[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-mongodb-mongodb-natural-language-querying-zh-CN":3,"guides-for-mongodb-mongodb-natural-language-querying":515,"similar-k17b76ft8ramd1xfapnvxkw2ph86n05c-zh-CN":516},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":239,"isFallback":224,"parentExtension":243,"providers":301,"relations":305,"repo":307,"tags":512,"workflow":513},1778694391552.7004,"k17b76ft8ramd1xfapnvxkw2ph86n05c",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"使用自然语言生成只读 MongoDB 查询 (find) 或聚合管道，并提供集合架构上下文和示例文档。当用户要求编写、创建或生成 MongoDB 查询时、希望在 MongoDB 中过滤/查询/聚合数据时、询问“如何查询...”时、需要查询语法帮助时、或讨论查找/过滤/分组 MongoDB 文档时，请使用此技能。不处理 Atlas Search（$search 运算符）、向量/语义搜索（$vectorSearch 运算符）、模糊匹配、自动完成索引或相关性评分 - 请为此使用 search-and-ai。不分析或优化现有查询 - 请为此使用 mongodb-query-optimizer。不处理涉及写入操作的聚合管道。需要 MongoDB MCP 服务器。",{"claudeCode":12},"mongodb/agent-skills","mongodb-natural-language-querying","https://github.com/mongodb/agent-skills",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":222,"workflow":237},1778694391552.7007,"kn7fjep1pds0g5g2m9zn1zx5ax86mjkr","zh-CN",{"checks":20,"evaluatedAt":192,"extensionSummary":193,"features":194,"nonGoals":200,"promptVersionExtension":204,"promptVersionScoring":205,"purpose":206,"rationale":207,"score":208,"summary":209,"tags":210,"tier":216,"useCases":217},[21,26,29,32,36,39,43,48,51,54,58,62,65,69,72,75,78,81,84,87,91,95,99,103,107,110,114,117,121,124,127,130,133,136,139,143,147,150,153,157,160,163,166,169,173,176,179,182,185,189],{"category":22,"check":23,"severity":24,"summary":25},"Practical Utility","Problem relevance","pass","描述清楚地说明了从自然语言生成 MongoDB 只读查询和聚合管道的问题，包括具体的用例和场景。",{"category":22,"check":27,"severity":24,"summary":28},"Unique selling proposition","通过提供集合架构上下文、示例文档以及遵守查询优化和验证的最佳实践，该技能提供了优于默认 LLM 行为的独特优势。",{"category":22,"check":30,"severity":24,"summary":31},"Production readiness","该技能似乎已为生产做好准备，提供查询生成工具，并概述了收集上下文、验证字段和格式化响应的清晰流程。",{"category":33,"check":34,"severity":24,"summary":35},"Scope","Single responsibility principle","该技能仅专注于生成只读 MongoDB 查询和聚合管道，具有明确的非目标，符合单一职责原则。",{"category":33,"check":37,"severity":24,"summary":38},"Description quality","描述准确地反映了该技能的功能，包括其对只读查询的关注、Atlas Search 等特定非目标，以及对 MCP 服务器的要求。",{"category":40,"check":41,"severity":24,"summary":42},"Invocation","Scoped tools","该技能使用了特定的 MCP 工具，如 `list-databases`、`list-collections`、`collection-indexes`、`collection-schema` 和 `find`，这些工具范围明确且界定清晰。",{"category":44,"check":45,"severity":46,"summary":47},"Documentation","Configuration & parameter reference","not_applicable","除了对 MCP 服务器的隐含要求（已在外部记录）之外，该技能本身没有暴露明确的参数或配置选项。",{"category":33,"check":49,"severity":24,"summary":50},"Tool naming","MCP 工具名称具有描述性，在 MongoDB 域内使用了清晰的动词-名词结构。",{"category":33,"check":52,"severity":24,"summary":53},"Minimal I/O surface","工具架构似乎只请求必要的信息，并且输出格式是结构化的，专门用于查询生成。",{"category":55,"check":56,"severity":24,"summary":57},"License","License usability","该扩展根据 Apache-2.0 许可证授权，这是一个宽松的开源许可证。",{"category":59,"check":60,"severity":24,"summary":61},"Maintenance","Commit recency","存储库显示了最近的提交，表明正在积极维护。",{"category":59,"check":63,"severity":46,"summary":64},"Dependency Management","该技能本身似乎没有直接的第三方依赖项，除了 MCP 服务器（这是先决条件）。",{"category":66,"check":67,"severity":46,"summary":68},"Security","Secret Management","该技能的功能是生成查询，不直接处理或公开机密信息。",{"category":66,"check":70,"severity":24,"summary":71},"Injection","该技能专注于生成查询代码，似乎不执行任意指令或将不可信的第三方数据作为代码加载。",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Supply-Chain Grenades","该技能在运行时不获取远程内容进行执行，所有必要的工具都是捆绑存储库或外部 MCP 服务器的一部分。",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox Isolation","该技能的操作仅限于生成查询代码，不涉及其预期范围之外的文件系统修改。",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox escape primitives","没有迹象表明该技能的逻辑中存在分离的进程启动或拒绝重试循环。",{"category":66,"check":82,"severity":24,"summary":83},"Data Exfiltration","该技能的目的是生成查询，而不是窃取数据。