[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-skill-mongodb-mongodb-search-and-ai-de":3,"guides-for-mongodb-mongodb-search-and-ai":514,"similar-k1766fag8f403pvmj6st943zyn86nnvf-de":515},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":15,"identity":239,"isFallback":224,"parentExtension":243,"providers":300,"relations":304,"repo":306,"tags":511,"workflow":512},1778694415976.5222,"k1766fag8f403pvmj6st943zyn86nnvf",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":13,"sourceUrl":14},"Leitet MongoDB-Benutzer bei der Implementierung und Optimierung von Atlas Search (Volltext), Vector Search (semantisch) und Hybrid Search-Lösungen an. Verwenden Sie diesen Skill, wenn Benutzer Suchfunktionen für textbasierte Abfragen (Autovervollständigung, Fuzzy-Suche, facettenreiche Suche), semantische Ähnlichkeit (Embeddings, RAG-Anwendungen) oder kombinierte Ansätze erstellen müssen. Verwenden Sie ihn auch, wenn Benutzer Textinhalte, Teilzeichenfolgenübereinstimmungen („enthält“, „beinhaltet“, „erscheint in“), groß-/kleinschreibungsunempfindliche oder mehrfeldige Textsuche oder Filterung über viele Felder mit variablen Kombinationen hinweg benötigen. Bietet Workflows für die Auswahl des richtigen Suchtyps, die Erstellung von Indizes, die Konstruktion von Abfragen und die Optimierung der Leistung mit dem MongoDB MCP-Server.\n",{"claudeCode":12},"mongodb/agent-skills","mongodb-search-and-ai","https://github.com/mongodb/agent-skills",{"_creationTime":16,"_id":17,"extensionId":5,"locale":18,"result":19,"trustSignals":222,"workflow":237},1778694415976.5225,"kn78ncrfnkrc5em5pk6mmvmswh86mh51","de",{"checks":20,"evaluatedAt":191,"extensionSummary":192,"features":193,"nonGoals":199,"promptVersionExtension":203,"promptVersionScoring":204,"purpose":205,"rationale":206,"score":207,"summary":208,"tags":209,"tier":216,"useCases":217},[21,26,29,32,36,39,43,47,50,53,57,61,65,69,72,75,78,81,84,87,91,95,99,103,107,110,113,116,120,123,126,129,132,135,138,142,146,150,153,157,160,163,166,169,173,176,179,182,185,188],{"category":22,"check":23,"severity":24,"summary":25},"Praktischer Nutzen","Relevanz des Problems","pass","Die Beschreibung benennt klar das Problem, MongoDB-Benutzer bei der Implementierung und Optimierung von Atlas Search-Lösungen anzuleiten, einschließlich Text-, Vektor- und Hybridsuche.",{"category":22,"check":27,"severity":24,"summary":28},"Alleinstellungsmerkmal","Der Skill bietet strukturierte Workflows und Anleitungen zur Auswahl von Suchtypen, zur Erstellung von Indizes und zur Optimierung von Abfragen, was über die grundlegende API-Interaktion hinausgeht und einen erheblichen Mehrwert gegenüber einer einfachen Aufforderung bietet.",{"category":22,"check":30,"severity":24,"summary":31},"Produktionsreife","Der Skill deckt den gesamten Lebenszyklus von der Entdeckung und Indexerstellung bis zur Abfrage und Optimierung ab, mit klaren Workflows und Prüfungen auf Versionskompatibilität, was auf seine Produktionsreife hindeutet.",{"category":33,"check":34,"severity":24,"summary":35},"Umfang","Prinzip der einzigen Verantwortung","Der Skill konzentriert sich auf die Implementierung und Optimierung von MongoDB Atlas Search und deckt lexikalische, Vektor- und Hybridsuche in einem kohärenten und gut definierten Umfang ab.",{"category":33,"check":37,"severity":24,"summary":38},"Qualität der Beschreibung","Die angezeigte Beschreibung spiegelt genau die Fähigkeiten des Skills wider, ist gut strukturiert und umreißt klar die Arten von Suchfunktionen, durch die er Benutzer führt.",{"category":40,"check":41,"severity":24,"summary":42},"Aufruf","Geltungsbereich von Tools","Der Skill verwendet spezifische Tools wie `list-databases`, `collection-schema`, `collection-indexes`, `atlas-inspect-cluster`, `create-index` und `aggregate` und nicht nur einen einzigen Generalistenbefehl.",{"category":44,"check":45,"severity":24,"summary":46},"Dokumentation","Konfigurations- und