14 skills · sorted by relevance
Prepare a local development environment for the Data Manager API with authentication and library installation guidance. It covers five programming languages and companion utilities for formatting, hashing, and encrypting user identifiers before ingestion.
Helps developers send conversion and event data to Google Ads, Google Analytics, and Floodlight through the Data Manager API. It covers destination setup, data formatting, validation, migration from other APIs, and checking processing results.
Guides developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the API. Don't use for implementing audience or event ingestion logic (use the data-manager-api-audience-ingestion or data-manager-api-event-ingestion skills instead).
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Guides implementation of audience uploads, individual removals, and full replacements through the Data Manager API. It covers formatting and hashing identifiers, validating requests, and checking processing results for Customer Match and supported device ID audiences.
Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).
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Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).
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Use this skill when configuring Data Manager in CRM Analytics: enabling objects for sync, scheduling data sync runs, setting up remote connections to external databases, monitoring sync status and error logs, or troubleshooting connected object issues. Trigger keywords: data sync, connected objects, Data Manager, sync schedule, remote connection, Snowflake connector, sync error, incremental sync, CRM Analytics data pipeline. NOT for pushing external data in programmatically via the External Data API — use data/analytics-external-data. NOT for authoring dataflow nodes — use admin/analytics-dataflow-development.
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Expert knowledge for Azure Health Data Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using FHIR/DICOM APIs, bulk import/export, de-identification, events, or Synapse/Data Lake integrations, and other Azure Health Data Services related development tasks. Not for Azure Health Bot (use azure-health-bot), Azure Data Manager for Agriculture (use azure-data-manager-for-agri), Azure Energy Data Services (use azure-energy-data-services).
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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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Expert knowledge for Azure Energy Data Services development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADME metrics/partitions, choosing tiers, securing auth/ACLs/legal tags, or integrating ACZ/DDMS with Databricks/Fabric, and other Azure Energy Data Services related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Data Manager for Agriculture (use azure-data-manager-for-agri).
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Extract, clean, and organize legacy construction data from archives. Migrate historical project data, cost records, and schedules into modern formats.
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Think and work like an expert Clinical Data Manager. Use when a task calls for Clinical Data Manager judgment. Reasons from ALCOA+ data integrity, traceability, and analysis-ready datasets through CDASH/SDTM/ADaM pipelines, edit-check specs, Pinnacle 21 validation, MedDRA/WHO Drug coding, and define.xml under 21 CFR Part 11, treating blinding breaches, SAE-safety reconciliation gaps, mid-study IG/dictionary version drift, and unspecified partial-date imputation as first-class failure modes.
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Use when a task needs the judgment of a Clinical Data Manager — designing a CRF/eCRF and edit-check specification, writing or triaging a data query, planning database lock readiness, reconciling external data (lab, ePRO, IRT) against the clinical database, or reviewing a data management plan for a trial.
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Use when a task needs the judgment of a biomedical/bioengineering engineer — running a design control phase (inputs, outputs, verification, validation) for a medical device, scoring a Design FMEA and deciding whether a failure mode needs mitigation, planning a human factors/usability validation study, building a design traceability matrix, or writing a design verification or risk-mitigation report. Distinct from a regulatory-affairs-specialist (owns the submission/clearance process, not the engineering itself) and from a clinical-data-manager/biostatistician (trial data and analysis, not device design).
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