「order」の検索結果

Authors reproducible Nextflow DSL2 pipelines built on reactive dataflow, where processes communicate only through channels and execution order is not guaranteed. Use when deciding channel/dataflow (Nextflow) vs rule-based (Snakemake) authoring; wiring queue vs value channels and fixing shared-reference exhaustion with .first(); composing DSL2 modules and subworkflows with take/main/emit; selecting container/conda profiles and pinning images by digest for portability across local/SLURM/LSF/AWS Batch/Google Batch/Kubernetes executors; diagnosing why -resume misses the cache (nondeterministic input order, mtime on network filesystems, mutable :latest tags) with cache 'lenient' and -dump-hashes; managing work/ vs publishDir and dynamic retry escalation; and choosing whether to adopt an nf-core community pipeline or author from scratch.

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Extract line items, quantities, unit prices, delivery dates, and supplier details from purchase order documents.

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Inspects a recorded CARLA .log without replaying it — show_recorder_file_info for the header/actors/frames, collision queries between actor categories, and blocked-actor queries for vehicles that got stuck. Use when the user asks to "what's in this recording", "show recorder info", "which vehicles collided", "find collisions in the log", or "which actors were blocked/stuck".

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Automated WCAG 2.1 AA accessibility testing with axe-core and Lighthouse CI. Auto-detects frontend framework (React, Next.js, Vue, Angular, Svelte, Astro, Flutter, React Native), discovers all routes and interactive components, installs Playwright + axe-core for page-level scanning and jest-axe/vitest-axe for component-level testing. Generates tests for color contrast (4.5:1), alt text, form labels, ARIA attributes, heading order, landmark regions, focus visibility, keyboard navigation (tab order, focus traps, modal focus management, skip-to-content), screen reader compatibility (aria-live regions, error announcements, toast notifications), and Flutter Semantics validation (48dp touch targets, semanticLabel). Reports violations by severity (critical, serious, moderate, minor) with WCAG criterion references. Use when adding a11y testing, auditing accessibility compliance, fixing contrast issues, or validating keyboard and screen reader support.

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親イシュー配下のサブイシュー（孫以下の全子孫を含む）を依存順を保ちつつ worktree で並列に自動実装・push 前 review・PR 作成・CI 監視・マージ可能状態化まで一括自動化。 「イシューツリーを並列実装」「配下のサブイシューをまとめて実装」「ツリー全体を並列で実装して」「イシュー階層を自動開発」で使用。 per-issue 計画立案（Plan: セッション継承モデル）→実装（Implement: sonnet）の分業。push 前 review（Review 通過後にのみ push・PR 作成して CI を 1 回だけ起動）。 外部チェック構成は args の externalChecks で明示（{"app", "context"} の組で宣言。[] で「なし」を確定して不要待機なし・未指定なら自動マージ停止・slug のみの旧形式は自動マージ fail-closed）。 自動 squash merge は autoMerge: true + externalChecks 明示（全 App の信頼済み context 宣言込み）の opt-in で実行（merge-exec の自己取得再検証 + サーバー側 branch protection 実測が前提。既定 false はマージ可能状態で停止し人間がマージ。サーバー側 workflow サンプル（upstream の docs/implement-issue-tree/auto-merge-sample.yml 参照）+ branch protection への委譲も可）。並列度（parallel）と依存（dependsOn）で実行順を制御。 Phase 単位で厳密に直列化したい場合は phaseGate: true（opt-in。ルート直下の子〔Phase 親〕を sub-issues リスト順に直列化し、前 Phase の全子孫が merged/closed になるまで次 Phase 配下に着手しない。既定 false は現行の post-order 優先度のみ）。 着手できる件数・blocked になる件数を事前に知りたい場合は dryRun: true（何も書かずに見積りだけ返す）。 単一イシューの実装は implement-issue、PR レビューは implement-review-pr を参照。

