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dt-davis-analyzers

Forecast and analyze Dynatrace time-series data with Davis Analyzers.

2|1|Updated Apr 15, 2026
Search Tags:#mcp#forecasting#notebooks#anomaly-detection#correlation#davis-analyzers
One-click install
npx skills add https://github.com/israel-salgado/dt-mcp-server --skill dt-davis-analyzers
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dt-davis-analyzers
Source: https://github.com/israel-salgado/dt-mcp-server/tree/main/.agents/skills/dt-davis-analyzers
Command: npx skills add https://github.com/israel-salgado/dt-mcp-server --skill dt-davis-analyzers

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Davis Analyzers provide AI-driven analysis including time series forecasting, anomaly detection, baseline calculation, and correlation to help investigate and monitor Dynatrace environments.

Core Features & Use Cases

  • List available analyzers and their capabilities
  • Execute analyzers with proper parameters and timeframes
  • Interpret analyzer results in investigations and notebooks
  • Always load dt-dql-essentials/SKILL.md first before any DQL or analyzer work
  • Combine analyzer output with Davis Problems and DQL

Quick Start

Run dt.statistics.GenericForecastAnalyzer for a given metric over a chosen timeframe and review the results in notebooks.

Frequently Asked Questions about dt-davis-analyzers

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I forecast time-series data and detect anomalies in Dynatrace environments?▼

You can forecast time-series data and detect anomalies by running Davis Analyzers like dt.statistics.GenericForecastAnalyzer over a chosen timeframe to generate forecasts, calculate baselines, and reveal metric correlations during investigations.

What do I need to run Davis Analyzers for time-series analysis?▼

Running Davis Analyzers requires loading dt-dql-essentials/SKILL.md first to establish the DQL foundation, then executing analyzers with proper parameters and timeframes via the MCP server within notebooks.

Can I use Davis Analyzers with notebooks to investigate Davis Problems?▼

Yes, Davis Analyzers integrate directly with notebooks and Davis Problems, allowing you to combine analyzer output with DQL workflows to investigate anomalies and monitor Dynatrace environments.

How does anomaly detection work when analyzing metrics with Davis Analyzers?▼

Anomaly detection works by executing analyzers with specified timeframes to calculate baselines and identify deviations, providing AI-driven analysis results that can be interpreted within investigations and notebooks.

What types of correlations can I reveal using Davis Analyzers?▼

Davis Analyzers reveal correlations across entities and metrics by executing analyzers with proper parameters, helping you identify relationships and dependencies during Dynatrace environment investigations.

Why do I need to load dt-dql-essentials before running Davis Analyzers?▼

You need to load dt-dql-essentials first because it provides the foundational DQL framework required before executing any analyzer work or DQL operations through the MCP server.

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