它与 MCP 服务器进行交互以获取架构和数据，但不会将这些数据发送给任意第三方。",{"category":66,"check":85,"severity":24,"summary":86},"Hidden Text Tricks","捆绑的 SKILL.md 文件似乎没有隐藏的操纵技巧或混淆内容。",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Opaque code execution","该技能的逻辑以可读的 markdown 格式呈现，不涉及混淆代码或运行时脚本获取。",{"category":92,"check":93,"severity":24,"summary":94},"Portability","Structural Assumption","该技能主要依赖 MCP 服务器和用户输入提供的信息，而不是对用户项目结构做出假设。",{"category":96,"check":97,"severity":24,"summary":98},"Trust","Issues Attention","最近 90 天内没有未解决的 issue，也没有已关闭的 issue，这表明该项目是新近的或维护良好，目前没有问题。",{"category":100,"check":101,"severity":24,"summary":102},"Versioning","Release Management","该存储库具有最近的提交日期，并且许可证可用，这表明版本稳定且已维护，尽管 frontmatter 中没有明确的版本号。",{"category":104,"check":105,"severity":24,"summary":106},"Execution","Validation","该技能的过程包括根据获取的架构验证字段名，确保查询生成健壮。",{"category":66,"check":108,"severity":24,"summary":109},"Unguarded Destructive Operations","该技能专注于生成只读查询，不执行破坏性操作。",{"category":111,"check":112,"severity":24,"summary":113},"Code Execution","Error Handling","该技能概述了一个清晰的错误处理流程，包括解释为什么无法生成查询以及请求澄清。",{"category":111,"check":115,"severity":46,"summary":116},"Logging","该技能的操作主要是基于提示的生成，不涉及破坏性操作或需要本地审计日志的出站调用。",{"category":118,"check":119,"severity":46,"summary":120},"Compliance","GDPR","该技能根据提供的架构和用户请求生成查询，本身不处理个人数据。",{"category":118,"check":122,"severity":24,"summary":123},"Target market","该技能的功能是数据库查询生成，没有固有的区域限制；它是全球适用的。",{"category":92,"check":125,"severity":24,"summary":126},"Runtime stability","该技能依赖于 MCP 服务器和标准的 MongoDB 交互，似乎没有对特定操作系统或 shell 环境做出假设。",{"category":44,"check":128,"severity":24,"summary":129},"README","README 文件提供了清晰的安装说明，适用于各种平台，并提供了关于 agent skills collection 的背景信息。",{"category":33,"check":131,"severity":24,"summary":132},"Tool surface size","该技能使用了有限的特定 MCP 工具集，远在推荐范围内。",{"category":40,"check":134,"severity":24,"summary":135},"Overlapping near-synonym tools","该技能为不同目的使用了特定的 MCP 工具（例如，schema、indexes、find），并且不公开近乎同义的工具。",{"category":44,"check":137,"severity":24,"summary":138},"Phantom features","所有宣传的功能，例如使用 MCP 工具收集上下文和生成查询，都得到了提供的 SKILL.md 和相关 MCP 工具的支持。",{"category":140,"check":141,"severity":24,"summary":142},"Install","Installation instruction","README 提供了详细的安装说明，适用于多种环境（Claude、Cursor、Codex、Gemini、Copilot CLI、Vercel、本地），并包含复制粘贴命令。",{"category":144,"check":145,"severity":24,"summary":146},"Errors","Actionable error messages","SKILL.md 详细说明了如何处理错误，包括解释原因、请求澄清和建议替代方案。",{"category":104,"check":148,"severity":46,"summary":149},"Pinned dependencies","该技能本身不捆绑带有依赖项的脚本；它依赖于外部 MCP 服务器和其自身管理的依赖项。",{"category":33,"check":151,"severity":46,"summary":152},"Dry-run preview","该技能生成查询，不执行状态更改操作或向外发送数据，因此不适用 dry-run 功能。",{"category":154,"check":155,"severity":46,"summary":156},"Protocol","Idempotent retry & timeouts","该技能是无状态的，用于生成代码；它不执行需要幂等性或超时设置的远程调用或状态更改操作。",{"category":118,"check":158,"severity":46,"summary":159},"Telemetry opt-in","没有迹象表明此技能会发出遥测数据。",{"category":40,"check":161,"severity":24,"summary":162},"Precise