u002Findex-lazy-consistent.md) — Understand indexing modes\n\n### 6. Throughput & Scaling — MEDIUM (prefix: `throughput-`)\n\n- [throughput-autoscale.md](rules\u002Fthroughput-autoscale.md) — Use autoscale for variable workloads\n- [throughput-right-size.md](rules\u002Fthroughput-right-size.md) — Right-size provisioned throughput\n- [throughput-serverless.md](rules\u002Fthroughput-serverless.md) — Consider serverless for dev\u002Ftest\n- [throughput-burst.md](rules\u002Fthroughput-burst.md) — Understand burst capacity\n- [throughput-container-vs-database.md](rules\u002Fthroughput-container-vs-database.md) — Choose allocation level wisely\n\n### 7. Global Distribution — MEDIUM (prefix: `global-`)\n\n- [global-multi-region.md](rules\u002Fglobal-multi-region.md) — Configure multi-region writes\n- [global-consistency.md](rules\u002Fglobal-consistency.md) — Choose appropriate consistency level\n- [global-conflict-resolution.md](rules\u002Fglobal-conflict-resolution.md) — Implement conflict resolution\n- [global-failover.md](rules\u002Fglobal-failover.md) — Configure automatic failover\n- [global-read-regions.md](rules\u002Fglobal-read-regions.md) — Add read regions near users\n- [global-zone-redundancy.md](rules\u002Fglobal-zone-redundancy.md) — Enable zone redundancy for HA\n\n### 8. Monitoring & Diagnostics — LOW-MEDIUM (prefix: `monitoring-`)\n\n- [monitoring-ru-consumption.md](rules\u002Fmonitoring-ru-consumption.md) — Track RU consumption\n- [monitoring-latency.md](rules\u002Fmonitoring-latency.md) — Monitor P99 latency\n- [monitoring-throttling.md](rules\u002Fmonitoring-throttling.md) — Alert on throttling\n- [monitoring-azure-monitor.md](rules\u002Fmonitoring-azure-monitor.md) — Integrate Azure Monitor\n- [monitoring-diagnostic-logs.md](rules\u002Fmonitoring-diagnostic-logs.md) — Enable diagnostic logging\n\n### 9. Design Patterns — HIGH (prefix: `pattern-`)\n\n- [pattern-change-feed-materialized-views.md](rules\u002Fpattern-change-feed-materialized-views.md) — Use Change Feed for materialized views\n- [pattern-efficient-ranking.md](rules\u002Fpattern-efficient-ranking.md) — Use count-based or cached approaches for ranking\n- [pattern-service-layer-relationships.md](rules\u002Fpattern-service-layer-relationships.md) — Use a service layer to hydrate document references\n\n### 10. Vector Search — HIGH (prefix: `vector-`)\n\n- [vector-enable-feature.md](rules\u002Fvector-enable-feature.md) — Enable vector search feature on account\n- [vector-embedding-policy.md](rules\u002Fvector-embedding-policy.md) — Define vector embedding policy on container\n- [vector-index-type.md](rules\u002Fvector-index-type.md) — Configure vector indexes (QuantizedFlat or DiskANN)\n- [vector-distance-query.md](rules\u002Fvector-distance-query.md) — Use VectorDistance() for similarity search\n- [vector-normalize-embeddings.md](rules\u002Fvector-normalize-embeddings.md) — Normalize embeddings for cosine similarity\n- [vector-repository-pattern.md](rules\u002Fvector-repository-pattern.md) — Implement repository pattern for vector search\n\n## How to Use\n\nEach rule is a separate file under [rules\u002F](.\u002Frules\u002F). When answering a Cosmos DB question,\nread only the relevant rule file(s) based on the prefix matching the topic:\n\n- Data modeling question → read `rules\u002Fmodel-*.md` files\n- Partition key question → read `rules\u002Fpartition-*.md` files\n- SDK\u002Fclient question → read `rules\u002Fsdk-*.md` files\n- etc.