Parameterreferenz","Alle relevanten Parameter für Indexerstellung, Abfragen und Versionsprüfungen sind im SKILL.md und in den Referenzdateien dokumentiert.",{"category":33,"check":48,"severity":24,"summary":49},"Tool-Namensgebung","Die verwendeten Tools (z. B. `create-index`, `aggregate`) sind beschreibend und folgen der Verb-Nomen-Konvention.",{"category":33,"check":51,"severity":24,"summary":52},"Minimale I/O-Oberfläche","Die Ein- und Ausgaben des Skills sind durch die aufgerufenen MCP-Tools und die angeforderten/zurückgegebenen strukturierten Daten gut definiert und vermeiden unnötige Datenüberfülle.",{"category":54,"check":55,"severity":24,"summary":56},"Lizenz","Lizenznutzbarkeit","Die Erweiterung ist unter Apache-2.0 lizenziert, einer permissiven Open-Source-Lizenz, wie aus der gebündelten LICENSE-Datei ersichtlich ist.",{"category":58,"check":59,"severity":24,"summary":60},"Wartung","Aktualität der Commits","Der letzte Commit war am 2026-05-11, was innerhalb der letzten 90 Tage liegt.",{"category":58,"check":62,"severity":63,"summary":64},"Abhängigkeitsverwaltung","not_applicable","Es wurden keine Drittanbieterabhängigkeiten erkannt, die eine spezielle Verwaltung erfordern.",{"category":66,"check":67,"severity":63,"summary":68},"Sicherheit","Geheimnisverwaltung","Der Skill verarbeitet keine Geheimnisse, da er für die Authentifizierung auf den MCP-Server angewiesen ist, der extern konfiguriert wird.",{"category":66,"check":70,"severity":24,"summary":71},"Injektion","Der Skill lädt keine externen Daten und ruft keine Remote-URLs ab. Benutzereingaben werden als Daten und nicht als Anweisungen behandelt.",{"category":66,"check":73,"severity":24,"summary":74},"Transitive Lieferketten-Granaten","Der Skill arbeitet ausschließlich mit seinen gebündelten Inhalten und ruft zur Laufzeit keinen externen Code oder Daten ab.",{"category":66,"check":76,"severity":24,"summary":77},"Sandbox-Isolierung","Der Skill interagiert mit der Umgebung über definierte MCP-Tools und versucht nicht, Dateien außerhalb seines zugewiesenen Geltungsbereichs zu ändern.",{"category":66,"check":79,"severity":24,"summary":80},"Sandbox-Escape-Primitive","Im Code des Skills wurden keine separaten Prozessaufrufe oder Wiederholungsschleifen für abgelehnte Toolaufrufe gefunden.",{"category":66,"check":82,"severity":24,"summary":83},"Datenexfiltration","Der Skill enthält keine Anweisungen zum Lesen oder Übermitteln vertraulicher Daten an Dritte.",{"category":66,"check":85,"severity":24,"summary":86},"Versteckte Texttricks","Der gebündelte Inhalt ist frei von versteckten Steuerungs-Tricks und alle Beschreibungen verwenden sauberes druckbares ASCII.",{"category":88,"check":89,"severity":24,"summary":90},"Hooks","Undurchsichtige Codeausführung","Die Logik des Skills ist im lesbaren SKILL.md-Text enthalten und beinhaltet keinen verschleierten oder minimierten Code.",{"category":92,"check":93,"severity":24,"summary":94},"Portabilität","Strukturelle Annahme","Der Workflow des Skills geht von Standard-MongoDB-Atlas-Interaktionen aus und verlässt sich nicht auf spezifische Dateistrukturen des Benutzerprojekts.",{"category":96,"check":97,"severity":24,"summary":98},"Vertrauen","Aufmerksamkeit für Probleme","Es gibt 0 offene und 0 geschlossene Issues in den letzten 90 Tagen, was auf ein geringes Volumen an Aktivitäten oder Problemen hindeutet.",{"category":100,"check":101,"severity":24,"summary":102},"Versionierung","Release-Management","Das Repository enthält eine CHANGELOG.md und verwendet semantische Versionierung in seinen Installationsanweisungen (z. B. `mongodb-mcp-server@1`), was auf ein gutes Release-Management hindeutet.",{"category":104,"check":105,"severity":24,"summary":106},"Codeausführung","Validierung","Der Skill stützt sich für die Eingabevalidierung auf die Tool-Schemas des MCP-Servers, und die Referenzdateien bieten strukturierte