Purpose","描述清楚地定义了该技能的目的（生成 MongoDB 只读查询/管道）、其操作的对象（MongoDB 集合）、用户意图（写入/过滤/查询/聚合），并包含明确的非目标。",{"category":40,"check":164,"severity":24,"summary":165},"Concise Frontmatter","Frontmatter 简洁、自包含，并在字符限制内准确总结了核心功能和触发条件。",{"category":44,"check":167,"severity":24,"summary":168},"Concise Body","SKILL.md 结构良好，少于 500 行，并将详细过程委托给文件内的部分，而不是外部文件。",{"category":170,"check":171,"severity":24,"summary":172},"Context","Progressive Disclosure","SKILL.md 组织良好，包含清晰的部分，用于上下文收集、查询生成、最佳实践和错误处理，在单个文件中展示了渐进式披露。",{"category":170,"check":174,"severity":46,"summary":175},"Forked exploration","该技能的主要功能是查询生成，而不是深入探索或代码审查，因此 `context: fork` 不适用。",{"category":22,"check":177,"severity":24,"summary":178},"Usage examples","提供了一个清晰的端到端示例工作流程，展示了用户输入、过程和预期的查询输出。",{"category":22,"check":180,"severity":24,"summary":181},"Edge cases","SKILL.md 解决了潜在问题，例如验证字段名、使用适当的运算符、优化聚合以及处理 geoJSON 格式，以及预防错误。",{"category":111,"check":183,"severity":46,"summary":184},"Tool Fallback","该技能需要 MCP 服务器，没有提到回退路径或替代工具。",{"category":186,"check":187,"severity":24,"summary":188},"Safety","Halt on unexpected state","该技能的错误处理部分指示在无法生成查询时解释原因并请求澄清，这暗示了在意外状态下会停止操作。",{"category":92,"check":190,"severity":24,"summary":191},"Cross-skill coupling","该技能是独立的，其功能定义清晰，没有对其他技能的隐含依赖。",1778694275554,"此技能根据自然语言输入生成只读 MongoDB 查询（find）和聚合管道，并利用集合架构和示例文档作为上下文。它通过 MCP 工具引导用户收集必要信息、分析架构和索引、选择 find 或 aggregation、以及格式化输出。",[195,196,197,198,199],"从自然语言生成 MongoDB find 查询。","从自然语言生成 MongoDB 聚合管道。","利用集合架构进行字段验证。","使用示例文档理解数据模式。","优先使用 find 查询而非聚合管道以简化操作。",[201,202,203],"处理 Atlas Search（$search、$vectorSearch）、模糊匹配、自动完成或相关性评分。","分析或优化现有的 MongoDB 查询。","处理涉及写入操作的聚合管道。","3.0.0","4.4.0","从自然语言生成准确高效的 MongoDB 只读查询和聚合管道，为用户节省时间并减少查询语法错误。","该技能的文档质量非常高，目的明确，用法示例充足，并且错误处理全面，以高标准的质量满足了所有评估标准。",99,"一个高质量的技能，用于从自然语言生成 MongoDB 查询和聚合管道。",[211,212,213,214,215],"mongodb","query-generation","aggregation-pipeline","natural-language","database","verified",[218,219,220,221],"当用户要求编写、创建或生成 MongoDB 查询时。","当用户希望在 MongoDB 中过滤、查询或聚合数据时。","当用户询问 MongoDB 的“如何查询...”时。","将类似 SQL 的请求翻译成 MongoDB 语法。",{"codeQuality":223,"collectedAt":225,"documentation":226,"maintenance":229,"security":233,"testCoverage":235},{"hasLockfile":224},false,1778694262857,{"descriptionLength":227,"readmeSize":228},826,2753,{"closedIssues90d":8,"forks":230,"hasChangelog":224,"openIssues90d":8,"pushedAt":231,"stars":232},20,1778514087000,111,{"hasNpmPackage":224,"license":234,"smitheryVerified":224},"Apache-2.0",{"hasCi":236,"hasTests":224},true,{"updatedAt":238},1778694391552,{"basePath":240,"githubOwner":211,"githubRepo":241,"locale":18,"slug":13,"type":242},"skills/mongodb-natural-language-querying","agent-skills","skill",{"_creationTime":244,"_id":245,"community":246,"display":247,"identity":250,"parentExtension":254,"providers":285,"relations":296,"tags":297,"workflow":298},1778694149049.3462,"k170hje3xzpy2mbkn00agzm38x86mkbz",{"reviewCount":8},{"description":248,"installMethods":249,"name":211,"sourceUrl":14},"Official Claude plugin for MongoDB (MCP Server + Skills). 