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概要と使いどころ
Use when reviewing rendered HTML, interactive components, or design-system patterns related to Use valid ARIA role values. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Ensure ARIA attributes are valid. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Ensure ARIA roles are contained by required parent roles. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Provide accessible names for ARIA command elements. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Use only allowed ARIA attributes for each role. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Remove focusable elements from aria-hidden containers. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Use valid values for ARIA attributes. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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。
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', 'adversarial plan', 'hostile planning', 'cross-critique plan', '하이퍼플랜', '적대적 계획', '교차 비평'.
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。
Adversarial multi-agent planning: a hostile team cross-critiques a plan before it is formalized. Use when planning needs maximum rigor or the user asks for a hyperplan / adversarial or cross-critique plan.
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。
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
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。
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'creative testing,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' 'static ads,' 'ad templates,' 'iMessage ad,' 'ChatGPT ad,' 'creative strategy,' 'creative roadmap,' 'creative retro,' 'hook writing,' 'creative review page,' 'motion video ad,' 'faceless video ad,' 'UGC ad,' 'greenscreen ad,' 'TikTok/Reels ad format,' 'Meta ad format tier list,' or 'creative format taxonomy.' Use it to produce or iterate ad copy at scale. Copy avoids AI tells like 'it's not X, it's Y' reveals. For campaign strategy and targeting, see ads. For landing page copy, see copywriting. Test hypotheses must be falsifiable, naming the metric, the comparison, and the expected direction.
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 zero-shot time-series forecasting with Google's TimesFM, including regular-grid CSV preparation, quantile forecasts, XReg covariates, and held-out evaluation. Uses the Apache-licensed TimesFM 2.5 checkpoint by default and documents the distinct TimesFM 3.0 multivariate API and weight-license requirements.
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。
Supports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.
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。
Queries public GenSpectrum LAPIS data for pathogen genomic surveillance, current lineage nomenclature, weekly sequence proportions, reporting delays, and descriptive mutation frequencies. Use for variant surveillance, Pango lineage validation, dominant submitted lineages, Nextclade assignment provenance, SARS-CoV-2, influenza/H5N1 clades, RSV, mpox, measles, dengue, or LAPIS queries. Distinguishes sequence prevalence from infection prevalence, clades from genotypes, missing calls from reference matches, and sampling changes from biological growth advantage.
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。
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
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 anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered 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。
Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.
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。
Conventions for SGLang environment variables — where to define, how to access, how to name, and how to deprecate. Use when adding, renaming, or reviewing any `SGLANG_*` environment variable (or migrating a legacy `SGL_*` alias), or when touching `python/sglang/srt/environ.py`.
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。
为角色/场景/道具设计视觉资产、编写或修复 VisualVariant 与阵容图的生成 Prompt 时使用。涵盖参考图布局（艺术身份板/序列关键帧/环境研究板/道具研究 板）、构图与镜头语言、图片审核误判规避、实体 continuity 与以主图为参考 的跨 Variant 衍生设计。不用于视频 Prompt 编译（见 professional-media-prompts）、 纯素材剪辑或只评价已生成产物。
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。
Identify poisoned training data and backdoored ML models across the pipeline using IBM's Adversarial Robustness Toolbox (activation clustering, spectral signatures, trigger reconstruction), Cleanlab for label-quality issues, and supply-chain checks like weight-hash verification and safetensors enforcement. Use before training or deploying on third-party/user-contributed data or downloaded checkpoints, during ML supply-chain reviews, or when investigating model misbehavior tied to specific inputs (suspected backdoor trigger).
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。
Pre-deployment security audit of Solidity smart contracts in a Foundry project. Combines static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing (forge fuzz + invariant tests with handlers) to catch reentrancy, access-control, oracle/price manipulation, and arithmetic bugs BEFORE deploying to an EVM chain. Also enforces key hygiene (no plaintext private keys, encrypted cast keystore) and a secure deploy workflow. Use when writing, reviewing, testing, or deploying Solidity/Foundry contracts, building a dApp, or working with forge/cast/anvil, MetaMask, or Web3/DeFi code.
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 Intel CHIPSEC to assess platform firmware configuration, SPI flash write protection, BIOS lock, SMM/SMRR, and Secure Boot variable state, dump SPI flash, and triage UEFI variables for firmware-level threats.
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。
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," or "hypothesis." For tracking implementation, see analytics-tracking.
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。
HeroUI v3 React component library (Tailwind CSS v4 + React Aria). Use when building UIs with HeroUI — creating Buttons, Modals, Forms, Cards; installing @heroui/react; configuring dark/light themes with oklch variables; or fetching component docs. Keywords: HeroUI, Hero UI, heroui, @heroui/react, @heroui/styles.
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。