Expert knowledge for Azure Microsoft Discovery development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment.
Expert knowledge for Azure Microsoft Discovery development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment.
Use when designing Discovery shared sessions, ACR tool images, REST jobs, supercomputer provisioning, or Log Analytics queries, and other Azure Microsoft Discovery related development tasks.
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Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
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Stars737
LicenseLICENSE
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Skill metadata
Parsed from SKILL.md frontmatter.
CompatibilityRequires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
More metadata
generated_at
2026-08-31
generator
docs2skills/1.0.0
Package contents
Files included with this skill beyond the listing page.
skill mdSKILL.md11,838 B
docsSUMMARY.md464 B
History
First seen on skills.sh
First recorded snapshot · 83 installs
SKILL.md
Azure Microsoft Discovery Skill
This skill provides expert guidance for Azure Microsoft Discovery. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. 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 readfile with the specified lines. For categories with file links (e.g., [security.md](security.md)), use readfile on the linked reference file
IMPORTANT for Agent: If metadata.generatedat is more than 3 months old, suggest the user pull the latest version from the repository. If mcpmicrosoftdocs tools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
Preferred: Use mcpmicrosoftdocs:microsoftdocs_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
Troubleshooting
L37-L42
Diagnosing and resolving Microsoft Discovery Engine task failures, and locating/using correlation IDs from Activity Logs to debug and trace issues.
Best Practices
L43-L49
Best practices for structuring projects and shared sessions, applying responsible AI, calibrating trust and safety patterns, and planning tool capabilities and compute for Discovery.
Decision Making
L50-L57
Guidance on selecting ACR setup, agent types, pricing/billing, and suitable AI models to design and configure Microsoft Discovery agents effectively.
Architecture & Design Patterns
L58-L62
Designing and implementing advanced shared session patterns in Discovery Engine, including multi-user session management, data sharing, and scalable architecture best practices.
Limits & Quotas
L63-L68
Planning capacity and Azure quotas for Microsoft Discovery deployments, plus required naming conventions and rules for Discovery resources.
Security
L69-L84
Security and compliance for Discovery: encryption at rest, customer-managed keys, RBAC/persona roles, managed identities, network hardening, secure supercomputer access, and audit logging.
Configuration
L85-L105
Configuring Discovery workspaces, storage, tools, supercomputers, and data handling, plus querying operational, indexing, and activity logs via Log Analytics and Kusto.
Integrations & Coding Patterns
L106-L113
Patterns and APIs for integrating tools/models into Discovery workflows, including Docker-based packaging, REST job execution, and action script implementation for action-based tools.
Deployment
L114-L119
Deploying Discovery infrastructure and tools: network-hardened stacks, Bicep-based deployments, REST provisioning of supercomputer resources, and publishing tool images to Azure Container Registry.