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Expert knowledge for Azure Data Manager for Agriculture development including limits & quotas, security, configuration, and integrations & coding patterns. Use when setting up BYOL creds/Private Link, ag data ingestion/IoT, AI/nutrient APIs, throttling, or Event Grid logs, and other Azure Data Manager for Agriculture related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Data Factory (use azure-data-factory), Azure Synapse Analytics (use azure-synapse-analytics), Azure Databricks (use azure-databricks).

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Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks.

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Guides DPIA for health and medical data processing covering Art. 9(2)(h)-(j) exemptions, HIPAA crosswalk for transatlantic operations, clinical trial data protection under EU CTR 536/2014, and genetic data specifics under Art. 9(1). Activate for healthcare systems, clinical research, health apps, or medical device data. Keywords: health data, DPIA, Art. 9, clinical trial, genetic data, HIPAA, medical records, special category.

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Builds comprehensive data inventory per GDPR Art. 30 Records of Processing Activities. Covers system-by-system discovery, data flow diagramming, third-party identification, and legal basis per category. Keywords: data inventory, data mapping, Art 30, RoPA, data flow, processing activities.

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Validate database integrity, test migrations forward and backward, verify schema constraints, manage seed data, detect migration drift, and identify query performance issues. Covers PostgreSQL, MySQL, MongoDB with Prisma, TypeORM, Drizzle, and SQLAlchemy, plus Testcontainers test databases. Use when: "database test," "migration test," "migration rollback," "rollback test," "data integrity," "SQL test," "schema validation," "seed data," "query performance," "Testcontainers." Not for: synthetic data generation/masking at scale — use test-data-management; Docker/IaC test-environment provisioning — use test-environments; SQL injection — use security-testing. Related: test-data-management, test-environments, security-testing, ci-cd-integration.

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Complete DataForSEO API integration for SEO data and analysis. Use when the user asks for keyword research, search volume, SERP analysis, backlink audits, competitor analysis, rank tracking, domain authority, technical SEO audits, content monitoring, Google Trends, or any SEO-related data queries. Covers all DataForSEO APIs including SERP, Keywords Data, DataForSEO Labs, Backlinks, OnPage, Domain Analytics, Content Analysis, Business Data, Merchant, App Data, and AI Optimization APIs. Outputs CSV files.

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Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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Use when designing deployable Salesforce configuration with Custom Metadata Types, especially when choosing between CMTs, Custom Settings, and Custom Objects, protecting packaged defaults, or exposing config to Apex, Flow, and formulas. Triggers: 'custom metadata vs custom settings', 'deployable config', 'protected custom metadata', 'feature flags in Salesforce'. NOT for hierarchical Custom Settings resolution, getInstance/getValues, or their SOQL cost — use admin/custom-metadata-types-and-settings. NOT for high-churn transactional or user-managed business records — use admin/object-creation-and-design. NOT for secrets — use integration/named-credentials-setup. More trigger keywords: __mdt, CustomMetadata .md file, customMetadata folder, getInstance, getAll, xsi:type, visibility PackageProtected, MetadataRelationship, EntityDefinition field, $CustomMetadata.

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Use when enabling, configuring, or monitoring Change Data Capture (CDC) entity selection, channel enrichment, and delivery usage limits from an admin perspective. Covers the PlatformEventChannel and PlatformEventChannelMember metadata, the standard ChangeEvents channel, custom __chn data channels, enrichedFields, filterExpression, destructive deselection, and PlatformEventUsageMetric / EventBusSubscriber monitoring. Trigger keywords: change data capture, CDC, entity selection, change event, platform event channel, channel member, enrichment, event delivery allocation. NOT for writing an Apex change-event trigger — use apex/change-data-capture-apex. NOT for subscribing an external system over Pub/Sub or CometD — use integration/change-data-capture-integration.

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iOS Core Data architect for persistent storage, CloudKit sync, schema migrations, and SwiftData migration. Activate on: Core Data, NSManagedObject, CloudKit sync, Core Data migration, NSFetchedResultsController, NSPersistentContainer, SwiftData migration path. NOT for: SwiftUI state management (use swiftui-data-flow-expert), server databases (use data-pipeline-engineer), SQLite direct (use mobile-offline-sync-architect).