Abfragemuster.",{"category":66,"check":108,"severity":24,"summary":109},"Ungeschützte destruktive Operationen","Der Skill erfordert eine ausdrückliche Benutzergenehmigung vor der Erstellung von Indizes und führt keine destruktiven Operationen ohne Benutzerbestätigung durch.",{"category":104,"check":111,"severity":24,"summary":112},"Fehlerbehandlung","Der Workflow des Skills beinhaltet Prüfungen auf Versionskompatibilität und fordert Benutzer zur Genehmigung auf, was auf ein Closed-Fail-Verhalten bei unerwarteten Zuständen hindeutet.",{"category":104,"check":114,"severity":63,"summary":115},"Protokollierung","Der Skill selbst führt keine destruktiven Aktionen oder ausgehenden Aufrufe durch, die eine lokale Audit-Protokollierung erfordern; diese werden vom MCP-Server behandelt.",{"category":117,"check":118,"severity":63,"summary":119},"Compliance","DSGVO","Der Skill arbeitet mit MongoDB-Schema und Datenstrukturen, nicht direkt mit personenbezogenen Daten, und übermittelt keine Daten an Dritte.",{"category":117,"check":121,"severity":24,"summary":122},"Zielmarkt","Der Skill ist für MongoDB Atlas-Benutzer weltweit breit anwendbar, es wurden keine regionalen Einschränkungen festgestellt.",{"category":92,"check":124,"severity":24,"summary":125},"Laufzeitstabilität","Der Skill stützt sich auf Standard-MongoDB-MCP-Server-Tools und gängige Shell-Befehle, was die plattformübergreifende Kompatibilität gewährleistet.",{"category":44,"check":127,"severity":24,"summary":128},"README","Die README-Datei bietet klare Installationsanweisungen für verschiedene Umgebungen und Links zu relevanter Dokumentation.",{"category":33,"check":130,"severity":24,"summary":131},"Größe der Tool-Oberfläche","Der Skill verwendet eine kleine, fokussierte Auswahl an MCP-Tools, die für seinen definierten Umfang relevant sind.",{"category":40,"check":133,"severity":24,"summary":134},"Überlappende Nah-Synonym-Tools","Der Skill verwendet eindeutige MCP-Tools für spezifische Aktionen und vermeidet Redundanz oder überlappende Funktionalität.",{"category":44,"check":136,"severity":24,"summary":137},"Phantom-Funktionen","Alle beworbenen Funktionen, wie die Implementierung und Optimierung von Atlas Search, Vector Search und Hybrid Search, werden durch die bereitgestellten Workflows und Referenzdateien unterstützt.",{"category":139,"check":140,"severity":24,"summary":141},"Installation","Installationsanleitung","Die README-Datei enthält umfassende Installationsanweisungen für mehrere Plattformen und Anleitungen zur Einrichtung des MCP-Servers.",{"category":143,"check":144,"severity":24,"summary":145},"Fehler","Aktionsfähige Fehlermeldungen","Die Workflows und Referenzdateien des Skills beschreiben Fehlerbedingungen wie Versionskonflikte und fehlende Indizes mit Anleitungen zur Behebung.",{"category":147,"check":148,"severity":63,"summary":149},"Ausführung","Angepinnte Abhängigkeiten","Der Skill verfügt über keine gebündelten Skripte mit externen Abhängigkeiten, die ein Anpinnen oder Interpreter-Deklarationen erfordern.",{"category":33,"check":151,"severity":24,"summary":152},"Trockenlauf-Vorschau","Der Skill erfordert eine ausdrückliche Benutzergenehmigung, bevor Indexerstellungsbefehle ausgeführt werden, und fungiert somit als Trockenlauf-Vorschau.",{"category":154,"check":155,"severity":63,"summary":156},"Protokoll","Idempotente Wiederholungsversuche & Timeouts","Der Skill verlässt sich für Wiederholungsversuche und Timeouts auf den MCP-Server und MongoDB-Operationen; er implementiert keine eigenen.",{"category":117,"check":158,"severity":63,"summary":159},"Telemetrie-Opt-in","Der Skill sendet keine Telemetrie; diese Funktionalität würde vom zugrunde liegenden Agenten oder MCP-Server übernommen, falls implementiert.",{"category":40,"check":161,"severity":24,"summary":162},"Präziser Zweck","Der Zweck ist präzise definiert und besagt, dass er MongoDB-Benutzer bei der Implementierung und Optimierung von Atlas