「value」の検索結果

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

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 the user asks to "build a message house", "write a PR-FAQ for our launch", or "define the launch narrative and value pillars"; derives from the positioning canvas a message house — tagline, one-liner, three value pillars, per-persona proof points (each labeled Measured / User-provided / [needs source]) — plus a working-backwards PR-FAQ narrative spine (launch-day tense, empty-chair test, five external + five internal FAQs) and per-channel message angle packs (angles, not finished copy). Not for the positioning canvas itself — use positioning-mapper; not for finished blog posts or pages — use content-writer; not for ad or email units — use each discipline creative builder; not for claim adjudication — use offer-claims-registry. 消息屋/PR-FAQ/价值支柱/发布叙事

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 the user asks to "build audience segments from my customer list", "make value-based / lookalike seed lists", "set up exclusion / suppression segments", or "map audiences to funnel stages across platforms"; turns the user's OWN customer/CRM/GA4 export into seed audiences, value-based lookalike SEED lists, exclusion/suppression segments, and a cross-platform funnel-stage targeting map, informing the ROAS A (Audience) dimension. Not for building account structure or match types — use campaign-architect; not for organic SERP intent — use keyword-research. 付费广告受众分群/种子人群/排除人群/相似人群种子

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。

Product-led growth and customer-base growth for B2B SaaS. Use this skill for self-serve funnel work (activation, time-to-value, free trial vs freemium, PQL definition, in-product upgrade moments, sales-assist triggers) and for growing revenue from existing customers (adoption, expansion, churn-save, renewal marketing, net revenue retention). Also triggers on: PLG, product-led growth, activation, aha moment, time to value, free trial, freemium, PQL, product qualified lead, onboarding, self-serve, customer marketing, expansion revenue, upsell, cross-sell, churn, retention, NRR, renewal.

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テストは存在するがアサーションが実質何も検証しておらず、実装が壊れても落ちない（常に PASS する）構造を diff-time で検出する。Check 1 missing assertion（テスト本体にアサーションが無い）、Check 2 tautological assertion（定数同士・入力自身・mock の戻り値自身を assert し SUT に依存しない）、Check 3 nonexistent expected literal（assertDontSee / assertNotContains 等の期待文字列が対象ファイルに実在しない）、Check 4 stale expected value（同一 diff で対象の出力が変わったのに期待値が据え置き）、Check 5 unscoped expectation（汎用的な属性・クラスを応答全体に対して assert し対象要素にスコープされていない）、Check 6 swallowed failure（例外の握り潰しや到達しない位置のアサーションで判定が成立しない）、の 6 Check を対象とする report-only。テストの有無は test-existence、未テスト経路の量は coverage-gap、非決定性は flaky-test、命名は test-naming、JS/TS の un-awaited resolves / rejects は vitest-mock-isolation、tdd-ledger artifact ベースの RED/GREEN 検証は plangate-tdd-evidence、.only / .skip / xit / @ts-ignore と空の catch は heuristic-review.mjs の決定論検出器へ委譲する

SharedPreferences (v2.5.5) for Flutter providing simple persistent key-value storage for non-sensitive user settings and app preferences. Use this skill when storing user preferences (theme mode, language selection, font size), app settings and configuration, feature flags or A/B test assignments, simple cache data, onboarding completion status, last selected values (filters, sort options), user consent flags, or any non-sensitive data that survives app restarts. Supports String, int, double, bool, and StringList types. NOT suitable for storing tokens, passwords, API keys, or any sensitive/encrypted data (use flutter_secure_storage instead). Ideal for quick persistent storage without database overhead.

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End-to-end Android indie idea workflow — feature-build phase only (no monetization). Phased — discover (if no idea) → generate 2 candidates → refine scope (offline/online, sharing, MVP vs full, core-value features) → risk/reward/tradeoff analysis when scoping down → emit idea brief. Use for greenfield app concepts, new feature ideation, idea discovery, or pre-design discovery before writing a design document. Triggers — new app idea, feature concept, indie dev brainstorm, validate idea, refine idea, what should I build, find an app idea, idea pipeline, I have no idea, help me find an app idea, scope down, MVP scoping, core value features.

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Expert en Domain Driven Design (bounded contexts, aggregates, value objects, repositories, ubiquitous language)

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DDD v3 — bounded contexts, aggregates, value objects, domain events, Ubiquitous Language, strategic design

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Brand-narrative single source of truth (Busabase App-in-Skill) built on the TALE discipline — Trace / Architect / Land / Evaluate. The agent drafts positioning, the message house of value pillars, the story bank, evidence-backed proof points, and vocabulary/tone guardrails; the human curates which drafts become the CANONICAL narrative; a drift monitor flags off-brand usage across channels. Use when the user invokes $kelly-brand or /kelly-brand, mentions brand narrative, brand messaging, positioning, message house, value pillars, story bank, proof points, tone/vocabulary guardrails, narrative quality (NQS), brand drift, or wants a single source of truth for what the brand says.