TanStack Table (React Table) v9 ヘッドレステーブル (@tanstack/react-table) の API リファレンス。 ark-ui / chakra-ui のスタイル付き Table とは別。 useTable, tableFeatures, createColumnHelper, flexRender, createCoreRowModel, sorting, column / global / fuzzy filtering, faceting, pagination, row selection, expanding, grouping / aggregation, column / row の ordering・pinning・sizing・visibility, virtualization。 v8 legacy (useReactTable / getCoreRowModel) と v9 移行。

GNU Make / Makefile リファレンス。 ターゲット、prerequisite、order-only、変数展開、自動変数、pattern rule、.PHONY、-j 並列・再帰 make、増分ビルド。 Rust / Cargo / xtask、Node.js / pnpm / Turborepo、Git hooks / CI との責務分離と開発コマンド共通化。 Makefile 設計・レビュー、Bash サンプル、診断スクリプト。

Motion アニメーションライブラリ (旧 Framer Motion) リファレンス。 React コンポーネント motion, AnimatePresence, AnimateView, LayoutGroup, LazyMotion, MotionConfig, Reorder。hooks useAnimate, useScroll, useSpring, useTransform, useMotionValue, useInView。 vanilla JS API animate, scroll, inView, hover, press, stagger, spring, timeline, motionValue。Vue 版 (motion-v) v-motion ディレクティブ, useScroll 等の composable, Motion+ 限定コンポーネント (Carousel, Cursor, Ticker, Typewriter, AnimateNumber)。transitions / layout / drag / gestures / SVG / scroll アニメーション、accessibility, performance, bundle 最適化, troubleshooting。

Defines cell populations in flow and spectral cytometry through manual gates (rectangle, polygon, quadrant, boolean) and reproducible automated gating (openCyto gating templates, flowDensity data-driven thresholds, flowClust model-based gates), organized as a hierarchical GatingSet (flowWorkspace) and round-tripped with FlowJo via CytoML. Covers the canonical gate order (time -> debris -> singlets -> live -> lineage), FMO-vs-isotype boundary setting, gate-order dependence and recompute semantics, rare-event/MRD gating, and per-population statistics. Use when building a gating strategy, automating a manual FlowJo scheme across samples, choosing manual vs data-driven gates, or extracting population frequencies.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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Think through the consequences of consequences — not just what happens immediately, but what happens next, and next after that, across time. Load when a decision looks obviously good or obviously bad on initial read, when the user is optimising for a short-term outcome that might create a long-term problem, when unintended consequences are a concern, or when deep-thinking diagnoses a second-order frame. Triggers on "what are the downstream effects", "what happens after that", "unintended consequences", "think ahead on this", "long-term vs short-term", or "what comes after that". Based on Howard Marks second-level thinking and Farnam Street mental models. Most powerful for decisions with delayed consequences or systemic effects.

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。

Defines cell populations in flow and spectral cytometry through manual gates (rectangle, polygon, quadrant, boolean) and reproducible automated gating (openCyto gating templates, flowDensity data-driven thresholds, flowClust model-based gates), organized as a hierarchical GatingSet (flowWorkspace) and round-tripped with FlowJo via CytoML. Covers the canonical gate order (time -> debris -> singlets -> live -> lineage), FMO-vs-isotype boundary setting, gate-order dependence and recompute semantics, rare-event/MRD gating, and per-population statistics. Use when building a gating strategy, automating a manual FlowJo scheme across samples, choosing manual vs data-driven gates, or extracting population frequencies.

