“data-driven”的搜索结果

Rank content angles by engagement data, competition level, and platform fit. Data-driven angle selection instead of guesswork. Use this skill when the user has a keyword or product and needs to decide WHAT to create, which angle to take, which format to use, or which platform to target. Triggers on: "what angle should I use", "rank content ideas for [keyword]", "best angle for [product]", "which content idea will perform best", "help me pick an angle", "what should I write about", "content angle for [topic]", "rank my content ideas", "which approach will get the most views", "data-driven content planning", "angle ranker", "content scoring", "which hook should I use", "compare these content ideas", "prioritize my content angles", "what video should I make".

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Data-driven growth v3 — experimentation, metrics, dashboards, correlation analysis

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Expert en croissance data-driven (experimentation, metrics, dashboards, correlation analysis)

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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.

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Interpret app metrics and make data-driven decisions. Covers DAU/MAU, retention, LTV, ARPU, App Store Connect analytics, AARRR funnel analysis, cohort analysis, and diagnostic decision trees. Use when user wants to understand their metrics, diagnose problems, or build a data-driven growth plan.

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Provides parameterized testing patterns with JUnit 5, generates data-driven unit tests using @ParameterizedTest, @ValueSource, @CsvSource, @MethodSource. Creates tests that run the same logic with multiple input values. Use when writing data-driven Java tests, multiple test cases from single method, or boundary value analysis.

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🇺🇸 KOL Outreach & Influencer Marketing Playbook — Complete SOP from discovery to ROI tracking. Battle-tested with 200+ KOL campaigns at AFFiNE (60k stars). Includes pricing benchmarks, email templates, content packages, platform algorithm guides, and data-driven evaluation frameworks. 🇨🇳 KOL 外联与红人营销实战手册 — 从发现筛选到 ROI 追踪的完整 SOP。基于 AFFiNE（60k stars）200+ 次 KOL 合作实战验证。包含报价基准、邮件模板、内容包模板、各平台算法指南、数据评估体系。 🇯🇵 KOLアウトリーチ＆インフルエンサーマーケティング実践ガイド — 発見からROI追跡までの完全SOP。AFFiNE（60k stars）での200回以上のKOLキャンペーン実績。価格ベンチマーク、メールテンプレート、コンテンツパッケージ、プラットフォームアルゴリズムガイド。 🇰🇷 KOL 아웃리치 & 인플루언서 마케팅 플레이북 — 발굴부터 ROI 추적까지 완전한 SOP. AFFiNE(60k stars) 200+ KOL 캠페인 실전 검증. 가격 벤치마크, 이메일 템플릿, 콘텐츠 패키지, 플랫폼 알고리즘 가이드. Triggers: "KOL outreach" | "influencer marketing" | "KOL campaign" | "influencer outreach" | "creator partnership" | "KOL strategy" | "red人" | "红人营销" | "KOL合作" | "达人合作" | "influencer pricing" | "KOL ROI" | "content creator outreach" | "KOL筛选"

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Unity data-driven design architecture. ScriptableObject config hierarchies, JSON data pipelines, designer handoff workflows, data versioning and migration, Inspector attributes for self-documenting configs. DECISION format: WHEN/DECISION/SCAFFOLD/GOTCHA. Based on Unity 6.3 LTS.

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Programmatic SEO planning and analysis for pages generated at scale from data sources. Covers template engines, URL patterns, internal linking automation, thin content safeguards, and index bloat prevention. Use when user says "programmatic SEO", "pages at scale", "dynamic pages", "template pages", "generated pages", "data-driven SEO", "pSEO", "template engine", "data-driven pages", "index bloat", or "thin content at scale".

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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.

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Creates marketing analytics reports, KPI dashboards, ROI calculations, and performance summaries for SME marketing teams. Handles weekly/monthly reporting, campaign analysis, content performance reviews, and data-driven recommendations. Use when user asks about marketing metrics, reporting, KPIs, dashboards, ROI analysis, performance review, or data-driven marketing decisions.