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。

Busabase-backed, read-only App-in-Skill portfolio dashboard that aggregates Webull brokerage holdings (accounts, positions, cash/margin, market value, unrealized P/L, day change, buying power). Use when the user invokes $kelly-invest-webull or /kelly-invest-webull, wants to review their Webull portfolio, holdings, positions, accounts (cash/margin), asset allocation, market value, unrealized P/L, day change, cash, or buying power. Read-only aggregation only — it never places, modifies, or cancels orders and never moves money.

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Execute a single deterministic Python script to compute WACC, DCF assumptions, projected free cash flows, enterprise value, and intrinsic value per share. Updates the metadata markdown.

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 QC, corrects signal drift, removes batch effects, filters features, normalizes samples, and imputes missing values for untargeted LC-MS/GC-MS metabolomics, framing each step as a measurement model that can create or erase biological signal. Use when processing a peak/feature table before statistical analysis, choosing a drift-correction or sample-normalization method, deciding QC RSD vs D-ratio filtering, or handling left-censored missing values. The feature table is produced by metabolomics/xcms-preprocessing or metabolomics/msdial-preprocessing; transformation/scaling for modeling defers to metabolomics/statistical-analysis; cross-study design issues link to experimental-design/batch-design.

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。

Windows アプリ開発 (Windows App SDK / WinRT) のファイル・設定・データ保存リファレンス。 Windows.Storage の StorageFile, StorageFolder, IStorageItem, FileIO, PathIO, CachedFileManager, DataReader, DataWriter。ApplicationData, ApplicationDataContainer, ApplicationDataCompositeValue によるローカル・ローミング設定。 FileOpenPicker, FileSavePicker, FolderPicker, StorageApplicationPermissions, KnownFolders によるファイルアクセスと権限。JsonObject, JsonArray, XmlDocument, SQLite, EF Core によるシリアライズと永続化。

Windows アプリ開発 (WinUI 3 / XAML) の UI 基盤リファレンス。 レイアウトパネル Grid, StackPanel, Canvas, RelativePanel, SplitView, ScrollViewer、 XAML マークアップ x:Bind, x:Name, x:Class, StaticResource, ThemeResource、 添付プロパティ, 依存関係プロパティ、 スタイル・テーマ Style, ControlTemplate, DataTemplate, VisualStateManager, ResourceDictionary, Acrylic, Mica, SystemBackdrop、 データバインディング Binding, INotifyPropertyChanged, ObservableCollection, IValueConverter, DataContext, MVVM、 アニメーション Storyboard, DoubleAnimation, EasingFunction, ThemeTransition, ConnectedAnimation, ImplicitAnimation。

mssql (node-mssql, Node.js 向け Microsoft SQL Server クライアント) の API リファレンス。 tedious / msnodesqlv8 ドライバー、SQL Server / T-SQL / TDS 接続、ConnectionPool、 `sql.query` タグ付きテンプレート、bulk insert、Table-Valued Parameter (TVP)、 prepared statement、isolation level、Diagnostics Channel、Azure AD 認証、CLI。 Drizzle ORM 経由の SQL Server 利用 (drizzle-orm/mssql-core) は別スキル drizzle が対象。

Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.

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 post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

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, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.

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 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.

Generates DDD Value Objects for PHP 8.5. Creates immutable, self-validating objects with equality comparison. Includes unit tests.

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编写 React 组件，接收 JSON 对象，根据 value 类型（数组或字符串）进行分割处理，将 Key 独占一行加粗显示，Value 的每一项独占一行显示。

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Build institutional-quality DCF valuation models in Excel — revenue projections, FCF build, WACC, terminal value, Bear/Base/Bull scenarios, 5x5 sensitivity tables. Pairs with excel-author. Use for intrinsic-value equity analysis.

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[BETA] AEM Cloud Service expert skill — migrate javax.inject.@Inject fields in Sling Model (@Model) classes to injector-specific annotations (@ValueMapValue / @OSGiService / @SlingObject). Self-discoverable (scan for @Model classes with field-level @Inject); the replacement is chosen deterministically from each field's declared type. Use for "fix @Inject in HeroModel.java", "modernize my Sling Models", or when scanning an AEM project for @Inject misuse. Detailed decision table, companion-annotation handling, import management, and file-level skip policy are in recipe.md. This skill is in beta. Verify all outputs before applying them to production projects.

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。