Search, Vector Search und Hybrid Search-Lösungen anleitet.",{"category":40,"check":164,"severity":24,"summary":165},"Prägnante Frontmatter","Die SKILL.md-Frontmatter ist prägnant und fasst die Kernfunktionalität und Anwendungsfälle des Skills effektiv zusammen.",{"category":44,"check":167,"severity":24,"summary":168},"Prägnanter Body","Der SKILL.md-Body ist gut strukturiert mit klaren Abschnitten und lagert detaillierte Verfahren in Referenzdateien aus, wodurch eine angemessene Länge beibehalten wird.",{"category":170,"check":171,"severity":24,"summary":172},"Kontext","Progressive Offenlegung","Detaillierte Verfahren für spezifische Suchtypen (lexikalisch, Vektor, Hybrid) sind ordnungsgemäß in separate Referenzdateien aufgeteilt und werden aus dem Haupt-SKILL.md verlinkt.",{"category":170,"check":174,"severity":63,"summary":175},"Verzweigte Erkundung","Der Workflow des Skills ist direktiv und beinhaltet keine umfangreiche Erkundung oder tiefe Code-Überprüfung, die von `context: fork` profitieren würde.",{"category":22,"check":177,"severity":24,"summary":178},"Anwendungsbeispiele","Die Referenzdateien enthalten klare End-to-End-Beispiele für verschiedene Suchmuster, einschließlich Indexdefinitionen und Aggregationspipelines.",{"category":22,"check":180,"severity":24,"summary":181},"Grenzfälle","Der Skill dokumentiert Fehlerfälle und Einschränkungen, wie z. B. Versionsprüfungen für Hybridsuche und die Behandlung fehlender Felder oder Indizes, mit Wiederherstellungsschritten.",{"category":104,"check":183,"severity":63,"summary":184},"Tool-Fallback","Der Skill ist für die Arbeit mit dem MongoDB MCP-Server konzipiert, der eine erforderliche Komponente ist, und verfügt über keinen Fallback-Pfad.",{"category":66,"check":186,"severity":24,"summary":187},"Stoppen bei unerwartetem Zustand","Der Skill weist explizit an, anzuhalten und den Benutzer zu informieren, wenn Versionsanforderungen für die Hybridsuche nicht erfüllt sind, und erfordert die Genehmigung, bevor mit der Indexerstellung fortgefahren wird.",{"category":92,"check":189,"severity":24,"summary":190},"Skill-übergreifende Kopplung","Der Skill ist in sich geschlossen und stützt sich nicht auf andere spezifische geladene Skills; er definiert klar seinen Umfang in Bezug auf MongoDB Atlas Search.",1778694322161,"Dieser Skill leitet Benutzer durch die Implementierung, Optimierung und Fehlerbehebung von Atlas Search (lexikalisch), Vector Search (semantisch) und Hybrid Search in MongoDB. Er behandelt die Auswahl des richtigen Suchansatzes, die Erstellung von Indizes, die Konstruktion von Abfragen und die Optimierung der Leistung, mit detaillierten Referenzdateien für jeden Suchtyp.",[194,195,196,197,198],"Leitet die Implementierung von Atlas Search, Vector Search und Hybrid Search an","Empfiehlt den geeigneten Suchtyp basierend auf dem Anwendungsfall","Bietet Workflows für die Indexerstellung und Abfragekonstruktion","Enthält detaillierte Referenzdateien für lexikalische, Vektor- und Hybridsuche","Bietet Anleitungen zu Versionsprüfungen und Abfrageoptimierung",[200,201,202],"Implementierung allgemeiner Datenbankverwaltungsaufgaben","Ersetzung der MongoDB Atlas-Benutzeroberfläche für die Indexverwaltung (stellt JSON für die manuelle Erstellung bereit)","Ausführung beliebiger Datenbankabfragen außerhalb von Suche und Indizierung","3.0.0","4.4.0","MongoDB-Benutzern die Möglichkeit zu geben, leistungsstarke Suchfunktionen zu erstellen, von einfacher Textübereinstimmung bis hin zu fortschrittlicher semantischer Ähnlichkeit und hybriden Ansätzen, indem klare Anleitungen und Workflows bereitgestellt werden.","Alle Prüfungen mit hoher Schweregrad bestanden. 