\n\nEach rule file contains:\n- Brief explanation of why it matters\n- Incorrect code example with explanation\n- Correct code example with explanation\n- Additional context and references\n\nSource: [AzureCosmosDB\u002Fcosmosdb-agent-kit](https:\u002F\u002Fgithub.com\u002FAzureCosmosDB\u002Fcosmosdb-agent-kit\u002Ftree\u002Fmain\u002Fskills\u002Fcosmosdb-best-practices\u002Frules)\n",{"data":40,"body":44},{"name":4,"license":31,"description":6,"metadata":41},{"author":42,"version":43},"cosmosdb-agent-kit","1.0.0",{"type":45,"children":46},"root",[47,56,62,86,93,98,143,149,178,193,317,330,410,423,492,505,717,730,788,801,859,872,941,954,1012,1025,1061,1074,1143,1149,1160,1205,1210,1233],{"type":48,"tag":49,"props":50,"children":52},"element","h1",{"id":51},"azure-cosmos-db-best-practices",[53],{"type":54,"value":55},"text","Azure Cosmos DB Best Practices",{"type":48,"tag":57,"props":58,"children":59},"p",{},[60],{"type":54,"value":61},"Comprehensive performance optimization guide for Azure Cosmos DB applications, containing\n73+ rules across 10 categories, prioritized by impact to guide automated\nrefactoring and code generation.",{"type":48,"tag":57,"props":63,"children":64},{},[65,67,74,76,84],{"type":54,"value":66},"73 individual rule files are in the ",{"type":48,"tag":68,"props":69,"children":71},"a",{"href":70},".\u002Frules\u002F",[72],{"type":54,"value":73},"rules\u002F",{"type":54,"value":75}," directory, one file per rule,\nsynced from the ",{"type":48,"tag":68,"props":77,"children":81},{"href":78,"rel":79},"https:\u002F\u002Fgithub.com\u002FAzureCosmosDB\u002Fcosmosdb-agent-kit",[80],"nofollow",[82],{"type":54,"value":83},"AzureCosmosDB\u002Fcosmosdb-agent-kit",{"type":54,"value":85},".\nLoad only the relevant rule file(s) when answering a question — do NOT load all files at once.",{"type":48,"tag":87,"props":88,"children":90},"h2",{"id":89},"when-to-apply",[91],{"type":54,"value":92},"When to Apply",{"type":48,"tag":57,"props":94,"children":95},{},[96],{"type":54,"value":97},"Reference these guidelines when:",{"type":48,"tag":99,"props":100,"children":101},"ul",{},[102,108,113,118,123,128,133,138],{"type":48,"tag":103,"props":104,"children":105},"li",{},[106],{"type":54,"value":107},"Designing data models for Cosmos DB",{"type":48,"tag":103,"props":109,"children":110},{},[111],{"type":54,"value":112},"Choosing partition keys",{"type":48,"tag":103,"props":114,"children":115},{},[116],{"type":54,"value":117},"Writing or optimizing queries",{"type":48,"tag":103,"props":119,"children":120},{},[121],{"type":54,"value":122},"Implementing SDK patterns",{"type":48,"tag":103,"props":124,"children":125},{},[126],{"type":54,"value":127},"Reviewing code for performance issues",{"type":48,"tag":103,"props":129,"children":130},{},[131],{"type":54,"value":132},"Configuring throughput and scaling",{"type":48,"tag":103,"props":134,"children":135},{},[136],{"type":54,"value":137},"Building globally distributed applications",{"type":48,"tag":103,"props":139,"children":140},{},[141],{"type":54,"value":142},"Implementing vector search and RAG patterns",{"type":48,"tag":87,"props":144,"children":146},{"id":145},"rule-index",[147],{"type":54,"value":148},"Rule Index",{"type":48,"tag":57,"props":150,"children":151},{},[152,154,161,163,169,171,176],{"type":54,"value":153},"Rules are grouped by category prefix. For a given question, load files matching\nthe relevant prefix (e.g., ",{"type":48,"tag":155,"props":156,"children":158},"code",{"className":157},[],[159],{"type":54,"value":160},"model-*.md",{"type":54,"value":162}," for data modeling, ",{"type":48,"tag":155,"props":164,"children":166},{"className":165},[],[167],{"type":54,"value":168},"sdk-*.md",{"type":54,"value":170}," for SDK usage).\nSee ",{"type":48,"tag":68,"props":172,"children":174},{"href":173},"rules\u002F_sections.md",[175],{"type":54,"value":173},{"type":54,"value":177}," for category descriptions.",{"type":48,"tag":179,"props":180,"children":182},"h3",{"id":181},"_1-data-modeling-critical-prefix-model",[183,185,191],{"type":54,"value":184},"1. 