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Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.","atlas-stream-processing",{"claudeCode":12},"SKILL.md frontmatter at skills/atlas-stream-processing/SKILL.md",[368,370,372,374,376,378,380],{"path":369,"priority":321},"SKILL.md",{"path":371,"priority":344},"references/connection-configs.md",{"path":373,"priority":344},"references/development-workflow.md",{"path":375,"priority":344},"references/mcp-troubleshooting.md",{"path":377,"priority":344},"references/output-diagnostics.md",{"path":379,"priority":344},"references/pipeline-patterns.md",{"path":381,"priority":344},"references/sizing-and-parallelism.md",{"basePath":383,"description":384,"displayName":385,"installMethods":386,"rationale":387,"selectedPaths":388,"source":322,"sourceLanguage":252,"type":242},"skills/mongodb-connection","Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.","mongodb-connection",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-connection/SKILL.md",[389,390],{"path":369,"priority":321},{"path":391,"priority":344},"references/monitoring-guide.md",{"basePath":393,"description":394,"displayName":395,"installMethods":396,"rationale":397,"selectedPaths":398,"source":322,"sourceLanguage":252,"type":242},"skills/mongodb-mcp-setup","Guide users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn't configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don't have the credentials set up.","mongodb-mcp-setup",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-mcp-setup/SKILL.md",[399],{"path":369,"priority":321},{"basePath":240,"description":401,"displayName":13,"installMethods":402,"rationale":403,"selectedPaths":404,"source":322,"sourceLanguage":252,"type":242},"Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks \"how do I query...\", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-natural-language-querying/SKILL.md",[405],{"path":369,"priority":321},{"basePath":407,"description":408,"displayName":409,"installMethods":410,"rationale":411,"selectedPaths":412,"source":322,"sourceLanguage":252,"type":242},"skills/mongodb-query-optimizer","Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: \"How do I optimize this query?\", \"How do I index this?\", \"Why is this query slow?\", \"Can you fix my slow queries?\", \"What are the slow queries on my cluster?\", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.","mongodb-query-optimizer",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-query-optimizer/SKILL.md",[413,414,416,418,420],{"path":369,"priority":321},{"path":415,"priority":344},"references/aggregation-optimization.md",{"path":417,"priority":344},"references/antipattern-examples.md",{"path":419,"priority":344},"references/core-indexing-principles.md",{"path":421,"priority":344},"references/update-query-examples.md",{"basePath":423,"description":424,"displayName":425,"installMethods":426,"rationale":427,"selectedPaths":428,"source":322,"sourceLanguage":252,"type":242},"skills/mongodb-schema-design","MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on \"design schema\", \"embed vs reference\", \"MongoDB data model\", \"schema review\", \"unbounded arrays\", \"one-to-many\", \"tree structure\", \"16MB limit\", \"schema validation\", \"JSON Schema\", \"time series\", \"schema migration\", \"polymorphic\", \"TTL\", \"data lifecycle\", \"archive\", \"index explosion\", \"unnecessary indexes\", \"approximation pattern\", \"document