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。

Structures biological experiments so inference is valid by construction, covering Fisher's principles (randomization, replication, local control), the experimental-vs-observational unit distinction and pseudoreplication (Hurlbert 1984; Lazic 2018), randomization mechanics (complete, restricted, stratified, rerandomization, run-order), blocking layouts (randomized complete block, Latin square, incomplete block), factorial designs and interactions, and the split-plot/nested error strata hidden inside multi-batch genomics. Use when deciding the experimental unit and what counts as a replicate, planning randomization and run order, choosing a blocked/factorial/split-plot/nested layout, avoiding pseudoreplication in cell-culture or animal studies, or specifying the random-effects structure of the analysis model. For assigning samples to sequencing batches/lanes/plates and batch-effect correction see experimental-design/batch-design; for regulated clinical-trial randomization see clinical-biostatistics.

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 the user asks about US-Canada cross-border CMV operations — CVOR (Commercial Vehicle Operator's Registration), NSC (National Safety Code), Ontario / Quebec / BC specific rules, US carrier obtaining Canadian operating authority, FAST card for drivers, customs (CBSA), Health Canada hazmat, and how Transport Canada equivalents differ from US FMCSA. Reference USMCA + Transport Canada NSC 14.

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 when the user asks to "これらのIssueを全部実装して", "implement these issues autonomously", "Issue一覧を自動で片付けて", "これらのタスクを順番に実装してPRにして", or provides a list of GitHub Issue numbers/URLs for autonomous batch implementation. Fetches all specified Issues, resolves dependency order, then iterates through each — creating a worktree, implementing, and opening a PR — without user intervention.

This skill should be used when the user wants to "synthesize two competing solutions without averaging", "resolve a design/value disagreement by lifting to a higher frame", "止揚 / アウフヘーベン", "矛盾を止揚", "独立案を統合", "平均化せず統合", "contradiction lift", "sublate competing designs", or has two good-but-divergent answers to the same question and wants a higher-order resolution (a selection mechanism) or an honest aporia — not a compromise. NOTE: Use this when two independent solutions diverge and you want to PRESERVE both truth-moments while lifting to a higher frame. Use devils-advocate to stress-test ONE proposal with an assigned opponent, strong-inference to find an unknown cause, and dialectic-loop to validate a claim against a real corpus.

Layout structure for web interfaces, from grouping and alignment to reading order, progressive disclosure, and adaptive breakpoints. Use when structuring a page or component, spacing or aligning controls, deciding what collapses at small sizes, handling RTL layout direction, or reviewing frontend code for layout. Triggers on layout, spacing, alignment, grouping, negative space, whitespace, visual hierarchy, reading order, progressive disclosure, breakpoints, responsive layout, container queries, safe area, full-bleed, edge-to-edge, layout margins, RTL layout, logical properties.

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编写C++通用模板函数，支持std::map和std::unordered_map作为通用容器传入，处理const正确性，支持可选的allocator模板参数，且禁止在函数内部构建临时对象。

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。

Compare cross-border e-commerce shipping options, packaging tactics, customs-risk signals, and speed-versus-cost tradeoffs for sellers, operations teams, and marketplace operators. Use when choosing routes, carriers, declaration practices, or packaging plans for parcel shipments without relying on live carrier APIs.

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CCXT cryptocurrency exchange library for Python developers. Covers both REST API (standard) and WebSocket API (real-time). Helps install CCXT, connect to exchanges, fetch market data, place orders, stream live tickers/orderbooks, handle authentication, and manage errors in Python. Use when working with crypto exchanges in Python projects, trading bots, data analysis, or portfolio management. Supports both sync and async (asyncio) usage.

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Break a clear scope or accepted specification into ordered tasks/packages when the user explicitly asks for a plan, estimate, dependency order, or task breakdown; do not trigger for ordinary implementation, every multi-step task, speculative parallelism, review, or completion.

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Use when authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.

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Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error ...

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Complete construction estimating and cost management system. Use when preparing project estimates, bid proposals, cost breakdowns, value engineering, change order management, or construction budget tracking. Covers residential, commercial, and infrastructure projects. Trigger on 'estimate', 'construction cost', 'bid', 'takeoff', 'cost breakdown', 'change order', 'value engineering', 'construction budget', 'unit pricing', 'RSMeans'.

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。