Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
日本語の概要は準備中です。原文の説明を表示しています。
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Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Aws Athena — aWS Athena query execution analysis, workgroup management, Data Catalog integration, and cost-per-query tracking. Covers query history, performance optimization, workgroup quota management, saved queries, and data scanned analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Expert in TanStack Query (React Query) — asynchronous state management. Covers data fetching, stale time configuration, mutations, optimistic updates, and Next.js App Router (SSR) integration.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
日本語の概要は準備中です。原文の説明を表示しています。
GraphDB探索エージェント - RyuGraphデータベースを自然言語またはCypherで探索し、関連するコードや仕様書を返却。/query-graph [クエリ] で呼び出し。
Create, edit, or debug parametric 3D CAD parts in CadQuery (Python) that export to STEP for SolidWorks. Use when the request involves CadQuery, .step/.stl export, or modelling a physical part — enclosure, bracket, PCB, motor mount, cam, gear. Also use when a STEP will not open in CAD, or geometry looks correct in STL but is invalid as a solid. Applies a verification discipline before export and documented OCC pitfalls.
日本語の概要は準備中です。原文の説明を表示しています。
Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Create a PostHog endpoint with the right shape on the first try — covers query kind choice, name conventions, what to expose as variables (HogQL code_name vs insight breakdown), data_freshness_seconds, and whether to materialise on day one. Use when the user says "create an endpoint", "expose this query as an API", "turn this insight into an endpoint", or asks for help structuring a new endpoint. Steers away from common mistakes: materialising a query with cohort breakdowns or compare mode, inline-only variables on a materialised endpoint, unbounded date ranges, ambiguous names.
日本語の概要は準備中です。原文の説明を表示しています。
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
日本語の概要は準備中です。原文の説明を表示しています。
CadQuery (Python 製 3D CAD スクリプティングライブラリ) リファレンス。 Workplane API (lineTo / extrude / revolve / sweep / loft / fillet / chamfer / shell)、 Sketch API、Assemblies (Constraint solver, 9 種制約)、Free Function API、 Selectors、Class hierarchy (Shape / Vertex / Edge / Wire / Face / Shell / Solid)、 Import / Export (STEP / DXF / STL / glTF / SVG)、Visualization (VTK, Jupyter)、CQGI。
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user asks about the FMCSA Drug & Alcohol Clearinghouse — full vs limited query, pre-employment vs annual query, query credit purchasing, who has access (employers, drivers, MROs, SAPs, state licensing agencies), reporting violations to the Clearinghouse, the "prohibited" status workflow, consent forms, or how to register/use the clearinghouse.fmcsa.dot.gov portal. Cite 49 CFR 382.701-727.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
日本語の概要は準備中です。原文の説明を表示しています。
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
日本語の概要は準備中です。原文の説明を表示しています。
Answer a question from the structured wiki before searching the web — "query the wiki", "what do we know about", synthesis request, cross-project research. Returns cited synthesis with wikilinks and counter-arguments.
日本語の概要は準備中です。原文の説明を表示しています。
Detect data exfiltration through DNS tunneling by analyzing query entropy, subdomain length, query volume, TXT record abuse, and response payload sizes using passive DNS monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes and optimizes SQL queries using EXPLAIN plans, index recommendations, query rewrites, and performance benchmarking. Use for "query optimization", "slow queries", "database performance", or "EXPLAIN analysis".
日本語の概要は準備中です。原文の説明を表示しています。
Offensive methodology for attacking GraphQL APIs during penetration tests and bug bounty engagements. Covers the full attack lifecycle: endpoint discovery, introspection abuse and blind schema reconstruction when introspection is disabled, authentication and authorization bypass through Relay node IDs and nested object traversal, injection via variables and directives, query batching for brute force and OTP bypass, denial of service through depth bombs and alias amplification, WebSocket subscription hijacking, information disclosure through verbose errors and field suggestion oracles, and file upload abuse via the multipart GraphQL specification. Includes tool-specific guidance for InQL, graphql-cop, CrackQL, BatchQL, Altair, GraphQL Voyager, and clairvoyance. Trigger on: GraphQL, graphql, introspection query, batching attack, query depth, GraphQL injection, GraphQL IDOR, field suggestion, GraphQL auth bypass, GraphQL DoS, GraphQL security, graphql-cop, InQL, CrackQL, BatchQL, Relay node, alias amplificat...
日本語の概要は準備中です。原文の説明を表示しています。