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).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-data-manager-for-agri
This skill provides expert guidance for Azure Data Manager for Agriculture. Covers limits & quotas, security, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.
> IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., security.md), use read_file on the linked reference file
> IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|----------|-------|-------------|
| Limits & Quotas | L32-L36 | Guidance on API throttling behavior and limits in Azure Data Manager for Agriculture, plus strategies to plan capacity, avoid rate-limit errors, and manage high-volume workloads. |
| Security | L37-L42 | Managing secure BYOL credential storage and configuring Azure Private Link private endpoints for Azure Data Manager for Agriculture services. |
| Configuration | L43-L49 | Configuring diagnostics and Event Grid for Data Manager for Agriculture, including enabling logs, choosing event schemas, and understanding sample event payloads. |
| Integrations & Coding Patterns | L50-L64 | Integrating external ag data sources (farm activities, sensors, weather, satellite imagery, ISVs), configuring ingestion jobs/IoT, and using AI/copilot and nutrient APIs with Azure Data Manager for Agriculture |
| Topic | URL |
|-------|-----|
| Plan and manage API throttling limits for Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-understanding-throttling |
| Topic | URL |
|-------|-----|
| Store and manage BYOL credentials securely in Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-byol-and-credentials |
| Create private endpoints for Azure Data Manager for Agriculture with Azure Private Link | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-set-up-private-links |
| Topic | URL |
|-------|-----|
| Enable and configure diagnostic logging for Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-set-up-audit-logs |
| Configure Azure Event Grid event schemas for Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-use-events |
| Review sample Azure Event Grid events for Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/sample-events |
| Topic | URL |
|-------|-----|
| Integrate and ingest farm activities data into Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-farm-operations-data |
| Configure Sentinel Hub satellite imagery ingestion for Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-ingest-satellite-imagery |
| Ingest sensor telemetry into Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-ingest-sensor-data |
| Integrate weather data providers with Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-ingest-weather-data |
| Use generative AI and copilot templates with Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/concepts-llm-apis |
| Configure farm activities ingestion jobs in Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-ingest-and-egress-farm-operations-data |
| Integrate Azure Data Manager for Agriculture with farm activities data providers | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-integrate-with-farm-ops-data-provider |
| Install and use ISV solutions with Azure Data Manager for Agriculture APIs | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-set-up-isv-solution |
| Push and consume sensor data as provider and customer in Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-set-up-sensor-as-customer-and-partner |
| Set up sensors as a customer in Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-set-up-sensors-customer |
| Onboard sensor partners and configure IoT Hub ingestion for Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-set-up-sensors-partner |
| Use plant tissue nutrient APIs in Azure Data Manager for Agriculture | https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-use-nutrient-apis |
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take microsoftdocs/azure-data-manager-for-agri from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.