Azure Immersive Reader Agent Skill

Expert knowledge for Azure AI Immersive Reader development including best practices, limits & quotas, security, configuration, and integrations & coding patterns. Use when tuning read-aloud/translation, storing user prefs, Entra auth setup, JS SDK integration, or language support, and other Azure AI Immersive Reader related development tasks. Not for Azure AI Language (use azure-language-service), Azure AI Speech (use azure-speech), Azure Translator (use azure-translator), Azure AI services (use microsoft-foundry-tools).

1k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

681

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-immersive-reader

The instruction itself

8 sections, as written by the author

Azure AI Immersive Reader Skill

This skill provides expert guidance for Azure AI Immersive Reader. Covers best practices, limits & quotas, security, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.

How to Use This Skill

> 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:

Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

| Category | Lines | Description |

|----------|-------|-------------|

| Best Practices | L33-L37 | Guidance on improving Immersive Reader performance by caching authentication tokens, including token reuse patterns and reducing auth overhead. |

| Limits & Quotas | L38-L42 | Supported languages and feature availability for Immersive Reader (e.g., which languages work with read-aloud, translation, and other capabilities). |

| Security | L43-L49 | Configuring Immersive Reader security: creating the resource with Entra auth, managing Entra role assignments, and setting cookie policy and user consent. |

| Configuration | L50-L56 | Configuring Immersive Reader behavior: read-aloud voice/speed, translation languages and behavior, and storing/managing per-user reading and language preferences. |

| Integrations & Coding Patterns | L57-L66 | Implementing Immersive Reader in web/iOS apps: launch flows, JS SDK usage, HTML/MathML prep, custom buttons, multi-resource setups, and Vision Read integration. |

Best Practices

| Topic | URL |

|-------|-----|

| Cache Immersive Reader auth tokens for performance | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-cache-token |

Limits & Quotas

| Topic | URL |

|-------|-----|

| Check supported languages for Immersive Reader features | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/language-support |

Security

| Topic | URL |

|-------|-----|

| Create Immersive Reader resource and configure Entra auth | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-create-immersive-reader |

| Configure Immersive Reader cookie policy and consent | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to/set-cookie-policy |

| Update Immersive Reader Entra role assignments for security | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/security-how-to-update-role-assignment |

Configuration

| Topic | URL |

|-------|-----|

| Configure Immersive Reader Read Aloud options | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-configure-read-aloud |

| Configure translation settings in Immersive Reader | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-configure-translation |

| Store and manage Immersive Reader user preferences | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-store-user-preferences |

Integrations & Coding Patterns

| Topic | URL |

|-------|-----|

| Customize the Immersive Reader launch button | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-customize-launch-button |

| Launch Azure Immersive Reader from application code | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-launch-immersive-reader |

| Use multiple Immersive Reader resources in one app | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-multiple-resources |

| Prepare HTML content for Immersive Reader integration | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to-prepare-html |

| Render MathML expressions in Immersive Reader | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/how-to/display-math |

| Use the Immersive Reader JavaScript SDK API | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/reference |

| Build iOS app integrating Vision Read and Immersive Reader | https://learn.microsoft.com/en-us/azure/ai-services/immersive-reader/tutorial-ios-picture-immersive-reader |

Other skills for the same job

different authors, same section of the catalogue

Azure Kubernetes Automatic Readiness

by microsoft

vendor ×3

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.

17k tokens

How to use it

Copy the folder

Take microsoftdocs/azure-immersive-reader from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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.