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Connect to databases, explore data, manage collections, optimize queries, generate reliable code, implement best practices, develop advanced features, and more.",{"claudeCode":210},{"basePath":251,"githubOwner":210,"githubRepo":241,"locale":252,"slug":241,"type":253},"","en","plugin",{"_creationTime":255,"_id":256,"community":257,"display":258,"identity":262,"providers":264,"relations":278,"tags":280,"workflow":281},1778694149049.346,"k17bjnvrfwx0ae2fnz7yj78p6h86mewp",{"reviewCount":8},{"description":259,"installMethods":260,"name":261,"sourceUrl":14},"Use the official MongoDB Skills with your favorite coding agent to build faster.",{"claudeCode":12},"mongodb-plugins",{"basePath":251,"githubOwner":210,"githubRepo":241,"locale":252,"slug":241,"type":263},"marketplace",{"evaluate":265,"extract":272},{"promptVersionExtension":266,"promptVersionScoring":204,"score":267,"tags":268,"targetMarket":270,"tier":271},"3.1.0",75,[210,214,241,269],"developer-tools","global","community",{"commitSha":273,"marketplace":274,"plugin":276},"HEAD",{"name":261,"pluginCount":275},1,{"mcpCount":8,"provider":277,"skillCount":8},"classify",{"repoId":279},"kd74vahs1zbjqzqbert490xyrd86nfv5",[241,214,269,210],{"evaluatedAt":282,"extractAt":283,"updatedAt":284},1778694174645,1778694149049,1778694461056,{"evaluate":286,"extract":292},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":287,"targetMarket":270,"tier":216},[210,288,289,290,291],"atlas","streaming","data-pipelines","cloud-management",{"commitSha":273,"license":234,"plugin":293},{"mcpCount":8,"provider":277,"skillCount":294},7,{"parentExtensionId":256,"repoId":279},[288,291,290,210,289],{"evaluatedAt":298,"extractAt":283,"updatedAt":299},1778694205322,1778694461243,{"evaluate":301,"extract":303},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":302,"targetMarket":270,"tier":216},[210,211,212,213,214,215],{"commitSha":273},{"parentExtensionId":245,"repoId":279,"translatedFrom":305},"k17b18bc1pkwm6r3xttpqzefj586ms2r",{"_creationTime":307,"_id":279,"identity":308,"providers":309,"workflow":507},1778694144418.9976,{"githubOwner":210,"githubRepo":241,"sourceUrl":14},{"classify":310,"discover":496,"github":499},{"commitSha":273,"extensions":311},[312,322,333,360,381,391,399,407,423,467,481],{"basePath":313,"displayName":314,"installMethods":315,"rationale":316,"selectedPaths":317,"source":321,"sourceLanguage":252,"type":263},".agents/plugins","mongodb-agent-skills",{"claudeCode":12},"marketplace.json at .agents/plugins/marketplace.json",[318],{"path":319,"priority":320},"marketplace.json","mandatory","rule",{"basePath":251,"displayName":261,"installMethods":323,"rationale":324,"selectedPaths":325,"source":321,"sourceLanguage":252,"type":263},{"claudeCode":12},"marketplace.json at .claude-plugin/marketplace.json",[326,328,330],{"path":327,"priority":320},".claude-plugin/marketplace.json",{"path":329,"priority":320},"README.md",{"path":331,"priority":332},"LICENSE","high",{"basePath":251,"description":248,"displayName":210,"installMethods":334,"license":234,"rationale":335,"selectedPaths":336,"source":321,"sourceLanguage":252,"type":253},{"claudeCode":210},"plugin manifest at .claude-plugin/plugin.json",[337,339,340,341,344,346,348,350,352,354,356,358],{"path":338,"priority":320},".claude-plugin/plugin.json",{"path":329,"priority":320},{"path":331,"priority":332},{"path":342,"priority":343},"skills/atlas-stream-processing/SKILL.md","medium",{"path":345,"priority":343},"skills/mongodb-connection/SKILL.md",{"path":347,"priority":343},"skills/mongodb-mcp-setup/SKILL.md",{"path":349,"priority":343},"skills/mongodb-natural-language-querying/SKILL.md",{"path":351,"priority":343},"skills/mongodb-query-optimizer/SKILL.md",{"path":353,"priority":343},"skills/mongodb-schema-design/SKILL.md",{"path":355,"priority":343},"skills/mongodb-search-and-ai/SKILL.md",{"path":357,"priority":332},".codex-plugin/plugin.json",{"path":359,"priority":332},".cursor-plugin/plugin.json",{"basePath":361,"description":362,"displayName":363,"installMethods":364,"rationale":365,"selectedPaths":366,"source":321,"sourceLanguage":252,"type":242},"skills/atlas-stream-processing","Manages MongoDB Atlas Stream Processing (ASP) workflows. 