Relational schema design — normalization, keys, constraints, and evolution — use when modeling data or reviewing a schema.
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。
596 件 ・ 関連度順
概要と使いどころ
Relational schema design — normalization, keys, constraints, and evolution — use when modeling data or reviewing a schema.
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。
Writing abstracts that get papers read — structured content, the 5-sentence core, and journal-specific constraints.
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。
Analyze vehicle routing and fleet optimization systems for route planning algorithms, multi-stop sequencing, time window constraints, and last-mile delivery 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。
Audit manufacturing production optimization systems for OEE (Overall Equipment Effectiveness) calculation accuracy, Six Big Losses categorization, job shop and flow shop scheduling algorithms (LP, MIP, constraint programming, genetic algorithm), Theory of Constraints bottleneck detection.
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。
Audit factory production scheduling systems for finite capacity planning, Drum-Buffer-Rope (DBR) Theory of Constraints implementation, dispatching rules (EDD, SPT, critical ratio), sequence-dependent changeover optimization, MRP 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。
Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.
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。
**WORKFLOW SKILL** — Create custom VS Code Copilot agents (.agent.md). USE FOR: new agents, tool restrictions, handoffs, orchestration patterns, discipline constraints. DO NOT USE FOR: general coding, VS Code extension development.
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。
Diagnose and draft or explicitly apply paid-ad optimizations using evidence, financial constraints, experiments, and capability-gated adapters. Use for campaign optimization, budget reallocation, bid changes, pausing or archiving ads, requests to delete campaigns, search-term or negative-keyword actions, creative rotation, or improving CPA and ROAS.
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。
Toolkit for creating animated GIFs optimized for Slack, with validators for size constraints and composable animation primitives. This skill applies when users request animated GIFs or emoji animations for Slack from descriptions like "make me a GIF for Slack of X doing Y".
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。
Plan and review paid-media budgets, bidding, pacing, marginal return, forecasts, CPA, ROAS, MER, LTV:CAC, constraints, and allocation across supported platforms. Use for ad budget allocation, media budget, bidding strategy, scaling, spend pacing, budget forecast, ROAS target, or investment tradeoffs.
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。
Diagnoses Google Ads account performance issues such as conversion loss (value or volume), low lead flow/volume, and lost impression share (opportunities) due to ad rank, bids, or budgets. Use when troubleshooting sudden performance drops, analyzing campaign impression share metrics, investigating low lead flow, or searching for bidding and budget constraints. Don't use for setting up new campaigns, uploading conversion events directly, or general Google Mobile Ads SDK integration issues (use gma-android-integrate instead).
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。
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
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。
Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.
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。
Plan a feature or system before implementation. Use when the user says "plan this", "I want to build X", "how do I implement Y", or when /ck:brainstorm produces a spec.md. Always run before /ck:cook. Modes (pick one): --fast (simple, single-file), --hard (research + red-team + validate). Composable flag (combine with any mode): --tdd — propagates into the cook pipeline. Every phase gets Design Constraints and Quality/Testing State; ck:cook confirms optional test and quality checks per phase.
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。
Plan a feature or system before implementation. Use when the user says "plan this", "I want to build X", "how do I implement Y", or when /ck:brainstorm produces a spec.md. Always run before /ck:cook. Modes (pick one): --fast (simple, single-file), --hard (research + red-team + validate). Composable flag (combine with any mode): --tdd — propagates into the cook pipeline. Every phase gets Design Constraints and Quality/Testing State; ck:cook confirms optional test and quality checks per phase.
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。
Phase 1 of the SRS workflow. User gives a project topic → AI runs a deep, categorized brainstorm (5 mandatory rounds) to fully understand actors, features, scope boundary, tech constraints, and business rules before writing anything.
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。
Phase 1 of the SRS workflow. User gives a project topic → AI runs a deep, categorized brainstorm (5 mandatory rounds) to fully understand actors, features, scope boundary, tech constraints, and business rules before writing anything.
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。
Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"
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。
Advanced Lightning App Builder usage: component visibility filters, custom page templates, Dynamic Forms, Dynamic Actions, page performance optimization, LWC targetConfig constraints on record pages. Use when building complex record pages or custom app templates. NOT for Dynamic Forms basics — use admin/dynamic-forms-and-actions. NOT for exposing an LWC via js-meta.xml targets — use lwc/lwc-app-builder-config.
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 setting up or modifying product bundles, product options, product rules, configuration attributes, and product features in Salesforce CPQ. Trigger keywords: CPQ product bundle, product rule, option constraint, feature configuration, dynamic bundle, filter rule, configuration attribute, bundle nesting. NOT for plain Products and Pricebooks without CPQ — use admin/products-and-pricebooks. NOT for moving an existing CPQ catalog between orgs — use data/product-catalog-migration-cpq. NOT for price rules, price actions or discount schedules — use admin/cpq-pricing-rules.
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 defining clinical data model requirements for Health Cloud: HL7/FHIR data mapping, interoperability requirements, FHIR R4-aligned object activation, CodeableConcept constraints, and middleware translation requirements. NOT for the field-level mapping work itself — use data/fhir-data-mapping. NOT for choosing legacy HC24__ EHR objects vs standard clinical objects — use data/health-cloud-data-model.
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。
Extract tacit knowledge through non-obvious microquestions — things only the user knows that can't be found in code, docs, or research. Use when you're about to guess at intent, context, or constraints during SAFEWORD's understanding flow. Also use when user says 'ask me', 'what do you need to know', or when another skill (bdd, brainstorm, debug) needs user context before proceeding. Do NOT use for questions answerable by reading the codebase or searching the web.
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。
Fully autonomous bug hunting pipeline — discover bugs in a scoped area using parallel subagents, independently triage each finding, fix confirmed issues with subagents, then audit all fixes against repo constraints and target platforms. Runs end-to-end without user interaction.
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。
Problem redefinition before problem solving. Takes a stated problem, extracts its premises, then spawns reframers applying different lenses (problem-vs-symptom, scope-shift, stakeholder-shift, level-of-abstraction, time-horizon, inversion, category-shift, constraints-shift) in isolation, and synthesizes the alternatives into a report with an orchestrator recommendation. Produces feedback only — no code, no tickets, no 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。