versioning\".","mongodb-schema-design",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-schema-design/SKILL.md",[429,430,432,434,436,438,440,442,444,446,448,450,452,454,456,458,460,462,464],{"path":369,"priority":321},{"path":431,"priority":344},"references/antipattern-excessive-lookups.md",{"path":433,"priority":344},"references/antipattern-unnecessary-collections.md",{"path":435,"priority":344},"references/antipattern-unnecessary-indexes.md",{"path":437,"priority":344},"references/fundamental-document-model.md",{"path":439,"priority":344},"references/fundamental-document-size.md",{"path":441,"priority":344},"references/fundamental-embed-vs-reference.md",{"path":443,"priority":344},"references/fundamental-schema-validation.md",{"path":445,"priority":344},"references/pattern-approximation.md",{"path":447,"priority":344},"references/pattern-archive.md",{"path":449,"priority":344},"references/pattern-attribute.md",{"path":451,"priority":344},"references/pattern-bucket.md",{"path":453,"priority":344},"references/pattern-computed.md",{"path":455,"priority":344},"references/pattern-document-versioning.md",{"path":457,"priority":344},"references/pattern-extended-reference.md",{"path":459,"priority":344},"references/pattern-outlier.md",{"path":461,"priority":344},"references/pattern-polymorphic.md",{"path":463,"priority":344},"references/pattern-schema-versioning.md",{"path":465,"priority":344},"references/pattern-time-series-collections.md",{"basePath":467,"description":468,"displayName":469,"installMethods":470,"rationale":471,"selectedPaths":472,"source":322,"sourceLanguage":252,"type":242},"skills/mongodb-search-and-ai","Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.\n","mongodb-search-and-ai",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-search-and-ai/SKILL.md",[473,474,476,478,480],{"path":369,"priority":321},{"path":475,"priority":344},"references/hybrid-search.md",{"path":477,"priority":344},"references/lexical-search-indexing.md",{"path":479,"priority":344},"references/lexical-search-querying.md",{"path":481,"priority":344},"references/vector-search.md",{"basePath":483,"description":484,"displayName":485,"installMethods":486,"rationale":487,"selectedPaths":488,"source":322,"sourceLanguage":252,"type":242},"tools/review-skill","Review a proposed Agent Skill for structural validity and content quality before publishing. Runs the skill-validator CLI to check for structural issues, scores the skill with an LLM judge, and interprets results to advise SMEs on what to address. Use when a user wants to review, validate, or quality-check an Agent Skill.","review-skill",{"claudeCode":12},"SKILL.md frontmatter at tools/review-skill/SKILL.md",[489,490,493,495],{"path":369,"priority":321},{"path":491,"priority":492},"assets/report.md","low",{"path":494,"priority":344},"references/install-skill-validator.md",{"path":496,"priority":344},"references/llm-scoring.md",{"sources":498},[499],"manual",{"closedIssues90d":8,"description":259,"forks":230,"license":234,"openIssues90d":8,"pushedAt":231,"readmeSize":228,"stars":232,"topics":501},[502,503,504,505,506,507],"agent","claude","cursor","gemini-cli-extension","mcp","skills",{"classifiedAt":509,"discoverAt":510,"extractAt":511,"githubAt":511,"updatedAt":509},1778694148853,1778694144419,1778694146756,[213,215,211,214,212],{"evaluatedAt":514,"extractAt":283,"updatedAt":238},1778694275726,[],[517,539,562,591,619,648],{"_creationTime":518,"_id":519,"community":520,"display":521,"identity":524,"providers":525,"relations":533,"tags":535,"workflow":536},1778694413837.2078,"k1724c581pj4qca8wdevmzkr0586n034",{"reviewCount":8},{"description":522,"installMethods":523,"name":469,"sourceUrl":14},"指导 MongoDB 用户实现和优化 Atlas Search（全文搜索）、Vector Search（语义搜索）和 Hybrid Search 解决方案。