Create design systems with tokens, components, and documentation. Use when building design systems, creating component libraries, or establishing design tokens.
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。
1.4万 件 ・ 関連度順
概要と使いどころ
Create design systems with tokens, components, and documentation. Use when building design systems, creating component libraries, or establishing design tokens.
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。
Generate high-quality academic Beamer slides from a thesis/paper (PDF, Word, or LaTeX source). Compatible with Claude Code and Codex. Supports thesis defense, proposal presentations, and conference talks. Built-in layout library with 13 professional page types, 5 color schemes, and interactive editing loop. Use when: (1) User asks to create thesis defense slides/PPT, (2) User wants to generate academic presentation from a paper, (3) User mentions beamer, 答辩PPT, 学术报告, 开题PPT, 论文幻灯片, or academic slides, (4) User has a PDF/docx/tex thesis and wants presentation output.
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 beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
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。
Preparation guide for ISO 31700 privacy by design for consumer goods certification. Covers the 30 requirements across design, production, and disposal phases. Includes gap assessment methodology, remediation planning, and mapping to GDPR Article 25 data protection by design obligations for consumer-facing products and services.
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。
Guides compliance with country-specific data localization requirements across key jurisdictions including Russia (242-FZ), China (PIPL Art. 40, CAC measures), India (DPDP Act), Turkey, Vietnam, and Indonesia. Covers localization assessment, architecture design, and exemption procedures. Keywords: data localization, data residency, PIPL, 242-FZ, cross-border restrictions.
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。
Structures risk mitigation planning and residual risk tracking for Data Protection Impact Assessments under GDPR Article 35(7)(d). Covers mitigation measure identification, implementation tracking, residual risk acceptance, and Art. 36 prior consultation triggers. Keywords: DPIA mitigation, risk treatment, residual risk, Art. 35(7)(d), safeguards, mitigation tracking, prior consultation.
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。
Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.
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 a feature specification from scratch through a relentless, evidence-based interview that walks the design tree decision-by-decision, resolving dependencies as it goes. Use when the user wants to plan, design, scope, specify, or flesh out a new feature, capability, or system behavior before implementation. Produces a feature specification focused on system behaviors, not implementation detail. Does not plan a restructure of code that already exists — use plan-a-change. Does not refine or stress-test an existing plan — use iterative-plan-review. Does not document already-built features — use project-documentation. Does not design the contract for an interface — use design-an-api. Does not research open-ended options before there is a feature to specify — use research. Does not map the bounded contexts of existing code — use ddd-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。
Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for planning the change its findings imply — use plan-a-change. Not for discovering bounded contexts, ubiquitous language, or where code boundaries diverge from domain boundaries — use ddd-analysis. Not for writing documentation or architectural decision records.
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 creating or maintaining UI design systems, design tokens, component documentation, responsive calculations, quality checks, or design-dev handoff materials.
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 beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
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。
Hardware verification tool for checking functional equivalence between two RTL designs (Verilog). Use when users need to: (1) Verify if two RTL versions are functionally equivalent, (2) Compare original vs. refactored RTL code, (3) Validate design changes or optimizations, (4) Identify semantic vs. cosmetic differences, (5) Generate counterexamples for non-equivalent designs. Analyzes interface alignment, state variables, logic differences, and produces detailed equivalence verdicts with plain language explanations. Particularly effective for design verification, code reviews, and regression testing of RTL modifications.
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 beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
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。
Game designer for creative vision, GDD creation, and narrative design. Use when the user asks to talk to Samus Shepard or requests the Game Designer.
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。
Design one-off HTML artifacts (landing, deck, prototype).
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 REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
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。
Lightweight standalone design spec for AI coding agents: codebase scan → bounded clarify pass (3–5 questions, not a grill) → reviewed design doc written to docs/plans/ → independent scored review → stop. No task board, no build. Use when you want a spec to discuss, hand off, or review before committing to implementation. Chains into absolute-work when ready to build. Triggers on "absolute spec", "write a spec", "spec out this feature", "draft a design doc", "I want a spec to hand off / review, don't build it yet".
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。
Design and build production-ready frontend interfaces with design systems, responsive layouts, accessible components, and dark mode support. Use when the user requests frontend design or provides relevant inputs for this 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。
Produce presenter-led AI avatar videos with Synthesia Studio and Synthesia API. Use for Synthesia-specific avatar video planning, avatar/voice/language selection, scripted scenes, template personalization, API job lifecycle, localization/dubbing, brand/training/product workflows, consent/rights/safety checks, artifact custody, troubleshooting, and final QA.
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。
Apply DDD tactical patterns when working with domain code, and validate proposed domain models before approval (design mode). Enforces aggregate design, value objects over primitives, entity identity rules, and bounded context boundaries. Use when creating or modifying domain models, designing aggregates, working in the domain layer, or when the user mentions 'domain', 'aggregate', 'value object', 'entity', 'bounded context', or 'DDD'.
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 CRISPR drug-modifier (chemogenomic) screens with drugZ (Li & Hart 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving 2-3x sensitivity over MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).
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 and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns. Use when screening genomes for AMR genes or tracking resistance in surveillance programs.
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。
Designs experiments to minimize and account for batch effects using balanced layouts and blocking strategies. Use when planning multi-batch experiments, assigning samples to sequencing lanes, or designing studies where technical variation could confound biological signals.
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。
Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.
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。