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",[367,369,371,373,375,377,379],{"path":368,"priority":320},"SKILL.md",{"path":370,"priority":343},"references/connection-configs.md",{"path":372,"priority":343},"references/development-workflow.md",{"path":374,"priority":343},"references/mcp-troubleshooting.md",{"path":376,"priority":343},"references/output-diagnostics.md",{"path":378,"priority":343},"references/pipeline-patterns.md",{"path":380,"priority":343},"references/sizing-and-parallelism.md",{"basePath":382,"description":383,"displayName":384,"installMethods":385,"rationale":386,"selectedPaths":387,"source":321,"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",[388,389],{"path":368,"priority":320},{"path":390,"priority":343},"references/monitoring-guide.md",{"basePath":392,"description":393,"displayName":394,"installMethods":395,"rationale":396,"selectedPaths":397,"source":321,"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",[398],{"path":368,"priority":320},{"basePath":400,"description":401,"displayName":402,"installMethods":403,"rationale":404,"selectedPaths":405,"source":321,"sourceLanguage":252,"type":242},"skills/mongodb-natural-language-querying","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.","mongodb-natural-language-querying",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-natural-language-querying/SKILL.md",[406],{"path":368,"priority":320},{"basePath":408,"description":409,"displayName":410,"installMethods":411,"rationale":412,"selectedPaths":413,"source":321,"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",[414,415,417,419,421],{"path":368,"priority":320},{"path":416,"priority":343},"references/aggregation-optimization.md",{"path":418,"priority":343},"references/antipattern-examples.md",{"path":420,"priority":343},"references/core-indexing-principles.md",{"path":422,"priority":343},"references/update-query-examples.md",{"basePath":424,"description":425,"displayName":426,"installMethods":427,"rationale":428,"selectedPaths":429,"source":321,"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",[430,431,433,435,437,439,441,443,445,447,449,451,453,455,457,459,461,463,465],{"path":368,"priority":320},{"path":432,"priority":343},"references/antipattern-excessive-lookups.md",{"path":434,"priority":343},"references/antipattern-unnecessary-collections.md",{"path":436,"priority":343},"references/antipattern-unnecessary-indexes.md",{"path":438,"priority":343},"references/fundamental-document-model.md",{"path":440,"priority":343},"references/fundamental-document-size.md",{"path":442,"priority":343},"references/fundamental-embed-vs-reference.md",{"path":444,"priority":343},"references/fundamental-schema-validation.md",{"path":446,"priority":343},"references/pattern-approximation.md",{"path":448,"priority":343},"references/pattern-archive.md",{"path":450,"priority":343},"references/pattern-attribute.md",{"path":452,"priority":343},"references/pattern-bucket.md",{"path":454,"priority":343},"references/pattern-computed.md",{"path":456,"priority":343},"references/pattern-document-versioning.md",{"path":458,"priority":343},"references/pattern-extended-reference.md",{"path":460,"priority":343},"references/pattern-outlier.md",{"path":462,"priority":343},"references/pattern-polymorphic.md",{"path":464,"priority":343},"references/pattern-schema-versioning.md",{"path":466,"priority":343},"references/pattern-time-series-collections.md",{"basePath":240,"description":468,"displayName":13,"installMethods":469,"rationale":470,"selectedPaths":471,"source":321,"sourceLanguage":252,"type":242},"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",{"claudeCode":12},"SKILL.md frontmatter at