当用户需要为文本查询（自动完成、模糊匹配、分面搜索）、语义相似性（嵌入、RAG 应用）或组合方法构建搜索功能时，请使用此技能。当用户需要文本包含、子字符串匹配（“包含”、“包括”、“出现在”）、不区分大小写或多字段文本搜索，或跨多个字段进行具有可变组合的过滤时，也请使用此技能。提供有关选择正确的搜索类型、创建索引、构建查询和使用 MongoDB MCP 服务器优化性能的工作流。\n",{"claudeCode":12},{"basePath":467,"githubOwner":211,"githubRepo":241,"locale":18,"slug":469,"type":242},{"evaluate":526,"extract":532},{"promptVersionExtension":204,"promptVersionScoring":205,"score":287,"tags":527,"targetMarket":270,"tier":216},[211,528,529,530,215,531],"atlas-search","vector-search","hybrid-search","search",{"commitSha":273},{"parentExtensionId":245,"repoId":279,"translatedFrom":534},"k17b18bc1pkwm6r3xttpqzefj586ms2r",[528,215,530,211,531,529],{"evaluatedAt":537,"extractAt":283,"updatedAt":538},1778694322274,1778694413837,{"_creationTime":540,"_id":541,"community":542,"display":543,"identity":547,"providers":548,"relations":556,"tags":558,"workflow":559},1778694375752.5935,"k176q0fcrs34d0qgcw5zcfr7e186mppv",{"reviewCount":8},{"description":544,"installMethods":545,"name":546,"sourceUrl":14},"为任何支持的驱动程序语言优化 MongoDB 客户端连接配置（池、超时、模式）。在处理/更新/审查实例化或配置 MongoDB 客户端（例如，调用 `connect()` 时）、配置连接池、对连接错误（ECONNREFUSED、超时、池耗尽）进行故障排除、优化与连接相关的性能问题时，请使用此技能。这包括构建具有 MongoDB 的无服务器函数、创建使用 MongoDB 的 API 端点、优化高流量 MongoDB 应用程序、创建长期运行任务和并发性，或调试与连接相关的失败等场景。",{"claudeCode":12},"MongoDB Connection Optimizer",{"basePath":383,"githubOwner":211,"githubRepo":241,"locale":18,"slug":385,"type":242},{"evaluate":549,"extract":555},{"promptVersionExtension":204,"promptVersionScoring":205,"score":287,"tags":550,"targetMarket":270,"tier":216},[211,215,551,552,553,554],"connection","performance","optimization","configuration",{"commitSha":273,"license":234},{"parentExtensionId":245,"repoId":279,"translatedFrom":557},"k175wmq2n17n23xzphj2zzt3qs86n3xd",[554,551,215,211,553,552],{"evaluatedAt":560,"extractAt":283,"updatedAt":561},1778694243014,1778694375752,{"_creationTime":563,"_id":564,"community":565,"display":566,"identity":572,"providers":576,"relations":584,"tags":587,"workflow":588},1778696691708.3264,"k179thjzaw5kepc7zhdj9sat3n86mcqp",{"reviewCount":8},{"description":567,"installMethods":568,"name":570,"sourceUrl":571},"Validate pending migrations for foreign key consistency, rollback safety, and best practices",{"claudeCode":569},"ruvnet/ruflo","migrate-validate","https://github.com/ruvnet/ruflo",{"basePath":573,"githubOwner":574,"githubRepo":575,"locale":252,"slug":570,"type":242},"plugins/ruflo-migrations/skills/migrate-validate","ruvnet","ruflo",{"evaluate":577,"extract":583},{"promptVersionExtension":204,"promptVersionScoring":205,"score":287,"tags":578,"targetMarket":270,"tier":216},[215,579,580,581,582,269],"migrations","sql","validation","code-quality",{"commitSha":273},{"parentExtensionId":585,"repoId":586},"k176me0sh9b6bc3gzttnywx4w986njzh","kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[582,215,269,579,580,581],{"evaluatedAt":589,"extractAt":590,"updatedAt":589},1778701008912,1778696691708,{"_creationTime":592,"_id":593,"community":594,"display":595,"identity":601,"providers":604,"relations":612,"tags":615,"workflow":616},1778693180473.1252,"k172br69jq6k4srh8e6fph3yex86mze7",{"reviewCount":8},{"description":596,"installMethods":597,"name":599,"sourceUrl":600},"Connect to Azure Database for PostgreSQL Flexible Server from Node.js/TypeScript using the pg (node-postgres) package. Use for PostgreSQL queries, connection pooling, transactions, and Microsoft Entra ID (passwordless) authentication. Triggers: \"PostgreSQL\", \"postgres\", \"pg client\", \"node-postgres\", \"Azure PostgreSQL connection\", \"PostgreSQL TypeScript\", \"pg Pool\", \"passwordless postgres\".