「power」の検索結果

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Best practices for building and maintaining applications with PowerSync: Cloud and self-hosted setup, sync configuration, client SDK usage, backend integration (Supabase, custom Postgres, MongoDB, Azure DocumentDB, MySQL, MSSQL), schema changes, watch and reactive queries (useQuery), attachments, the upload queue, and debugging. Use this skill whenever the user mentions PowerSync, a @powersync/* package (@powersync/web, @powersync/react-native, @powersync/node), the powersync Flutter/Dart package, the powersync Rust crate, wa-sqlite, offline-first sync, local-first architecture, sync rules, sync streams, uploadData, fetchCredentials, disconnectAndClear, logout or user switching in a synced app, real-time data replication, Electric Cloud migration, Electric Shapes, an app stuck on Syncing, data not syncing, or wants to add offline-capable sync to a mobile or web app, even if they do not explicitly name PowerSync.

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。

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Compute statistical power, required sample size, and minimum detectable effect (MDE) for a study design, then write a registry-ready power section. Handles two-arm RCTs (with clustering / ICC and unequal allocation), multiple-arm corrections, and a simulation-based power option for non-standard designs (DiD/event-study, IV, panel). Use when user says "power analysis", "power calculation", "MDE", "minimum detectable effect", "how big a sample do I need", "is my study powered", "power for an RCT", or when /preregister needs a power section for an experiment. Produces a power/MDE table, power curves, and a methods paragraph to paste into a preregistration.

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。

superpowersの作業記録を読み、作業の重複や計画逸脱、時間・トークン消費などを調べます。ファイルの行番号を根拠に、経緯を報告書へまとめるスキルです。

• 作業の重複や計画逸脱を調べたいとき
• セッションの時間や消費量の確認
• スキルが使われたか確認したいとき

発表用のメモやPowerPointから、ブラウザで動くHTMLスライドを作ります。見本でデザインを選び、画面に収まるレイアウトとアニメーションを整えます。

• 登壇や社内報告のスライド作成
• PowerPointをHTML化したいとき
• 見本から資料のデザインを選びたいとき

Calculates sample sizes and statistical power for study planning. Applies when someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for complex designs — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Also handles requests that only mention an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-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。

Sample-size and statistical power calculations for planning studies. Use whenever someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-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。

Author, validate, and test Power Query M expressions in semantic model partitions. Automatically invoke when the user mentions "Power Query", "M code", "M expression", "partition expression", "query folding", or asks to "write Power Query", "fix Power Query", "test a partition", "preview partition data", "debug Power Query step", "optimize Power Query".

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。

Sets up a Power Platform Pipeline for automated Power Pages deployments. Power Platform Pipelines is Microsoft's native CI/CD tool built into the Power Platform — no external infrastructure required. Use when asked to: "set up ci/cd", "create pipeline", "setup pipeline", "set up power platform pipelines", "create power pipelines", "automate deployments", "set up automated deployment", "create deployment pipeline", "use power pipelines". Also handles: "set up github actions" or "set up azure devops pipeline" (shows coming-soon guidance for those platforms).

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。

Power Platform ソリューションの全体アーキテクチャを設計する。Copilot Studio / Power Automate / Code Apps / Copilot Managed Runtime / Power Pages / AI Builder の使い分け判断、コンポーネント選定、統合パターンを決定する。社内向け画面は利用者のライセンス（Power Apps Premium か、Copilot Credits の従量課金か）と利用頻度をヒアリングし、Code Apps と Copilot Managed Runtime を使い分ける。構成が確定したら、実装着手前に admin スキルで環境チェック（既定環境ではないか・マネージド環境・Code Apps / MCP の有効化・セキュリティ ロール）と DLP 事前チェック（使用コネクタがブロックされていないか・Business / Non-business が混在しないか）を実行して結果をユーザーに提示する。Agent 365 の AI チームメイトを採用する場合はライト実装（PoC）と本格実装（private リポジトリ + CI/CD + Agent Evals）を AskUserQuestion で選ばせ、Git ホスティング（GitHub / Azure DevOps Repos / その他）も確定してから実装へ進む。外部の文章を読むエージェントではプロンプト インジェクション対策を設計段階で工数に含める。

Expert-level power systems covering power generation, transmission, distribution, power flow analysis, fault analysis, protection, and power electronics.

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。

Foundation skill for Power Automate via FlowStudio MCP — auth setup, the reusable MCP helper (Python + Node.js), tool discovery via `list_skills` / `tool_search`, and oversized-response handling. Load this skill first when connecting an agent to Power Automate. For specialized workflows, load `flowstudio-power-automate-build`, `flowstudio-power-automate-debug`, `flowstudio-power-automate-monitoring` (Pro+), or `flowstudio-power-automate-governance` (Pro+) — each contains the workflow narrative, this skill provides the plumbing they all rely on. Requires a FlowStudio MCP subscription or compatible server — see https://mcp.flowstudio.app

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。

PowerPoint資料の作成・内容抽出・編集を支援するスキル。文章やグラフ、画像、発表者ノートを扱い、会社のテンプレートに沿った資料作成にも対応します。

• 報告資料や提案資料を作りたいとき
• 資料から文章やノート、グラフ値を抽出
• ロゴや文言、グラフ値を更新したいとき

Systematically deobfuscates multi-layer PowerShell malware using AST analysis, dynamic tracing, and tools like PSDecode and PowerDecode to reveal hidden payloads and C2 infrastructure. Use during incident response or malware analysis when a PowerShell script is obfuscated with encoding, string manipulation, or invocation tricks and you need to recover the underlying commands, dropped payloads, or C2 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。

Monitor and control Tesla Powerwall and energy sites through the Tesla Fleet API: live power status, backup reserve, operation mode, storm watch. Trigger phrases: tesla powerwall, powerwall, tesla energy, backup reserve, storm watch.

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。

Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-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。

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。

Power BI custom visual (.pbiviz) development with the pbiviz toolchain and its MCP server. Automatically invoke when the user mentions "custom visual", "pbiviz", "develop a Power BI visual", "powerbi-visuals-tools", "IVisual", "capabilities.json", "visual formatting model", "visual certification", "publish a visual to AppSource", or asks to scaffold, build, debug, package, certify, or publish a .pbiviz developer visual.

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 whenever the user mentions "pbir", "pbir-cli", "Power BI reports", or "PBI reports", works with .pbir, .pbip, or .pbix files, or wants to refresh, screenshot, or visually verify a report that is open in Power BI Desktop. Covers creating, exploring, formatting, validating, and publishing Power BI reports through the pbir CLI and object model, plus driving Power BI Desktop (canvas reload, page screenshots) and querying connected or local semantic models.

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。

Activates and provisions a Power Pages website in a Power Platform environment via the Power Platform REST API. Use when the user wants to activate, provision, turn on, or enable a Power Pages website or portal.

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。