'xp' 검색 결과

A platform decision framework for experimentation. When to use Statsig vs PostHog vs GrowthBook vs Optimizely vs Amplitude vs Eppo vs Kameleoon. How to migrate between them. How to coordinate when multi-platform is genuinely warranted. The decisions that compound for years and the ones you can defer. Triggers on which experimentation platform, choose Statsig vs PostHog, evaluate experimentation tools, switch experimentation platform, migrate from Optimizely, consolidate experimentation tools, multi-platform experimentation, experimentation platform decision, ab test platform selection, feature flag platform vs experiment platform, warehouse-native experiments, vendor lock-in experimentation. Also triggers when a team is asking about cost, governance, or migration cost across experimentation tools, or when an evaluation is starting.

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Running experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction with CUPED, sequential testing, and the operational tradeoffs vs platforms like Statsig and Optimizely. Triggers on warehouse-native experimentation, run experiments in BigQuery, run experiments in Snowflake, dbt experiments, SQL t-test, CUPED variance reduction, exposure log, sample ratio mismatch, sequential testing, mSPRT, doubly robust estimation, build vs buy experimentation. Also triggers when the team is choosing between platform and warehouse, building warehouse-native experiment infrastructure, auditing one, or running an experiment with a custom metric the platform cannot handle.

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Expo (React Native フレームワーク, Expo SDK 58 / EAS) のリファレンス。 Expo Router (file-based routing, expo-server, data loaders, +api.ts), app.json / app.config, config plugins, Expo Modules API, expo-* SDK, Expo UI, EAS Build / Update / Submit / Workflows, eas.json, expo-updates (OTA), CNG / prebuild, Expo CLI (npx expo), development build (dev-client), expo-notifications push。

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Diagnoses bias, anomalies, and strange-looking results on a specific PostHog experiment. Covers empty / 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, and surprises after mid-run edits. Symptom-driven dispatch to the right diagnostic. TRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping, notices PostHog numbers disagreeing with their SQL, sees an A/A test showing significance, or reports surprises after mid-run edits. DO NOT TRIGGER when: creating a new experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-lifecycle).

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Kotlin과 JetBrains Exposed로 데이터베이스 조회와 추가·수정·삭제를 구현하는 패턴을 제공합니다. 연결 재사용, 구조 변경, 트랜잭션과 테스트도 다룹니다.

• 데이터베이스 조회와 수정 구현
• 데이터베이스 연결 재사용 설정
• 데이터베이스 구조 변경 관리

Plan A/B tests to compare page changes using clear hypotheses and meaningful measures. The skill helps define sample size, duration, traffic allocation, and result interpretation, and organize a continuing program of prioritized experiments.

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• Compare headlines or signup buttons
• Estimate test sample size and duration
• Interpret results and possible adverse effects

Find professionals with relevant experience and request a written or voice answer, or a short call, through Instant Expert. Use it for customer discovery and practical advice, with a free simulated test mode to try the process.

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• Gathering firsthand experience from practitioners
• Interviewing potential customers
• Requesting a short call with a named professional

Create and analyze AI model evaluation experiments in Arize using the ax CLI, a command-line tool. Collect real model outputs, export results, compare evaluation scores, and identify examples where a new model performs worse.

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• Comparing models on the same evaluation dataset
• Finding examples that perform worse after a model change
• Exporting experiment results for further analysis

Write and troubleshoot n8n expressions, the formulas that pass and transform data between workflow steps. Covers field references, webhook inputs, dates, strings, and choosing between expressions and Code nodes for data transformations.

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• Fixing expression syntax errors
• Using webhook data in downstream steps
• Formatting dates and strings

Create, update, and analyze Mixpanel dashboards using live report data. Summarize trends and relationships across metrics, adjust report layouts, and add text cards that explain findings alongside the charts.

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• Understand metrics and trends in an existing dashboard
• Build a dashboard for product health monitoring
• Rearrange reports and add missing metrics

Create and edit EAS workflow YAML files to automate builds and deployments for Expo projects. Check required settings, job dependencies, and dynamic values against the latest schema, which defines the accepted configuration.

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• Create an automated build workflow for an Expo project
• Edit EAS deployment automation
• Check workflow settings and job dependencies

Set up Tailwind CSS v4 in Expo using react-native-css and NativeWind v5. Configure styling across iOS, Android, and Web, create components that accept CSS class names, and define shared themes with platform-specific fonts and colors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add Tailwind CSS v4 to an Expo project
• Create components that accept CSS class names
• Define shared themes with platform-specific fonts and colors

Set up Tailwind CSS v4 in Expo using react-native-css and NativeWind v5. Configure styling across iOS, Android, and Web, create components that accept CSS class names, and define shared themes with platform-specific fonts and colors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add Tailwind CSS v4 to an Expo project
• Create components that accept CSS class names
• Define shared themes with platform-specific fonts and colors

Support experimental validation of designed proteins through a cloud laboratory. Prepare and optimize sequences, submit tests for binding, expression, thermal stability, or enzyme activity, track experiment progress, and retrieve results through the API.