\n",{"claudeCode":598},"microsoft/agent-skills","azure-postgres-ts","https://github.com/microsoft/agent-skills",{"basePath":602,"githubOwner":603,"githubRepo":241,"locale":252,"slug":599,"type":242},".github/plugins/azure-sdk-typescript/skills/azure-postgres-ts","microsoft",{"evaluate":605,"extract":611},{"promptVersionExtension":204,"promptVersionScoring":205,"score":287,"tags":606,"targetMarket":270,"tier":216},[607,608,609,215,610],"postgresql","typescript","azure","node-postgres",{"commitSha":273},{"parentExtensionId":613,"repoId":614},"k178kb88kvde2xfvrp03jpy6cn86nav5","kd77czgnv00rfjm815pcc5xx5986n5t8",[609,215,610,607,608],{"evaluatedAt":617,"extractAt":618,"updatedAt":617},1778695769892,1778693180473,{"_creationTime":620,"_id":621,"community":622,"display":623,"identity":629,"providers":632,"relations":640,"tags":643,"workflow":644},1778694650366.6177,"k178jsxt2xc6pq5dfwhsy826mh86my49",{"reviewCount":8},{"description":624,"installMethods":625,"name":627,"sourceUrl":628},"Neon Serverless Postgres 的使用指南和最佳实践。涵盖入门、使用 Neon 进行本地开发、选择连接方法、Neon 功能、身份验证（@neondatabase/auth）、PostgREST 风格的数据 API（@neondatabase/neon-js）、Neon CLI 以及 Neon 的平台 API/SDK。可用于任何与 Neon 相关的问题。",{"claudeCode":626},"neondatabase/agent-skills","neon-postgres","https://github.com/neondatabase/agent-skills",{"basePath":630,"githubOwner":631,"githubRepo":241,"locale":18,"slug":627,"type":242},"skills/neon-postgres","neondatabase",{"evaluate":633,"extract":639},{"promptVersionExtension":204,"promptVersionScoring":205,"score":287,"tags":634,"targetMarket":270,"tier":216},[635,636,215,637,638],"postgres","neon","documentation","best-practices",{"commitSha":273},{"repoId":641,"translatedFrom":642},"kd7fnpnf2z4z7frgbq47jwrzzh86nx09","k1739tdkkxjmmx9m9gk67e8s5986me1q",[638,215,637,636,635],{"evaluatedAt":645,"extractAt":646,"updatedAt":647},1778694576976,1778694510092,1778694650366,{"_creationTime":649,"_id":650,"community":651,"display":652,"identity":658,"providers":662,"relations":667,"tags":669,"workflow":670},1778687399826.0325,"k17269dg7c9710vn40ysst9cbx86nekj",{"reviewCount":8},{"description":653,"installMethods":654,"name":656,"sourceUrl":657},"Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Provides execution plan analysis, pagination optimization, batch operations, and performance monitoring guidance.",{"claudeCode":655},"github/awesome-copilot","sql-optimization","https://github.com/github/awesome-copilot",{"basePath":659,"githubOwner":660,"githubRepo":661,"locale":252,"slug":656,"type":242},"skills/sql-optimization","github","awesome-copilot",{"evaluate":663,"extract":666},{"promptVersionExtension":204,"promptVersionScoring":205,"score":287,"tags":664,"targetMarket":270,"tier":216},[580,552,553,215,665],"tuning",{"commitSha":273},{"repoId":668},"kd7dsmv976w8rtkqnjjfdtfgks86nnmw",[215,553,552,580,665],{"evaluatedAt":671,"extractAt":672,"updatedAt":671},1778689968064,1778687399826]