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Prepare high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-engineer).

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Expert in turning data visualizations into compelling video and animation content for social media and marketing. Activate on: data commercial, animated chart, data storytelling video, chart animation, Remotion data video, Motion Canvas, Flourish animation, D3 animation, data viz social media, dashboard recording, data narrative video. NOT for: static data visualization (use data-viz-2025), general video editing (use video-processing-editing), full video production pipeline (use ai-video-production-master).

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Insurance-industry App-in-Skill for read-only data governance, backed by an operator-provisioned Busabase workspace (one Drive node for the file drive plus four Bases for QA pairs, featured information, insurer notices, and user feedback) and trusted export/restore/PDF-text-backfill scripts. Use when the user invokes $kelly-insure-data or /kelly-insure-data, wants an insurance data workspace with UI, needs to review insurance files, metadata completeness, QA pairs, featured information, insurer notices, or user feedback, wants to back up or restore a Kelly Insure Data Busabase workspace from local PDFs, or wants Busabase Drive/Base data surfaced for data quality review and ongoing data governance.

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Prepare high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-engineer).

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Expert in turning data visualizations into compelling video and animation content for social media and marketing. Activate on: data commercial, animated chart, data storytelling video, chart animation, Remotion data video, Motion Canvas, Flourish animation, D3 animation, data viz social media, dashboard recording, data narrative video. NOT for: static data visualization (use data-viz-2025), general video editing (use video-processing-editing), full video production pipeline (use ai-video-production-master).

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用于 Nuxt 4 应用开发、审查和性能改善，防止服务端与浏览器显示不一致，并整理数据获取、各页面的渲染与缓存规则及延迟加载方式。

• 修复服务端与浏览器显示不一致
• 审查页面数据获取方式
• 确定各页面的渲染与缓存规则

帮助医疗应用分类患者、员工及财务敏感信息，设计按医疗机构划分的行级访问控制和审计记录，并检查日志、网址及浏览器存储中的信息泄露。

• 检查处理患者记录的代码
• 设计医疗机构间的访问控制
• 记录敏感信息的查看与修改

连接运行中的Jupyter，保留变量和已加载数据，反复试验Python代码、检查对象及编辑单元格，并可重启后从上到下验证整个笔记本。

• 保留变量并逐步探索数据
• 检查DataFrame和Python对象
• 试验并修改API调用或复杂代码

Organize single-cell measurements with cell and gene metadata, read and write h5ad or Zarr files, and prepare subsets or combined datasets. Includes guidance on handling large annotated matrices without loading all measurement values into memory.

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• Read and write h5ad or Zarr datasets
• Combine experimental batches with source labels
• Select cells or genes using metadata

Plan GDPR data handling for systems processing EU personal data. Review consent, requests from people to access or delete their data, collection limits, retention, encryption, and access controls as part of system design and compliance reviews.

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• Designing systems that process EU personal data
• Reviewing consent forms and purpose-specific choices
• Organizing responses to data access and deletion requests

Turn a business use case into a Dataverse solution using Python. Get table and relationship designs, implementation code, usage instructions, and recommendations for error recovery, logging, monitoring, and performance based on the expected workload.

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• Designing customer and document management solutions
• Building data migration or scheduled synchronization jobs
• Implementing order processing and approval workflows

Generate concise Python examples for working with Microsoft Dataverse. Cover SDK installation, browser-based authentication, creating, reading, updating, and deleting records, plus bulk operations and retrieving results in pages using official example patterns.

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• Set up the SDK and browser-based authentication
• Create, read, update, and delete individual records
• Create or update records in bulk

Turn application requirements into an Azure Cosmos DB NoSQL data model. Gather read and write patterns, workload volumes, and relationships, then document container structures, partition keys for distributing data, indexes, and design trade-offs in two Markdown files.

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• Designing a data model for a new application
• Choosing how to group and partition related data
• Reviewing database costs for high-volume workloads

Retrieve price and trading volume data for US, Hong Kong, and Canadian stocks, ETFs, and indices through Yahoo Finance. Also gather company profiles, financial statements, dividends, and ownership data for market research and historical strategy testing.

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• Collect historical prices across several stock markets
• Review company financial statements and ownership
• Check dividend and stock split histories