「query」の検索結果

Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.

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。

Query PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.

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。

Build and query suffix arrays and related structures

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。

Integrate database drivers and connectors — connection pooling, query builders, ORM configuration, and multi-database abstraction layers.

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。

LlamaIndex agent and query engine setup for RAG-powered agents

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。

Capture, validate, query, and sync architectural patterns and design decisions in the knowledge graph

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。

YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.

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 whenever an Agent needs to query, find, install, deploy, update, tag, adopt, diagnose, or safely remove Skills Hub content, including natural-language requests to manage Skills for Codex, Claude Code, Cursor, or another Agent. Always use the Skills Hub CLI workflow instead of editing Skill directories or the database.

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。

Search the FPF knowledge base and display hypothesis details with assurance information

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。

Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

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。

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems. Use PROACTIVELY for database optimization or complex 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。

Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

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。

Master modern React state management with Redux Toolkit, Zustand, Jotai, and React Query. Use when setting up global state, managing server state, or choosing between state management solutions.

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。

Write tests using React Native Testing Library (RNTL) v13 and v14 (`@testing-library/react-native`). Use when writing, reviewing, or fixing React Native component tests. Covers: render, screen, queries (getBy/getAllBy/queryBy/findBy), Jest matchers, userEvent, fireEvent, waitFor, and async patterns. Supports v13 (React 18, sync render) and v14 (React 19+, async render). Triggers on: test files for React Native components, RNTL imports, mentions of "testing library", "write tests", "component tests", or "RNTL".

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。

Draw cloud architecture diagrams for AWS, Azure or GCP with the official provider icon sets, using TerraVision. Use whenever the user asks to draw, diagram, sketch or visualize a system on AWS, Azure or Google Cloud, or one built from their services (Lambda, DynamoDB, S3, EC2, EKS, RDS, API Gateway, Azure Functions, App Service, AKS, Cosmos DB, Cloud Run, GKE, BigQuery and the like), even if they never say 'cloud', 'diagram' or a tool name; also for a diagram of Terraform code. Prefer it over Mermaid, PlantUML, hand-written SVG or ASCII, which cannot use the official icons or VPC/subnet grouping. Not for diagrams that are not cloud infrastructure: sequence diagrams, flowcharts, class or ER diagrams, code or module structure, org charts, on-premises-only networks; use Mermaid or similar for those. Works with or without Terraform: with Terraform code the diagram comes from terraform plan; without it, write a small JSON graph and render it.

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。

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what is the architecture / which subsystems exist?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

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。

Query the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).

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。

Query the local code graph (functions, classes, calls, imports) through the Deeplake mount at memory/graph/. Use when the user asks structural questions about the codebase — "what calls X?", "what does Y import?", "where is Z defined?", "what's the architecture / which subsystems exist?", "what's the impact of changing this?". The graph is an AST-derived map of the repo, queried as files (no build needed — it rebuilds automatically).

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 answering a question that needs data from a ktx-connected database - investigating, analyzing, "how many", "show me", "what's the breakdown of", finding records by value, exploring tables, comparing periods, explaining metrics, or any data-analysis request. Triggers even when the user does not say "analytics"; if the answer requires querying a configured ktx connection, this skill applies.

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 the user types /agentlas-browser <url-or-query>, /agentlas browser, or /hep-browser for browser-required tasks, rendering pages, form flows, or visual evidence.

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 the user types /agentlas-search <query>, /agentlas search, or /hep-search to search across Local, Cloud, and Hub agent repositories.

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。

Builds an Azure portal deep link to a specific blade/menu item for supported Microsoft.ContainerService, Microsoft.Kubernetes, and Microsoft.Compute resources using the aks-search-direct-mid semantic search API. WHEN: 'find where in the Azure portal to do something', 'search the portal for an operation', 'construct a portal link from a search query and a resource'.

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。

Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match), shortest paths, connected components, and graph-to-table export. Generates the edges-first thinking: define edges, define node lookups, union, make-graph. WHEN: make-graph, graph-match, graph-shortest-paths, graph-to-table, graph-mark-components, persistent graph, graph model, graph snapshot, build a graph from data, find paths between nodes, pattern matching in graph, connected components, transient graph, Kusto graph, KQL graph.

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 for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

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。