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Design Patterns — HIGH (prefix: ",{"type":48,"tag":155,"props":1019,"children":1021},{"className":1020},[],[1022],{"type":54,"value":1023},"pattern-",{"type":54,"value":192},{"type":48,"tag":99,"props":1026,"children":1027},{},[1028,1039,1050],{"type":48,"tag":103,"props":1029,"children":1030},{},[1031,1037],{"type":48,"tag":68,"props":1032,"children":1034},{"href":1033},"rules\u002Fpattern-change-feed-materialized-views.md",[1035],{"type":54,"value":1036},"pattern-change-feed-materialized-views.md",{"type":54,"value":1038}," — Use Change Feed for materialized views",{"type":48,"tag":103,"props":1040,"children":1041},{},[1042,1048],{"type":48,"tag":68,"props":1043,"children":1045},{"href":1044},"rules\u002Fpattern-efficient-ranking.md",[1046],{"type":54,"value":1047},"pattern-efficient-ranking.md",{"type":54,"value":1049}," — Use count-based or cached approaches for ranking",{"type":48,"tag":103,"props":1051,"children":1052},{},[1053,1059],{"type":48,"tag":68,"props":1054,"children":1056},{"href":1055},"rules\u002Fpattern-service-layer-relationships.md",[1057],{"type":54,"value":1058},"pattern-service-layer-relationships.md",{"type":54,"value":1060}," — Use a service layer to hydrate document references",{"type":48,"tag":179,"props":1062,"children":1064},{"id":1063},"_10-vector-search-high-prefix-vector",[1065,1067,1073],{"type":54,"value":1066},"10. Vector Search — HIGH (prefix: ",{"type":48,"tag":155,"props":1068,"children":1070},{"className":1069},[],[1071],{"type":54,"value":1072},"vector-",{"type":54,"value":192},{"type":48,"tag":99,"props":1075,"children":1076},{},[1077,1088,1099,1110,1121,1132],{"type":48,"tag":103,"props":1078,"children":1079},{},[1080,1086],{"type":48,"tag":68,"props":1081,"children":1083},{"href":1082},"rules\u002Fvector-enable-feature.md",[1084],{"type":54,"value":1085},"vector-enable-feature.md",{"type":54,"value":1087}," — Enable vector search feature on account",{"type":48,"tag":103,"props":1089,"children":1090},{},[1091,1097],{"type":48,"tag":68,"props":1092,"children":1094},{"href":1093},"rules\u002Fvector-embedding-policy.md",[1095],{"type":54,"value":1096},"vector-embedding-policy.md",{"type":54,"value":1098}," — Define vector embedding policy on container",{"type":48,"tag":103,"props":1100,"children":1101},{},[1102,1108],{"type":48,"tag":68,"props":1103,"children":1105},{"href":1104},"rules\u002Fvector-index-type.md",[1106],{"type":54,"value":1107},"vector-index-type.md",{"type":54,"value":1109}," — Configure vector indexes (QuantizedFlat or DiskANN)",{"type":48,"tag":103,"props":1111,"children":1112},{},[1113,1119],{"type":48,"tag":68,"props":1114,"children":1116},{"href":1115},"rules\u002Fvector-distance-query.md",[1117],{"type":54,"value":1118},"vector-distance-query.md",{"type":54,"value":1120}," — Use VectorDistance() for similarity search",{"type":48,"tag":103,"props":1122,"children":1123},{},[1124,1130],{"type":48,"tag":68,"props":1125,"children":1127},{"href":1126},"rules\u002Fvector-normalize-embeddings.md",[1128],{"type":54,"value":1129},"vector-normalize-embeddings.md",{"type":54,"value":1131}," — Normalize embeddings for cosine similarity",{"type":48,"tag":103,"props":1133,"children":1134},{},[1135,1141],{"type":48,"tag":68,"props":1136,"children":1138},{"href":1137},"rules\u002Fvector-repository-pattern.md",[1139],{"type":54,"value":1140},"vector-repository-pattern.md",{"type":54,"value":1142}," — Implement repository pattern for vector search",{"type":48,"tag":87,"props":1144,"children":1146},{"id":1145},"how-to-use",[1147],{"type":54,"value":1148},"How to Use",{"type":48,"tag":57,"props":1150,"children":1151},{},[1152,1154,1158],{"type":54,"value":1153},"Each rule is a separate file under ",{"type":48,"tag":68,"props":1155,"children":1156},{"href":70},[1157],{"type":54,"value":73},{"type":54,"value":1159},". When answering a Cosmos DB question,\nread only the relevant rule file(s) based on the prefix matching the topic:",{"type":48,"tag":99,"props":1161,"children":1162},{},[1163,1176,1188,1200],{"type":48,"tag":103,"props":1164,"children":1165},{},[1166,1168,1174],{"type":54,"value":1167},"Data modeling question → read ",{"type":48,"tag":155,"props":1169,"children":1171},{"className":1170},[],[1172],{"type":54,"value":1173},"rules\u002Fmodel-*.md",{"type":54,"value":1175}," files",{"type":48,"tag":103,"props":1177,"children":1178},{},[1179,1181,1187],{"type":54,"value":1180},"Partition