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概要と使いどころ
shadcn/ui expert guidance — CLI, component installation, composition patterns, custom registries, theming, Tailwind CSS integration, and high-quality interface design. Use when initializing shadcn, adding components, composing product UI, building custom registries, configuring themes, or troubleshooting component issues.
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, synthesize, and iteratively improve agent skills following the Agent Skills specification. Use when asked to "create a skill", "write a skill", "synthesize sources into a skill", "improve a skill from positive/negative examples", "update a skill", or "maintain skill docs and registration". Handles source capture, precision passes, authoring, registration, and validation.
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 logistic regression for clinical trial outcomes (binary, ordinal, multinomial) with marginal-vs-conditional estimand reporting per FDA 2023 covariate adjustment guidance, g-computation/standardisation for marginal effects, modified Poisson for RR, Brant test for proportional odds, Firth penalty for separation, and Hauck-Donner detection. Use when modeling binary or ordinal endpoints in confirmatory or exploratory clinical trials.
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。
Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform
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。
Literature: retrieve document-level scientific evidence from publications, clinical-trial registries, and patent sources. Use for PubMed records, reproducible searches, trial registrations, patent evidence, abstracts, study metadata, stable identifiers, and citation provenance.
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 key terms from multiple signed contracts and build a structured XLSX contract register tracking parties, dates, value, and renewal terms.
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 websites and web apps using 21st.dev — the largest marketplace of shadcn/ui-based React Tailwind components with 1400+ components. Use when user mentions "21st.dev", "21st", "ใช้ 21st", "จาก 21st", "build with 21st", "21st component", "21st magic MCP", or references the 21st.dev component registry in any language. Covers building complete sites (landing pages, dashboards, portfolios, e-commerce storefronts, auth pages), browsing and installing individual 21st.dev components into existing projects, and setting up the 21st.dev MCP server. Also trigger when user wants premium UI components specifically from the 21st.dev registry. Do NOT trigger for general web development, standard shadcn/ui, plain Tailwind CSS, React Native, API development, testing, deployment, or any task that doesn't explicitly reference 21st or 21st.dev.
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。
Figma REST API / Plugin API / Widget API / Code Connect / MCP Server リファレンス。 OAuth / Personal Access Token / Plan Access Token 認証、files, variables, webhooks, Dev Mode, Dev Resources, SCIM, activity-logs, library-analytics エンドポイント。 figma グローバルオブジェクト、node types (FrameNode, TextNode, ComponentNode 等)、 data types、figma.variables、figma.codegen、figma.ui。 useSyncedState, useSyncedMap, usePropertyMenu, AutoLayout, register。 Code Connect CLI / UI / React / SwiftUI / Compose / HTML / Storybook / custom parsers。 Figma MCP Server ツール・プロンプト・Code to Canvas・Write to Canvas。
Fastify (Node.js 高速 HTTP サーバーフレームワーク, v5) の API リファレンス。 `fastify.register`, encapsulation, `fastify-plugin`, `decorateRequest` / `decorateReply`, `onRequest` / `preHandler` / `onSend` フック, JSON Schema + Ajv, Type Providers (TypeBox / Zod), `fastify.inject`, `FST_ERR_*`, find-my-way ルーティング, fastify-cli, v4→v5 移行。
OpenAI Apps SDK / ChatGPT plugins (developers.openai.com/plugins) のリファレンス。 ChatGPT 内で動くアプリを MCP サーバーとして公開する側の API。 window.openai, useOpenAiGlobal, registerAppTool, ui://widget, _meta, openai/outputTemplate, OAuth 認証, Checkout API, 接続テスト・審査・申請。
React Hook Form v7 (RHF、非制御フォームライブラリ) リファレンス。 別名: rhf, React-Hook-Form。 useForm, register, handleSubmit, watch, setValue, getValues, reset、 Controller (制御コンポーネント連携)、useFieldArray (動的フィールド)、 バリデーション、resolver (Zod / Yup / Joi 連携)、エラーメッセージ、formState。
Swift Standard Library・Concurrency・プロトコル/ジェネリクス・Observation リファレンス。 async/await、actor、Sendable、Task、TaskGroup、AsyncSequence、AsyncStream、 Equatable、Hashable、Comparable、Codable、Identifiable、Optional、Result、 generics、some/any opaque types、Observable、@Observable、ObservationRegistrar。
Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.
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 recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.
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。
Discover RBP binding motifs from CLIP-seq peaks or single-nucleotide crosslink sites using HOMER, MEME/STREME, kpLogo, mCross (CL-position-registered motifs), PEKA (positional k-mer enrichment), RBPamp (affinity), and RNA Bind-n-Seq (RBNS) cross-validation. Use when characterizing RBP sequence specificity, registering motifs to crosslink positions, validating in vivo CLIP motifs against in vitro RBNS Kd, reconciling motif disagreements across tools, or correcting for the uracil crosslinking bias that contaminates raw CLIP motif logos.
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 logistic regression for clinical trial outcomes (binary, ordinal, multinomial) with marginal-vs-conditional estimand reporting per FDA 2023 covariate adjustment guidance, g-computation/standardisation for marginal effects, modified Poisson for RR, Brant test for proportional odds, Firth penalty for separation, and Hauck-Donner detection. Use when modeling binary or ordinal endpoints in confirmatory or exploratory clinical trials.
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 Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.
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。
Issues, busca, comentários, tags, artigos e registro de trabalho no YouTrack Cloud via MCP oficial. Use quando o usuário disser "YouTrack", "criar issue", "minhas issues", "buscar tarefas", "comentar na issue", "atribuir para", "mudar o estado", "registrar horas", "artigo da knowledge base", ou citar um ID tipo PROJ-123. Boards e sprints são da skill youtrack-rest.
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。
Deliver a small bounded change inside an initialized SDD Composy workspace through the quick path: at most five implementation files, a registered TASK, TDD, evidence, trace, and a verified verdict, escalating otherwise. Use for a precise objective with no existing task — 'ajuste rápido via SDD', 'quick fix under SDD', 'small change to X in the SDD flow'. Do NOT use for an already registered task (sdd-execute), for architecture, migrations, or destructive work, or in repositories without SDD Composy (other plugins' quick).
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 optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions "form optimization," "lead form conversions," "form friction," "form fields," "form completion rate," "contact form," "nobody fills out our form," "form abandonment," "too many fields," "demo request form," or "lead form isn't converting." Use this for any non-signup form that captures information. For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-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。
Package and publish a skill to the skills.sh community registry, a public GitHub repo, or both. Load when the user asks to publish a skill, share a skill publicly, submit a skill to the registry, release a skill, or when universal-skill-creator offers publishing as a final step after creation. Also triggers on "push this skill to skills.sh", "make this skill public", "share this skill", or "contribute this skill to the community". Validates quality before publishing, packages correctly (zip for multi-file, .md for atomic), writes a README if missing, and publishes via npx skills CLI.
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 Container Registry SDK for Python. Use for managing container images, artifacts, and repositories.
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。
Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.
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 recurrent and driver copy number alterations across a tumor cohort with GISTIC2 (G-score, Ziggurat deconstruction, focal vs broad/arm-level analysis, q-values from permutation) and quantify copy-number signatures with the Steele 2022 COSMIC framework and the Drews 2022 CINSignatures framework. Covers driver-gene localization from recurrence peaks, distinguishing focal drivers from arm-level passengers, and the caller-sensitivity caveats of copy-number signatures. Use when finding recurrently amplified or deleted regions in a cohort, localizing driver genes, separating focal from broad events, running GISTIC2, or extracting copy-number mutational signatures.
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。