Expert knowledge for Azure AI Metrics Advisor development including decision making, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring data feeds, tuning anomaly detection, managing alerts/hooks, or calling Metrics Advisor REST/SDKs, and other Azure AI Metrics Advisor related development tasks. Not for Azure AI Anomaly Detector (use azure-anomaly-detector), Azure Monitor (use azure-monitor), Azure Stream Analytics (use azure-stream-analytics).
npx skills add https://github.com/MicrosoftDocs/Agent-Skills --skill azure-metrics-advisor
This skill provides expert guidance for Azure AI Metrics Advisor. Covers decision making, 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 |
|----------|-------|-------------|
| Decision Making | L33-L37 | Guidance on estimating, controlling, and optimizing Metrics Advisor costs and usage, including pricing factors, quotas, and cost-management best practices. |
| Limits & Quotas | L38-L42 | Service limits for Metrics Advisor: max metrics, dimensions, alerts, data ingestion rates, detection constraints, and guidance on scaling within quotas. |
| Security | L43-L48 | Configuring Metrics Advisor security: data encryption, auth options (keys, AAD), and creating/managing secure credential entities for data sources and monitoring. |
| Configuration | L49-L53 | Setting up Metrics Advisor: configuring alert hooks (email/webhook), alerting rules, data feed and detection settings, and tuning anomaly detection behavior for your instance. |
| Integrations & Coding Patterns | L54-L58 | Connecting Metrics Advisor to various data sources, crafting valid ingestion queries, and using its REST API/SDKs to integrate anomaly detection into applications |
| Topic | URL |
|-------|-----|
| Plan and manage Azure Metrics Advisor costs and usage | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/cost-management |
| Topic | URL |
|-------|-----|
| Understand Metrics Advisor limits and constraints | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/faq |
| Topic | URL |
|-------|-----|
| Configure encryption and authentication for Metrics Advisor | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/encryption |
| Create and manage Metrics Advisor credential entities securely | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/how-tos/credential-entity |
| Topic | URL |
|-------|-----|
| Configure Metrics Advisor instance and detection settings | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/how-tos/configure-metrics |
| Topic | URL |
|-------|-----|
| Connect diverse data sources to Metrics Advisor | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/data-feeds-from-different-sources |
| Use Metrics Advisor REST API and client SDKs | https://learn.microsoft.com/en-us/azure/ai-services/metrics-advisor/quickstarts/rest-api-and-client-library |
Query the OFR (Office of Financial Research) Hedge Fund Monitor API for hedge fund data including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms. Access time series data on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management. No API key or registration required. Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data.
Design and automate Extract, Transform, Load data pipelines for data integration and analytics
Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.
Auto-instrument Node.js applications with distributed tracing, metrics, and logs.
Azure Monitor Query SDK for Java. Execute Kusto queries against Log Analytics workspaces and query metrics from Azure resources.
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
Use this skill when you need to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
Take microsoftdocs/azure-metrics-advisor 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.