key question → read ",{"type":48,"tag":155,"props":1182,"children":1184},{"className":1183},[],[1185],{"type":54,"value":1186},"rules\u002Fpartition-*.md",{"type":54,"value":1175},{"type":48,"tag":103,"props":1189,"children":1190},{},[1191,1193,1199],{"type":54,"value":1192},"SDK\u002Fclient question → read ",{"type":48,"tag":155,"props":1194,"children":1196},{"className":1195},[],[1197],{"type":54,"value":1198},"rules\u002Fsdk-*.md",{"type":54,"value":1175},{"type":48,"tag":103,"props":1201,"children":1202},{},[1203],{"type":54,"value":1204},"etc.",{"type":48,"tag":57,"props":1206,"children":1207},{},[1208],{"type":54,"value":1209},"Each rule file contains:",{"type":48,"tag":99,"props":1211,"children":1212},{},[1213,1218,1223,1228],{"type":48,"tag":103,"props":1214,"children":1215},{},[1216],{"type":54,"value":1217},"Brief explanation of why it matters",{"type":48,"tag":103,"props":1219,"children":1220},{},[1221],{"type":54,"value":1222},"Incorrect code example with explanation",{"type":48,"tag":103,"props":1224,"children":1225},{},[1226],{"type":54,"value":1227},"Correct code example with explanation",{"type":48,"tag":103,"props":1229,"children":1230},{},[1231],{"type":54,"value":1232},"Additional context and references",{"type":48,"tag":57,"props":1234,"children":1235},{},[1236,1238],{"type":54,"value":1237},"Source: ",{"type":48,"tag":68,"props":1239,"children":1242},{"href":1240,"rel":1241},"https:\u002F\u002Fgithub.com\u002FAzureCosmosDB\u002Fcosmosdb-agent-kit\u002Ftree\u002Fmain\u002Fskills\u002Fcosmosdb-best-practices\u002Frules",[80],[1243],{"type":54,"value":83},{"items":1245,"total":1430},[1246,1265,1283,1302,1319,1335,1354,1366,1378,1396,1404,1417],{"slug":1247,"name":1247,"fn":1248,"description":1249,"org":1250,"tags":1251,"stars":28,"repoUrl":29,"updatedAt":1264},"amazon-location-service","integrate Amazon Location Service APIs","Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1252,1255,1258,1261],{"name":1253,"slug":1254,"type":15},"API Development","api-development",{"name":1256,"slug":1257,"type":15},"AWS","aws",{"name":1259,"slug":1260,"type":15},"Maps","maps",{"name":1262,"slug":1263,"type":15},"Navigation","navigation","2026-07-12T08:13:53.294026",{"slug":1266,"name":1266,"fn":1267,"description":1268,"org":1269,"tags":1270,"stars":28,"repoUrl":29,"updatedAt":1282},"amplify-workflow","build full-stack apps with AWS Amplify","Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync\u002FDynamoDB including schema modeling, enum types, relationships, authorization rules), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify\u002F directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM\u002FCDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1271,1274,1275,1276,1279],{"name":1272,"slug":1273,"type":15},"Auth","auth",{"name":1256,"slug":1257,"type":15},{"name":26,"slug":27,"type":15},{"name":1277,"slug":1278,"type":15},"Frontend","frontend",{"name":1280,"slug":1281,"type":15},"TypeScript","typescript","2026-07-12T08:13:47.134012",{"slug":1284,"name":1284,"fn":1285,"description":1286,"org":1287,"tags":1288,"stars":28,"repoUrl":29,"updatedAt":1301},"analyzer","analyze queried data for trends","Analyze queried data for trends, week-over-week comparisons, distributions, funnels, cohorts, top-N lists, anomalies, sanity checks, and report-ready findings. Use after or alongside ClickHouse queries when the user wants insight rather than raw rows.