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Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

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dbt Core/Cloud data transformations, testing, documentation, and CI/CD. Activate on: dbt, data transformation, analytics engineering, ref, source, staging model, mart, dbt test. NOT for: orchestration/scheduling (use airflow-dag-orchestrator), data warehouse tuning (use data-warehouse-optimizer).

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Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.

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Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering.

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Helps design ClickHouse tables, write analytical queries, and improve slow queries. Covers loading data in batches, preparing reusable summaries, and monitoring performance for large datasets, real-time dashboards, and time-series analysis.

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• Designing tables for large-scale analytics
• Improving slow aggregation queries
• Loading large datasets in batches

将多个社交平台的指标汇总为单个HTML分析仪表板，支持图表详情、所选时段比较和明暗主题切换，并按现有设计指南统一配色、字体与组件。

• 集中查看多个社交平台的指标
• 比较图表中选定的时段
• 查看图表数据点及相关分析

收集GitHub公开仓库的星标、复刻、贡献者、议题、拉取请求和近期活动，生成可在一屏查看的HTML仪表板，也可附带支持更新和核查数据来源的文件。

• 集中查看仓库活动
• 编写开源项目健康报告
• 查看主要贡献者及近期议题和拉取请求

Review forms, API requests, and browser storage to find personal data that no active feature needs. Identify unnecessary collection, suggest removal or anonymisation, and check analytics and logs for exposed personal identifiers and missing retention periods.

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• Reviewing personal data collected by forms
• Finding personal identifiers in analytics and logs
• Reviewing browser storage and retention periods

Set up and troubleshoot website conversion tracking for leads and purchases. Check that events represent confirmed success, prevent duplicate counts, and verify that conversions actually reach advertising or analytics platforms.

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• Set up tracking for confirmed form submissions
• Investigate missing or duplicate conversions
• Check differences between GA4 and Google Ads

Assess how marketing channels contribute to conversions and revenue. Compare attribution models, which assign credit to customer interactions, reconcile conflicting reports, and design first-party tracking that connects browsing history to bookings or purchases.

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• Reconciling conversion counts across advertising tools, analytics, and CRM
• Comparing first-touch and last-touch credit
• Designing surveys to capture word-of-mouth discovery

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

Analyze endpoint, cloud storage, and email logs for signs of insider data theft. Use pandas to compare upload volumes with normal user behavior and examine data loss prevention alerts, unusual file access, and activity outside working hours.

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• Investigating suspected insider data theft
• Finding users with unusually large uploads
• Reviewing file access outside working hours

Build or tune a monitoring pipeline that learns normal user behavior from activity logs. Use Elasticsearch or OpenSearch to score unusual activity, compare colleagues in similar roles, and combine warning signs into insider threat alerts.

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• Building continuous monitoring for insider threats
• Scoring unusual logins and large downloads
• Comparing behavior across similar job roles

Analyze authentication logs to spot suspicious sign-ins, password attacks, and possible account compromise. Statistical baselines and machine learning help compare login activity with normal user behavior, while example SIEM queries support security investigations.

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• Investigating suspicious sign-in alerts
• Detecting geographically inconsistent logins
• Finding brute force and password spraying

Analyze access logs from AWS S3, GCS, and Azure Blob Storage to spot unusual downloads, unfamiliar IP addresses, and request spikes. Compare activity with normal patterns and prioritize findings for suspected data theft investigations.

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• Investigating suspected data theft from cloud storage
• Finding bulk downloads outside normal working hours
• Checking unfamiliar IP addresses and sudden request spikes

Investigate suspicious Azure activity by querying administrative and sign-in logs. Create KQL queries, Azure's log search language, to examine role assignments, resource changes, unusual access, and other signals for cloud security monitoring.

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• Investigate suspicious administrative activity in Azure
• Check newly added administrator roles
• Review resource and network security rule changes

Plan A/B tests that compare page or product changes, with clear hypotheses, sample sizes, success metrics, and traffic allocation. Get a structured test plan and guidance for interpreting results and deciding what to try next.

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• Comparing signup button copy
• Planning a pricing page experiment
• Estimating sample size and test duration

Coordinate project delivery by routing requests to eight specialist skills or running a verified delivery workflow. Use live Jira data for progress analysis and completion forecasts, with recorded evidence and checks before tasks are closed.

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• Analyze sprint progress and forecast completion ranges
• Produce project health reports from live Jira data
• Route Jira permission and configuration reviews

Find the right specialist skill for a marketing question, coordinate content, SEO, advertising, and analytics tasks, or review gaps across current activities. Get recommended next steps or a campaign plan with a sequence and timeline.

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• Choosing a marketing skill for a specific question
• Coordinating a product launch campaign
• Reviewing gaps and priorities across marketing activities

Plan A/B tests that compare page variations, from headlines to pricing layouts. Define a hypothesis, choose success metrics, calculate sample size and duration, and prepare launch checks and results reports to support decisions.

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• Comparing landing page headlines
• Testing signup button changes
• Planning pricing page experiments

Plan a game season or limited-time event across content, story, rewards, pricing, measurement, and player communication. Coordinate role-based agents to produce a season design, analytics plan, and communication calendar for production.

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• Plan a game season or limited-time event
• Design reward tracks and seasonal currency pricing
• Define success metrics and A/B tests

Gather usage, performance, and error data from configured sources for a chosen time window. Produce a compact, saved product report with followup actions, and show its headlines in chat to support regular reviews of product activity.

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• Reviewing product usage and errors over the past 24 hours
• Checking product activity during a launch window
• Saving weekly reports to track changes over time

Develop time-series and event-data solutions with TimescaleDB, an extension for PostgreSQL. The skill provides organized references for installation, time-based tables, ongoing aggregate calculations, compression, and performance troubleshooting.

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• Learn how to install and use TimescaleDB
• Design tables for time-series and event data
• Implement time-bucket and continuous aggregates

Use Google's APIs to review search performance, page speed, indexing status, and organic traffic. Combine real visitor measurements with search and analytics data to identify SEO issues and create reports.

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• Reviewing search clicks, impressions, and rankings
• Tracking page experience metrics over 25 weeks
• Checking whether Google has indexed specific URLs