Expert knowledge for Azure Confidential Ledger development including troubleshooting, decision making, security, integrations & coding patterns, and deployment. Use when configuring ACL auth/attestation, integrating with Blob/Cosmos, using MST payloads, or deploying via ARM/Terraform, and other Azure Confidential Ledger related development tasks. Not for Azure Confidential Computing (use azure-confidential-computing), Azure Key Vault (use azure-key-vault), Azure Dedicated HSM (use azure-dedicated-hsm), Azure Payment Hsm (use azure-payment-hsm).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-confidential-ledger
This skill provides expert guidance for Azure Confidential Ledger. Covers troubleshooting, decision making, security, integrations & coding patterns, and deployment. 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 |
|----------|-------|-------------|
| Troubleshooting | L33-L38 | Diagnosing and resolving Microsoft Signing Transparency (MST) ledger verification issues, plus steps to verify ledger integrity and inspect individual ledger entries. |
| Decision Making | L39-L44 | Choosing between ACL Explorer tools for viewing/querying ledgers, and guidance on migrating applications and data from Managed CCF to Azure Confidential Ledger |
| Security | L45-L57 | Auth, attestation, identity, and access control for Confidential Ledger: Entra ID setup, app registration, RBAC, cert-based users, client certs, node quote verification, and deployment security. |
| Integrations & Coding Patterns | L58-L67 | Patterns and examples for integrating ACL with Blob Storage, Power Automate, Cosmos DB, organizing ledger data, designing MST payloads/claims, and writing JavaScript user-defined functions. |
| Deployment | L68-L72 | How to deploy and provision Azure Confidential Ledger instances using ARM templates or Terraform, including required parameters and configuration steps. |
| Topic | URL |
|-------|-----|
| Troubleshoot Microsoft’s Signing Transparency Ledger verification issues | https://learn.microsoft.com/en-us/azure/confidential-ledger/microsoft-signing-transparency-troubleshoot |
| Verify MST ledger integrity and inspect entries | https://learn.microsoft.com/en-us/azure/confidential-ledger/microsoft-signing-transparency-verify-signatures |
| Topic | URL |
|-------|-----|
| Choose between Azure Confidential Ledger Explorer tools | https://learn.microsoft.com/en-us/azure/confidential-ledger/ledger-explorer-concepts |
| Migrate from Managed CCF to Azure Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/managed-confidential-consortium-framework-migration |
| Topic | URL |
|-------|-----|
| Authenticate and attest Azure Confidential Ledger nodes securely | https://learn.microsoft.com/en-us/azure/confidential-ledger/authenticate-ledger-nodes |
| Configure Microsoft Entra authentication for Azure confidential ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/authentication-azure-ad |
| Create and configure client certificates for Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/create-client-certificate |
| Manage Entra token-based users and roles in Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/manage-azure-ad-token-based-users |
| Manage certificate-based users and roles in Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/manage-certificate-based-users |
| Register Confidential Ledger applications in Microsoft Entra ID | https://learn.microsoft.com/en-us/azure/confidential-ledger/register-application |
| Secure Azure Confidential Ledger deployments and access | https://learn.microsoft.com/en-us/azure/confidential-ledger/secure-confidential-ledger |
| Implement advanced UDFs with RBAC in Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/user-defined-endpoints |
| Verify node quotes and establish trust in Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/verify-node-quotes |
| Topic | URL |
|-------|-----|
| Integrate Blob Storage digests with Azure Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/create-blob-managed-app |
| Integrate Azure confidential ledger with Power Automate and Cosmos DB | https://learn.microsoft.com/en-us/azure/confidential-ledger/create-power-automate-workflow |
| Organize and access data in Azure confidential ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/data-organization |
| Design MST payloads, claims, and auditing workflows | https://learn.microsoft.com/en-us/azure/confidential-ledger/microsoft-signing-transparency-usage |
| Run user-defined functions in Azure Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/server-side-programming |
| Create simple JavaScript UDFs in Confidential Ledger | https://learn.microsoft.com/en-us/azure/confidential-ledger/user-defined-functions |
| Topic | URL |
|-------|-----|
| Deploy Azure Confidential Ledger via ARM template | https://learn.microsoft.com/en-us/azure/confidential-ledger/quickstart-template |
| Provision Azure Confidential Ledger using Terraform | https://learn.microsoft.com/en-us/azure/confidential-ledger/quickstart-terraform |
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-confidential-ledger 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.