skills/mongodb-search-and-ai/SKILL.md",[472,473,475,477,479],{"path":368,"priority":320},{"path":474,"priority":343},"references/hybrid-search.md",{"path":476,"priority":343},"references/lexical-search-indexing.md",{"path":478,"priority":343},"references/lexical-search-querying.md",{"path":480,"priority":343},"references/vector-search.md",{"basePath":482,"description":483,"displayName":484,"installMethods":485,"rationale":486,"selectedPaths":487,"source":321,"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",[488,489,492,494],{"path":368,"priority":320},{"path":490,"priority":491},"assets/report.md","low",{"path":493,"priority":343},"references/install-skill-validator.md",{"path":495,"priority":343},"references/llm-scoring.md",{"sources":497},[498],"manual",{"closedIssues90d":8,"description":259,"forks":230,"license":234,"openIssues90d":8,"pushedAt":231,"readmeSize":228,"stars":232,"topics":500},[501,502,503,504,505,506],"agent","claude","cursor","gemini-cli-extension","mcp","skills",{"classifiedAt":508,"discoverAt":509,"extractAt":510,"githubAt":510,"updatedAt":508},1778694148853,1778694144419,1778694146756,[211,214,213,210,215,212],{"evaluatedAt":513,"extractAt":283,"updatedAt":238},1778694322274,[],[516,539,569,592,613,644],{"_creationTime":517,"_id":518,"community":519,"display":520,"identity":524,"providers":525,"relations":533,"tags":535,"workflow":536},1778694378261.7441,"k17fkkx5s0960j77wnp642y0vs86nmq7",{"reviewCount":8},{"description":521,"installMethods":522,"name":523,"sourceUrl":14},"Optimieren Sie die Konfiguration von MongoDB-Clientverbindungen (Pools, Timeouts, Muster) für jede unterstützte Treibersprache. Verwenden Sie diese Fähigkeit, wenn Sie an Funktionen arbeiten/diese aktualisieren/überprüfen, die einen MongoDB-Client instanziieren oder konfigurieren (z. B. beim Aufruf von `connect()`), Verbindungspools konfigurieren, Verbindungsprobleme beheben (ECONNREFUSED, Timeouts, Pool-Erschöpfung), Leistungsprobleme im Zusammenhang mit Verbindungen optimieren. Dies schließt Szenarien wie das Erstellen von serverlosen Funktionen mit MongoDB, das Erstellen von API-Endpunkten, die MongoDB verwenden, die Optimierung von MongoDB-Anwendungen mit hohem Datenverkehr, das Erstellen von langlaufenden Aufgaben und Nebenläufigkeit oder das Debuggen von verbindungsbezogenen Fehlern ein.",{"claudeCode":12},"MongoDB Connection Optimizer",{"basePath":382,"githubOwner":210,"githubRepo":241,"locale":18,"slug":384,"type":242},{"evaluate":526,"extract":532},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":527,"targetMarket":270,"tier":216},[210,214,528,529,530,531],"connection","performance","optimization","configuration",{"commitSha":273,"license":234},{"parentExtensionId":245,"repoId":279,"translatedFrom":534},"k175wmq2n17n23xzphj2zzt3qs86n3xd",[531,528,214,210,530,529],{"evaluatedAt":537,"extractAt":283,"updatedAt":538},1778694243014,1778694378261,{"_creationTime":540,"_id":541,"community":542,"display":543,"identity":549,"providers":553,"relations":562,"tags":565,"workflow":566},1778696691708.3108,"k174bsewq8k21t0bg3rrzcxkcd86mrgx",{"reviewCount":8},{"description":544,"installMethods":545,"name":547,"sourceUrl":548},"Query AgentDB through the controller bridge -- semantic routing, hierarchical recall, causal graphs, context synthesis, pattern store/search",{"claudeCode":546},"ruvnet/ruflo","agentdb-query","https://github.com/ruvnet/ruflo",{"basePath":550,"githubOwner":551,"githubRepo":552,"locale":252,"slug":547,"type":242},"plugins/ruflo-agentdb/skills/agentdb-query","ruvnet","ruflo",{"evaluate":554,"extract":561},{"promptVersionExtension":203,"promptVersionScoring":204,"score":555,"tags":556,"targetMarket":270,"tier":216},99,[557,214,558,215,559,505,560],"agentdb","query","knowledge-graph","llm",{"commitSha":273},{"parentExtensionId":563,"repoId":564},"k1702kbgkcgg2way9x5303rpr186n62a","kd7ed28gj8n0y3msk5dzrp05zs86nqtc",[557,214,559,560,505,558,215],{"evaluatedAt":567,"extractAt":568,"updatedAt":567},1778699766010,1778696691708,{"_creationTime":570,"_id":571,"community":572,"display":573,"identity":577,"providers":580,"relations":588,"tags":589,"workflow":590},1778696691708.307,"k176zwpf986zp7jmtfwp20fnfh86mcws",{"reviewCount":8},{"description":574,"installMethods":575,"name":576,"sourceUrl":548},"Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).",{"claudeCode":546},"V3 