1,730 件 ・ 関連度順
概要と使いどころ
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
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。
Compatibility alias for the original ScrapeCreators social scraping skill. Use scrapecreators-api for current endpoint guidance and the task-specific Brand Growth research skills for finished 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。
Provides guidance for implementing OpenTelemetry instrumentation in .NET codebases, covering tracing (Activities/Spans), metrics, logs, naming conventions, error handling, performance, SDK setup, resources, context propagation, and API design best practices.
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 fix .NET HTTPS dev certificate trust issues on Linux. Covers the full certificate lifecycle from generation to system CA bundle inclusion, with distro-specific guidance for Ubuntu, Fedora, Arch, and WSL2.
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。
Write unit and integration tests for Akka.NET actors using modern Akka.Hosting.TestKit patterns. Covers dependency injection, TestProbes, persistence testing, and actor interaction verification. Includes guidance on when to use traditional TestKit.
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 PharmGKB / CPIC / DPWG for drug-gene interactions; calls CYP2D6/CYP2C9/CYP2C19/DPYD/TPMT/NUDT15/UGT1A1/SLCO1B1 star alleles and phenotype with PharmCAT, Cyrius (CYP2D6 structural variants), Aldy, Stargazer; applies Caudle 2020 activity-score translation. Use when implementing pharmacogenomic-guided prescribing, applying CPIC vs DPWG guidance, screening HLA risk alleles for ICI / antiepileptics / abacavir, or interpreting compound TPMT+NUDT15 thiopurine risk.
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 Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.
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 CUT&RUN (Skene Henikoff 2017) and CUT&Tag (Kaya-Okur 2019) chromatin profiling data. Handles SEACR vs MACS2 peak calling (with the btaf375 2025 benchmark guidance), pA-MNase vs pA-Tn5 vs pAG-Tn5 chimera differences, E. coli spike-in carryover normalization, IgG-only control logic (no input), characteristic fragment-size signatures (25-75 bp for CUT&Tag), and lower depth requirements (5M reads typical vs 25M for ChIP). Use when calling peaks from CUT&RUN/CUT&Tag, scaling by E. coli spike-in carryover, choosing SEACR norm mode, or comparing CUT&RUN/Tag results to traditional ChIP.
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。
Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.
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。
Computes and interprets treatment effect measures (OR, RR, RD, HR, NNT) with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen, MOVER, profile likelihood, Bender NNT) and reports marginal vs conditional estimands per FDA 2023 covariate adjustment guidance. Use when reporting treatment effects in confirmatory trials, comparing effect sizes across studies, or constructing forest plots.
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。
Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.
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。
Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection 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。
Builds and reviews SwiftUI views with modern MV architecture, state, composition, isolated previews, and migration guidance. Covers @Observable ownership, @State/@Bindable/@Environment wiring, view decomposition, ViewModifiers, environment values, .task loading, iOS 26+ handoffs, Writing Tools, clipboard availability, and performance. Use when structuring SwiftUI state, managing @Observable, composing views, previewing meaningful UI states, or correcting SwiftUI 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。
Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
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。
Expert guidance for simulating RoadRunner scenarios via the MATLAB programmatic API and Simulink co-simulation. Use when the user wants to run a simulation, step through a simulation, control actors during co-simulation, add observers, attach sensors, retrieve simulation logs, or read/write scenario variables. Covers simulateScenario, createSimulation, ScenarioSimulation set/get, ActorSimulation getAttribute/setAttribute, addObserver, SensorSimulation, Simulink co-sim blocks, and publishActorBehavior. NOT for project setup, scene building, scenario authoring, or trajectory export.
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。
CloudBase PostgreSQL access-pattern and slow-query quality guidance. Use when designing how tables are read and written, eliminating per-row database calls, adding indexes for filters or joins, reviewing high-traffic data access, or explaining a slow SQL query. Not for first-time PG SDK setup, login UI, or NoSQL collections.
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。
Guidance for using asc cli in this repo (flags, output formats, pagination, auth, and discovery). Use when asked to run or design asc commands or interact with App Store Connect via the 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。
Modern web design trends, principles, and implementation patterns for 2024-2025. Use this skill when designing websites, creating interactive experiences, implementing design systems, ensuring accessibility, or building performance-first interfaces. Triggers on tasks involving modern design trends, micro-interactions, scrollytelling, bold minimalism, cursor UX, glassmorphism, accessibility compliance, performance optimization, or design system architecture. References animation skills (GSAP, Framer Motion, React Spring), 3D skills (Three.js, R3F, Babylon.js), and component libraries for implementation guidance.
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。
Expert guidance for the Fabric CLI (`fab`) and the Fabric and Power BI REST APIs: workspaces, items, lakehouses, notebooks, pipelines, semantic models, reports, capacities, OneLake, deployment and admin. Also estimates the capacity units (CU) an operation will consume and its impact on the capacity before running it. Automatically invoke whenever the user mentions Fabric, Power BI Service, a Fabric or Power BI workspace, a capacity or F SKU, OneLake, `fab`, or asks to create, run, refresh, schedule, deploy or delete anything in Fabric, including preview items such as Plan, Ontology, Graph or Copilot.
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。
Friendly, jargon-free onboarding for people new to coding agents and Power BI agentic development. Invoke for setup, prerequisites, tool installation, terminal guidance, safety questions, or explanations of models, context, prompts, tools, and environments. Use setup mode for concise installation help, explain mode for guided learning, and improve-my-agent-setup for an existing setup audit.
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。
TOM and ADOMD.NET guidance via PowerShell for connecting to Power BI Desktop's local Analysis Services instance. Covers model enumeration, DAX queries, metadata modification, annotations, calendar definitions, field parameters, query tracing, DAX library package management (daxlib.org), and the Desktop Bridge for reloading and screenshotting the report canvas. Automatically invoke when the user mentions "Power BI Desktop", "Analysis Services port", "TOM", "ADOMD", "daxlib", "DAX library", "DAX UDF package", or asks to "connect to PBI Desktop", "query PBI Desktop with DAX", "modify PBI Desktop model", "add a measure to PBI", "capture visual queries", "create a field parameter", "validate DAX", "intercept DAX queries", "install daxlib", "add DAX SVG", "add IBCS", "reload the report canvas", "screenshot a report page", "Desktop Bridge", or to work with the model and report in Power BI Desktop together.
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。
Guidance for Power BI Project (PBIP) structure, thick and thin reports, project renames, forks, and validation. Use for .pbip, .pbism, .platform, definition.pbir, PBIP vs PBIX, or cross-cutting project operations.
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。