「que」の検索結果

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

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WHAT: Draws a code change or part of a codebase as an animated architecture or data-flow diagram, on its own or in a pull request. WHEN: asked to diagram, visualise or explain a change or a system, or when a pull request should carry a diagram. KEYWORDS: PR Lens, diagram, architecture, data flow, visualise, visualize, pull request

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。

Skip profile question when user explicitly refuses to answer. When user says 'I don't want to answer' or 'skip this question', use this tool to stop asking about that item.

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。

A medical-research-native literature reading skill for users with clinical, bioinformatics, translational, and basic experimental backgrounds. Use this skill whenever a user wants to read, analyze, critique, or interpret a medical or scientific paper — whether they provide a PDF, abstract, DOI, PMID, or just a title. Triggers include requests like \"analyze this paper\", \"critique this study\", \"is this a strong paper?\", \"give me similar studies\", \"prepare me for journal club\", \"help me understand this bioinformatics paper\", \"what are the weaknesses here?\", or \"turn this into a mind map\". Also activate for any downstream deliverables such as journal club kits, comparison tables, PI decision briefs, replication starters, or follow-up experiment designs. Do NOT treat as a generic summarizer — this skill performs structured evidence-type classification, track-specific critical appraisal, interpretation-boundary judgment, and research-grade follow-up generation.

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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 expansion, HyDE, and multi-query generation for improved retrieval

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。

Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)

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。

Scene and sequence craft (场景/段落/细节/道具/悬念/情趣) — merged from Robert McKee's scene design and five-step scene analysis (value turn, beats, text/subtext, turning points, pacing, image systems), McKee's Dialogue scene types (balanced, comic, asymmetric, indirect, reflexive, minimal), Syd Field's sequence and scene elements, Neill Hicks (less is more, enter late leave early, energy), Richard Walter (action over talk, small gestures, avoid phones/cars/restaurants, list twelve alternative locations), Wendy Henson (action paragraphs, transitions, story-doing), Julian Hoxter (scene beats, objectives and tactics), Mei Feng's value test, and Lu Jun's chapters 意趣要足 (suspense, delay, wit), 细节要妙, 道具要精, 场景要当. Use when writing or fixing a single scene, choosing a location, building a sequence, planting a prop or detail, designing suspense and delay, cutting a scene that "nothing happens" in, or turning talk into action.

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 or revise Chinese social-media covers through the registered Skill-封面 asset system, reusable styles, presenter identities, ratio-specific layouts, and exact replacement prompts. Use only when the user explicitly says“skill-cover”“Skill-封面”“实战风格”, requests the registered style/gesture assets, asks for simultaneous 3:4 and 4:3 registered-layout output, replaces a reference cover's person with the current digital-human frame, or extends this registered cover system. Do not use for a generic“制作封面/生成封面”request; generic cover requests belong to dog-skill.

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。

dontbesilent 好问题生成器。把模糊问题改写成 Agent 可推理、可批评、可验证的问题说明书，并判断它能被自动化解决到什么程度。 触发方式：/dbs-good-question、/好问题、/问题说明书、/Agent可解性、「这个问题能不能自动化解决」「帮我把问题说清楚」 Turn fuzzy problems into agent-solvable problem briefs and evaluate automation readiness. Trigger: /dbs-good-question, "clarify this problem", "can an agent solve this"

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 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。

ktx's semantic layer - a structured catalog of sources (tables/views), measures, joins, and segments expressed as YAML. Covers the schema and how to query it via `sl_query`. Use when the task involves querying pre-defined metrics (ARR, churn, retention, LTV, MAU) or reading SL source YAML to understand the catalog. Capture is handled by the `sl_capture` skill (memory-agent only).

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 a meta-agent request is too ambiguous to safely generate, package, publish, or adapt without one to five targeted questions.

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 Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier, and tier comparison. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics. Includes lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, storage tiers, hot cool cold archive, storage tier comparison, when to use storage tiers, lifecycle management, Azure Storage concepts. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).

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Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection.

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Triage inbound journalist source queries and draft a response only when the user's expertise is a real fit. Runs each query through proven source-request lenses (4-gate fit triage, credential-standing test, deadline read, BLUF/inverted-pyramid drafting), kills weak fits, asks for missing proof, and never auto-sends.

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。

Start and control Minutes Coach, the separate real-time copilot HUD, with an explicit meeting goal. Use only for explicit Coach or HUD lifecycle requests such as "start Minutes Coach", "open the Coach HUD", "pause Minutes Coach", "resume Minutes Coach", "Minutes Coach status", or "stop Minutes Coach". Do not use for requests that explicitly ask the current terminal agent to watch or strategize; those belong to minutes-live-sidekick. An ambiguous request such as "coach me live" requires one short surface clarification and must not automatically start Coach.

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Implement Roblox physical simulation and queries with assemblies, anchoring, constraints, collision groups, CanCollide/CanTouch/CanQuery, raycasts and overlap queries, mass, impulses, forces, velocity, moving assemblies, cleanup, and network ownership. Use for Roblox collisions, hit detection, RaycastParams, PhysicsService, projectiles, vehicles, knockback, constraints, deprecated BodyMovers, unstable motion, or client-owned physics exploits.

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Build traceable internal-review proposal, RFI, RFP, tender, bid, and questionnaire responses from supplied questions and approved sources. Use to analyze questions, contribute business or product evidence, or draft qualified responses.

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Review, approve, request changes on, or reject pending wiki edit drafts in Arkon. Requires editor or admin role. Triggers on: review drafts, pending reviews, check draft queue, approve draft, reject draft, request changes, send draft back, review wiki changes.

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 construction request for information so the site can act on it — a direct answer, the drawing or specification reference that supports it, and an explicit statement of whether it changes cost or programme. Use when asked to respond to an RFI, answer a contractor query, or handle a request for information on site, or when RFIs keep coming back for clarification. Produces the answer with its reference, the cost and time implication stated, the instruction status, the distribution list, and the register entry.

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。