Memory Unification",{"basePath":578,"githubOwner":551,"githubRepo":552,"locale":252,"slug":579,"type":242},".claude/skills/v3-memory-unification","v3-memory-unification",{"evaluate":581,"extract":586},{"promptVersionExtension":203,"promptVersionScoring":204,"score":555,"tags":582,"targetMarket":270,"tier":216},[583,214,557,584,585,212],"memory","hnsw","migration",{"commitSha":273,"license":587},"MIT",{"repoId":564},[557,214,584,583,585,212],{"evaluatedAt":591,"extractAt":568,"updatedAt":591},1778699464598,{"_creationTime":593,"_id":594,"community":595,"display":596,"identity":600,"providers":602,"relations":609,"tags":610,"workflow":611},1778696691708.2996,"k175z5j3knm69exj7qpfwy3e1586nh3w",{"reviewCount":8},{"description":597,"installMethods":598,"name":599,"sourceUrl":548},"Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.\n",{"claudeCode":546},"embeddings",{"basePath":601,"githubOwner":551,"githubRepo":552,"locale":252,"slug":599,"type":242},".agents/skills/embeddings",{"evaluate":603,"extract":608},{"promptVersionExtension":203,"promptVersionScoring":204,"score":555,"tags":604,"targetMarket":270,"tier":216},[599,212,584,605,606,215,607],"sql-js","ai","retrieval",{"commitSha":273},{"repoId":564},[606,599,584,607,215,605,212],{"evaluatedAt":612,"extractAt":568,"updatedAt":612},1778698905205,{"_creationTime":614,"_id":615,"community":616,"display":617,"identity":623,"providers":627,"relations":637,"tags":640,"workflow":641},1778693180473.1177,"k179t7487ft90cyp6e4xypxsgh86nq5q",{"reviewCount":8},{"description":618,"installMethods":619,"name":621,"sourceUrl":622},"Azure AI Search SDK for Python. Use for vector search, hybrid search, semantic ranking, indexing, and skillsets.\nTriggers: \"azure-search-documents\", \"SearchClient\", \"SearchIndexClient\", \"vector search\", \"hybrid search\", \"semantic search\".\n",{"claudeCode":620},"microsoft/agent-skills","Azure AI Search SDK for Python","https://github.com/microsoft/agent-skills",{"basePath":624,"githubOwner":625,"githubRepo":241,"locale":252,"slug":626,"type":242},".github/plugins/azure-sdk-python/skills/azure-search-documents-py","microsoft","azure-search-documents-py",{"evaluate":628,"extract":636},{"promptVersionExtension":203,"promptVersionScoring":204,"score":629,"tags":630,"targetMarket":270,"tier":216},95,[631,632,633,634,212,213,635],"azure","ai-search","sdk","python","semantic-search",{"commitSha":273,"license":587},{"parentExtensionId":638,"repoId":639},"k171mfx6atvhq1bkhpky84v4b186n9qd","kd77czgnv00rfjm815pcc5xx5986n5t8",[632,631,213,634,633,635,212],{"evaluatedAt":642,"extractAt":643,"updatedAt":642},1778695120589,1778693180473,{"_creationTime":645,"_id":646,"community":647,"display":648,"identity":652,"providers":654,"relations":662,"tags":664,"workflow":665},1778696691708.3264,"k179thjzaw5kepc7zhdj9sat3n86mcqp",{"reviewCount":8},{"description":649,"installMethods":650,"name":651,"sourceUrl":548},"Validate pending migrations for foreign key consistency, rollback safety, and best practices",{"claudeCode":546},"migrate-validate",{"basePath":653,"githubOwner":551,"githubRepo":552,"locale":252,"slug":651,"type":242},"plugins/ruflo-migrations/skills/migrate-validate",{"evaluate":655,"extract":661},{"promptVersionExtension":203,"promptVersionScoring":204,"score":207,"tags":656,"targetMarket":270,"tier":216},[214,657,658,659,660,269],"migrations","sql","validation","code-quality",{"commitSha":273},{"parentExtensionId":663,"repoId":564},"k176me0sh9b6bc3gzttnywx4w986njzh",[660,214,269,657,658,659],{"evaluatedAt":666,"extractAt":568,"updatedAt":666},1778701008912]