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1289,1292,1295,1298],{"name":1290,"slug":1291,"type":15},"Analytics","analytics",{"name":1293,"slug":1294,"type":15},"ClickHouse","clickhouse",{"name":1296,"slug":1297,"type":15},"Data Analysis","data-analysis",{"name":1299,"slug":1300,"type":15},"Statistics","statistics","2026-07-12T08:14:05.606036",{"slug":1303,"name":1303,"fn":1304,"description":1305,"org":1306,"tags":1307,"stars":28,"repoUrl":29,"updatedAt":1318},"artifact-management","manage and organize analysis artifacts","Save, organize, and describe reusable analysis artifacts such as SQL, result snapshots, CSV exports, summaries, caveats, plots, and report-ready files. Use when users ask to save, export, share, cite, reproduce, or organize data-analysis outputs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1308,1309,1312,1315],{"name":1296,"slug":1297,"type":15},{"name":1310,"slug":1311,"type":15},"Productivity","productivity",{"name":1313,"slug":1314,"type":15},"Reporting","reporting",{"name":1316,"slug":1317,"type":15},"SQL","sql","2026-07-12T08:14:09.265555",{"slug":1320,"name":1320,"fn":1321,"description":1322,"org":1323,"tags":1324,"stars":28,"repoUrl":29,"updatedAt":1334},"attorney-assist","connect with attorneys for legal consultation","Connects the user with a LegalZoom attorney for legal consultation. Use when a user asks about attorneys, lawyers, or legal help, or when contract review reveals high risks or low-confidence findings.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1325,1328,1331],{"name":1326,"slug":1327,"type":15},"Contracts","contracts",{"name":1329,"slug":1330,"type":15},"Legal","legal",{"name":1332,"slug":1333,"type":15},"Risk Assessment","risk-assessment","2026-07-12T08:13:45.878361",{"slug":1336,"name":1336,"fn":1337,"description":1338,"org":1339,"tags":1340,"stars":28,"repoUrl":29,"updatedAt":1353},"building-pydantic-ai-agents","build AI agents with Pydantic AI","Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add tools\u002Fcapabilities, defer capability loading, stream output, define agents from YAML, or test agent behavior.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1341,1344,1347,1350],{"name":1342,"slug":1343,"type":15},"Agents","agents",{"name":1345,"slug":1346,"type":15},"LLM","llm",{"name":1348,"slug":1349,"type":15},"Multi-Agent","multi-agent",{"name":1351,"slug":1352,"type":15},"Python","python","2026-07-12T08:14:01.893781",{"slug":1294,"name":1294,"fn":1355,"description":1356,"org":1357,"tags":1358,"stars":28,"repoUrl":29,"updatedAt":1365},"query ClickHouse databases via CLI","Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal using the official clickhousectl CLI, including the browser OAuth login flow. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate clickhousectl. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see Scope).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1359,1360,1363,1364],{"name":1290,"slug":1291,"type":15},{"name":1361,"slug":1362,"type":15},"CLI","cli",{"name":1293,"slug":1294,"type":15},{"name":26,"slug":27,"type":15},"2026-07-12T08:14:06.829692",{"slug":1367,"name":1367,"fn":1368,"description":1369,"org":1370,"tags":1371,"stars":28,"repoUrl":29,"updatedAt":1377},"cline-session-history","search and browse Cline session history","Search and browse Cline session history. Use when the user asks to find, list, inspect, or export Cline sessions by time period, prompt content, status, model, provider, source, mode, workspace, or other criteria. Also use when the user wants to read a session transcript or export sessions to a directory. Trigger phrases include \"find my session\", \"search my session history\", \"show me past sessions\", \"what was that session where\", \"find the session that started with\", and any mention of past Cline conversations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1372,1373,1376],{"name":1342,"slug":1343,"type":15},{"name":1374,"slug":1375,"type":15},"History","history",{"name":1310,"slug":1311,"type":15},"2026-07-19T06:03:13.945151",{"slug":1379,"name":1379,"fn":1380,"description":1381,"org":1382,"tags":1383,"stars":28,"repoUrl":29,"updatedAt":1395},"convex-design","build reactive backends with Convex","Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries\u002Fmutations\u002Factions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM\u002Fagent workflows on Convex's one-platform stack.