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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.

中文简介正在准备中。当前显示原文说明。

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.

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Complete guide for TUnit advanced applications. Use when using TUnit for data-driven testing, dependency injection, or integration testing. Covers MethodDataSource, ClassDataSource, Matrix Tests, Properties filtering. Includes Retry/Timeout control, WebApplicationFactory integration, Testcontainers multi-service orchestration. Keywords: TUnit advanced, TUnit advanced, MethodDataSource, ClassDataSource, Matrix Tests, MatrixDataSource, MicrosoftDependencyInjectionDataSource, Property, Retry, Timeout, data-driven testing, test filtering, WebApplicationFactory TUnit, multi-container orchestration

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Create HTML presentations for marketing, pitches, and data-driven explanations. Use Chart.js graphs, reusable design settings, responsive layouts, and writing formulas to shape slide content and choose layouts suited to the presentation's purpose.

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• Creating marketing presentation slides
• Building a pitch deck
• Explaining data with Chart.js graphs

Design reusable pose data for 2D characters, covering emotions, actions, mouth shapes, and repeated movements. Organize changes to individual body parts, pose durations, and transitions so animation sequences have clearly defined stages.

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• Planning a reusable set of emotional expressions
• Designing walking and other repeated movements
• Organizing mouth shapes for a character

Build reusable data packages for local 2D character animation. Define separate body parts, rotation points, layer order, movement limits, and views so a shared renderer can animate each character using its own rig data.

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• Prepare a 2D character for local animation
• Define joint rotation points and movement limits
• Organize mouths, eyes, and props as separate parts

Build custom interactive charts, network diagrams, and maps with d3.js. Guides data-driven drawing, tooltips, zooming, animation, responsive sizing, and accessibility, with examples that work in plain JavaScript or frameworks such as React, Vue, and Svelte.

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• Building charts with custom layouts and styling
• Creating network diagrams and geographic visualizations
• Adding tooltips, zooming, and animated transitions

Plan large sets of search-focused pages using templates and data. The skill helps assess keyword demand, design useful page variations, organize internal links, choose a publishing platform, and check quality before launch.

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• Planning service pages for different locations
• Designing comparison page templates
• Building a directory from existing data

Migrate existing PowerShell Pester tests through major versions from v3 to v6. The skill guides assertion updates, setup restructuring, mock changes, and execution configuration, using before-and-after test results to investigate failures while preserving what each test checks.

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• Migrating Pester tests one major version at a time
• Fixing tests broken by a Pester upgrade
• Updating legacy Should and Invoke-Pester syntax

Write focused Java unit tests with JUnit 5, including tests that repeat checks across different inputs. Covers clear test structure, exception checks, mock objects that replace dependencies, and ways to organize test suites.

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• Writing a unit test for a Java method
• Checking the same behavior with multiple input values
• Testing exceptions and related assertions

Write focused C# unit tests with XUnit, including tests that run against multiple input datasets. Apply consistent naming, setup, assertions, shared fixtures, and mock dependencies to keep tests readable, independent, and organized.

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• Set up an XUnit test project for C#
• Test multiple input cases with Theory and data attributes
• Check exceptions and isolate dependencies with mocks

Write and improve C# unit tests with MSTest 3.x/4.x. Covers assertions that check expected results, tests with multiple input sets, asynchronous setup, cleanup, and test organization, with guidance on APIs that differ between versions.

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• Create a C# unit test project
• Test multiple input sets with DataRow or DynamicData
• Update exception checks to modern assertion APIs

Write C# unit tests with NUnit using clear naming, focused assertions, and independent test cases. Covers project setup, testing with multiple input values, exception checks, and replacing dependencies with mocks to test components in isolation.

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• Setting up an NUnit test project
• Testing the same behavior with multiple inputs
• Checking exceptions and collection contents