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• Submit designed proteins for binding tests
• Request expression, thermal stability, or enzyme activity tests
• Optimize sequences for solubility before experiments

Implement structured telemetry, such as counters and events, from DOCA applications to external consumers. Guides publishing API selection, schema and source setup, build and test workflows, and debugging lifecycle errors or reports that never reach the receiver.

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• Publish packet counters and bandwidth gauges from a DOCA application
• Define event fields and initialize schemas and sources
• Investigate DOCA_ERROR_BAD_STATE during event reporting

World-class explainer video expertise combining the visual storytelling of Kurzgesagt, the simplification genius of Common Craft, and the conversion science of high-performing SaaS landing pages. Explainer videos transform complex ideas into clear, compelling stories. Great explainers don't just inform—they illuminate. They take abstract concepts and make them feel obvious. The best explainer videos understand that simplicity is the ultimate sophistication, that showing beats telling, and that the goal isn't to impress with complexity—it's to make the viewer feel smart. Use when "explainer, explainer video, how it works, product demo, onboarding video, training video, educational video, whiteboard, animated explainer, explain this, simplify, concept video, SaaS video, explainer, video, animation, educational, product, demo, onboarding, SaaS" mentioned.

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Use Nexscope (Search Intelligence Framework) data to analyze ASIN traffic source composition and exposure distribution, covering current period/previous period/newly entered/exited period comparisons. Trigger when the user mentions ASIN traffic sources, traffic structure analysis, organic traffic vs paid traffic share, exposure score breakdown, period comparison, new/exited traffic keywords, competitor traffic analysis, SP ad keyword count, brand ad exposure, Amazon's Choice exposure, editorial recommendation exposure, Top Rated exposure, video ad exposure, organic search exposure ratio, PPC traffic sources, promotional deal traffic sources, recommendation slot structure breakdown, ASIN traffic analysis, traffic sources, organic traffic share, ad traffic share, exposure analysis, traffic structure, period-over-period comparison, keyword churn, Nexscope. Even if the user does not explicitly mention "Nexscope", if their need involves analyzing an ASIN's traffic sources, exposure channel distribution, cross-period comparison, or competitor traffic structure comparison, this skill should also be triggered.

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Get started with Xpoz — set up authentication, verify your account, configure tracking, and discover available skills. Use when asked to "set up Xpoz", "connect to Xpoz", "get started with Xpoz", "what can Xpoz do", "new to Xpoz", "install Xpoz", or "my Xpoz account".

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xp-harness の skill / agent を新規作成・改修するとき、または xp-harness そのものの設計判断 (取り込む / 取り込まない / 翻訳する) を考えるときに必ず発火させる skill。xp-harness の中核思想 (最終形の理想像 = エージェント群と利用者で XP の開発チームを成す、価値で導きつつ規律装置最小注入、エンジニアとして振る舞う、ペアプロ哲学、中央集権より decentralized、outside-in 例外なし、対話と自走の境界、INVEST の取捨、共創を目指す対話) を context に inject し、新規 skill / agent の設計判断や既存 skill / agent の改修判断を、xp-harness 思想と整合させるためのもの。

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Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a relative reference ("latest", "most recent", "the one I created yesterday"), filters by status (running, draft, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.

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Maintain Remotion’s expert listings, portraits, and generated cards, then regenerate the homepage animation with transparency. The workflow covers separate Chrome and Safari video formats and checks that matching assets stay consistent across both homepage consumers.

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• Add or edit an expert listing
• Update portraits and regenerate expert cards
• Regenerate transparent homepage animations

Analyze gene-expression differences in bulk RNA-seq data using PyDESeq2. Validate count tables and experimental designs, test explicit comparisons, adjust for multiple testing, shrink effect estimates, and export statistical results with volcano and MA plots.

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• Compare gene expression between treatment and control groups
• Analyze expression differences while accounting for batch effects
• Validate count tables against sample metadata

Build and train Mixture of Experts models, which activate selected specialist networks for each input. Use DeepSpeed or HuggingFace workflows to configure routing, balance workloads, distribute experts across GPUs, and optimize inference.

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• Designing MoE models for a limited compute budget
• Implementing Mixtral-style expert routing
• Adjusting expert workloads and training stability

Search BioStudies and ArrayExpress by keywords or retrieve study information using an accession, a study’s registration identifier. Returns concise summaries and can save complete API responses to a file for further inspection.

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• Search for studies related to RNA
• Find single-cell studies in ArrayExpress
• Retrieve study details by accession