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1384,1385,1388,1389,1392],{"name":1272,"slug":1273,"type":15},{"name":1386,"slug":1387,"type":15},"Backend","backend",{"name":26,"slug":27,"type":15},{"name":1390,"slug":1391,"type":15},"Real-time","real-time",{"name":1393,"slug":1394,"type":15},"Storage","storage","2026-07-12T08:13:37.101253",{"slug":4,"name":4,"fn":5,"description":6,"org":1397,"tags":1398,"stars":28,"repoUrl":29,"updatedAt":30},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1399,1400,1401,1402,1403],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":26,"slug":27,"type":15},{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"slug":1405,"name":1405,"fn":1406,"description":1407,"org":1408,"tags":1409,"stars":28,"repoUrl":29,"updatedAt":1416},"data-analyst","analyze ClickHouse analytics data","Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1410,1411,1412,1415],{"name":1290,"slug":1291,"type":15},{"name":1293,"slug":1294,"type":15},{"name":1413,"slug":1414,"type":15},"Dashboards","dashboards",{"name":1296,"slug":1297,"type":15},"2026-07-12T08:13:31.975246",{"slug":1418,"name":1418,"fn":1419,"description":1420,"org":1421,"tags":1422,"stars":28,"repoUrl":29,"updatedAt":1429},"dataproc-skills","manage Dataproc clusters and jobs","Skills to interact with your Dataproc clusters and jobs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1423,1426],{"name":1424,"slug":1425,"type":15},"Data Engineering","data-engineering",{"name":1427,"slug":1428,"type":15},"Operations","operations","2026-07-12T08:13:42.179275",45,{"items":1432,"total":1482},[1433,1440,1448,1455,1462,1468,1475],{"slug":1247,"name":1247,"fn":1248,"description":1249,"org":1434,"tags":1435,"stars":28,"repoUrl":29,"updatedAt":1264},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1436,1437,1438,1439],{"name":1253,"slug":1254,"type":15},{"name":1256,"slug":1257,"type":15},{"name":1259,"slug":1260,"type":15},{"name":1262,"slug":1263,"type":15},{"slug":1266,"name":1266,"fn":1267,"description":1268,"org":1441,"tags":1442,"stars":28,"repoUrl":29,"updatedAt":1282},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1443,1444,1445,1446,1447],{"name":1272,"slug":1273,"type":15},{"name":1256,"slug":1257,"type":15},{"name":26,"slug":27,"type":15},{"name":1277,"slug":1278,"type":15},{"name":1280,"slug":1281,"type":15},{"slug":1284,"name":1284,"fn":1285,"description":1286,"org":1449,"tags":1450,"stars":28,"repoUrl":29,"updatedAt":1301},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1451,1452,1453,1454],{"name":1290,"slug":1291,"type":15},{"name":1293,"slug":1294,"type":15},{"name":1296,"slug":1297,"type":15},{"name":1299,"slug":1300,"type":15},{"slug":1303,"name":1303,"fn":1304,"description":1305,"org":1456,"tags":1457,"stars":28,"repoUrl":29,"updatedAt":1318},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1458,1459,1460,1461],{"name":1296,"slug":1297,"type":15},{"name":1310,"slug":1311,"type":15},{"name":1313,"slug":1314,"type":15},{"name":1316,"slug":1317,"type":15},{"slug":1320,"name":1320,"fn":1321,"description":1322,"org":1463,"tags":1464,"stars":28,"repoUrl":29,"updatedAt":1334},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1465,1466,1467],{"name":1326,"slug":1327,"type":15},{"name":1329,"slug":1330,"type":15},{"name":1332,"slug":1333,"type":15},{"slug":1336,"name":1336,"fn":1337,"description":1338,"org":1469,"tags":1470,"stars":28,"repoUrl":29,"updatedAt":1353},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1471,1472,1473,1474],{"name":1342,"slug":1343,"type":15},{"name":1345,"slug":1346,"type":15},{"name":1348,"slug":1349,"type":15},{"name":1351,"slug":1352,"type":15},{"slug":1294,"name":1294,"fn":1355,"description":1356,"org":1476,"tags":1477,"stars":28,"repoUrl":29,"updatedAt":1365},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1478,1479,1480,1481],{"name":1290,"slug":1291,"type":15},{"name":1361,"slug":1362,"type":15},{"name":1293,"slug":1294,"type":15},{"name":26,"slug":27,"type":15},43]