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概要と使いどころ
Lightweight guidance for using the Redis Rate Limit TypeScript SDK, including setup steps, basic usage, and pointers to advanced algorithm, features, pricing, and traffic‑protection docs.
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Generate, extend, or audit design tokens in DTCG format with the 3-tier architecture (primitive → semantic → component). Use when the user wants a color palette, type scale, spacing/shadow/radius/motion tokens, multi-brand theming, or wants to validate token files. Covers colors, typography, spacing, shadows, borders, breakpoints, motion, gradients, opacity, blur, sizing, states, theming.
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。
Summarize YouTube videos by extracting transcripts and generating structured notes. Use when the user wants to summarize a YouTube video, extract key points from a talk, create study notes from a lecture, or get timestamps for important moments. Supports multiple URL formats and languages.
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。
Amap (Gaode) Maps comprehensive service for POI search, route planning, travel planning, nearby search, heatmap visualization, and geocoding. Use when user wants to search locations, plan routes, find nearby places, or visualize geographic 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。
AI PPT Generator skill. Quickly generate well-structured, professionally formatted presentation drafts from topics and outlines. Use when user wants to create PowerPoint presentations.
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。
从零开始或通过转换 PowerPoint 文件创建令人惊叹、动画丰富的 HTML 演示文稿（Presentations）。适用于用户想要构建演示文稿、将 PPT/PPTX 转换为 Web 页面或为演讲/路演创建幻灯片（Slides）的场景。通过视觉探索而非抽象选择，帮助非设计师发掘其审美偏好。
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 adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and patterns.
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。
从零开始创建令人惊叹、动画丰富的 HTML 演示文稿，或通过转换 PowerPoint 文件生成。适用于用户想要构建演示文稿、将 PPT/PPTX 转换为 Web 页面、或为演讲/路演创建幻灯片的场景。帮助非设计师用户通过视觉探索而非抽象选择来发现他们的审美偏好。
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。
从零开始或通过转换PowerPoint文件创建令人惊艳、动画丰富的HTML演示文稿。当用户想要构建演示文稿、将PPT/PPTX转换为网页格式，或为演讲/推介创建幻灯片时使用。帮助非设计师通过视觉探索而非抽象选择发现他们的美学。
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。
从头开始创建令人惊叹、动画丰富的 HTML 演示文稿，或通过转换 PowerPoint 文件生成。当用户想要构建演示文稿、将 PPT/PPTX 转换为网页版，或为演讲/路演创建幻灯片时使用。帮助非设计师通过视觉探索而非抽象选择来发现他们的审美。
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。
Make the build step a real gate on what you actually distribute — build scripts that warn and exit 0 on a missing input, size checks with only an upper bound, hand-maintained file lists that drift from the entrypoints they must cover, committed bundles that go stale when only the source changes, GNU-only shell in release scripts that aborts on the other OS, and verification that runs against the source tree instead of the artifact. Use when writing or reviewing a build/package script, a `dist/` copy step, a release workflow that uploads a zip or installer, or a committed compiled asset.
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。
Automatically find references for academic paper Markdown files. Reads full paper text, identifies each knowledge point requiring citation (epidemiological data, mechanism descriptions, existing research conclusions, etc.), searches PubMed for 3-5 most relevant articles per kn...
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 structured SOAP notes from clinical narratives, transcripts, or existing notes; use when the user needs de-identified clinical documentation organized into Subjective, Objective, Assessment, and Plan sections, with clear assumptions and review points.
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Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.
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 a structured case-control study framework with explicit source population logic, control selection rules, matching decisions, exposure measurement planning, and bias-control checkpoints.
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 complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk review.
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 discovery, modeling, and validation workflows for prognostic biomarkers in biomedical and clinical research. Always use this skill when the user needs a prognostic biomarker study blueprint rather than a diagnostic test protocol, predictive biomarker design, treatment recommendation, or a completed manuscript. Focus on endpoint family, follow-up horizon, time scale, candidate marker strategy, model-building logic, risk stratification framework, and internal/external validation requirements. Do not invent cohort size, event rate, assay readiness, literature support, or validation access.
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 retrospective or prospective clinical cohort study protocols for biomedical and clinical research. Always use this skill when the user needs a cohort-based study plan rather than a general study idea, evidence summary, or mechanistic experiment design. Focus on cohort appropriateness, enrollment logic, baseline time-zero definition, follow-up structure, endpoint definition, variable collection, confounding control, and a coherent primary statistical analysis line. Do not invent data availability, follow-up completeness, outcome ascertainment quality, sample size adequacy, or causal interpretability.
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Use when performing time-dependent ROC curve analysis for survival data with follow-up time, event status, and a numeric marker. Supports CSV/TXT/TSV/Excel input, `risk_score` as the default marker unless `--marker_col` is provided, parameter validation, standardized output directories, AUC table export, ROC point export, and PDF figure generation.
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。
Extracts concrete unmet clinical needs from guidelines, reviews, real-world studies, and clinical-practice evidence. Use this skill when a user wants to turn broad medical research value into specific clinical pain points such as weak early detection, poor risk stratification, treatment-response heterogeneity, monitoring gaps, diagnostic delay, undertreatment, overtreatment, or implementation failure. Always ground unmet-need claims in retrieved evidence and distinguish true care gaps from generic statements of importance.
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Explains why studies on the same biomedical topic reach different or opposing conclusions by auditing differences in population, endpoint definition, sample source, assay or platform, study design, statistical model, adjustment strategy, validation chain, and bias control. It separates true contradiction from apparent contradiction caused by framing or methods. Never fabricate references, PMIDs, DOIs, trial identifiers, dataset details, platform details, study features, or conflict explanations that are not supported by the input.
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Rapidly maps the evidence landscape around a medical topic by organizing major research streams, target populations, endpoints, methods, evidence density, and thin areas. Use this skill BEFORE medical-research-gap-finder — it provides the structured landscape that makes formal gap analysis more rigorous. Do not use for formal gap identification, study design, or protocol planning directly.
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。
Guide for upgrading Stripe API versions, webhook endpoints, server-side SDKs, Stripe.js, and mobile SDKs
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 mapping code paths, entrypoints, and likely hot files before profiling.
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。