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datadog-mcp-server

get-metric-metadata

Read-only

Retrieve metadata (type, unit, description) for a specific Datadog metric to understand its properties and configuration.

Instructions

Get metadata for a specific Datadog metric (type, unit, description)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricNameYesFull metric name. Example: system.cpu.user
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, covering safety and result variability. The description adds that it returns type, unit, and description, providing context about the output. However, it does not disclose potential issues like missing metadata for some metrics or authentication requirements. With annotations handling basic traits, the description adds moderate value beyond structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, 10 words, front-loaded with verb and resource. No filler words. Perfectly concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Simple tool with one parameter and no output schema. Description lists the three key metadata fields, which is sufficient for most use cases. Could optionally mention that the metadata might be empty or contain additional fields, but not necessary for typical usage. Completeness is high for this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage: metricName is described as 'Full metric name. Example: system.cpu.user'. The description does not add new semantic meaning beyond the schema. Baseline 3 per guidelines for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'get', resource 'metadata for a specific Datadog metric', and specifies what metadata is included (type, unit, description). It distinguishes from sibling tools like get-metrics which list metrics, and list-active-metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives like get-metrics or list-active-metrics. The description does not mention prerequisites (e.g., knowing the metric name) or scenarios where this tool is preferred. Sibling tools provide similar functionality but no comparative advice is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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