get_metric_metadata

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

With no annotations provided, the description carries the full burden. It discloses the type of data returned (units, description, tags, integration information) but does not explicitly state that the operation is read-only, mention any required permissions, or describe error behavior. The read-only nature is logical but not explicitly stated, so it falls short of full transparency.

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

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

The description is a single, complete sentence that front-loads the verb and resource. It is concise without unnecessary words and effectively communicates the tool's purpose in one line.

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

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

For a simple tool with one parameter and no output schema, the description adequately covers the return values by listing what metadata is included. It doesn't explain response format or error cases, but given the low complexity, it is mostly complete.

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

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

The schema already provides 100% coverage for the single parameter (metricName is described as 'Name of the metric to get metadata for'). The description adds no additional meaning or syntax details beyond what's in the schema, so the baseline score of 3 is appropriate.

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

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

The description clearly states the action ('Retrieve') and the resource ('metadata about a Datadog metric'), with specific content areas ('units, description, tags, and integration information'). This is specific enough to distinguish from sibling tools like query_metrics (which queries time-series data) and list_metrics (which lists metrics).

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

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

The description implies a use case (retrieving metadata rather than querying metric data) but does not explicitly state when to prefer this tool over alternatives such as query_metrics or list_metrics. No exclusions or context are provided, so it only partially guides the agent on tool selection.

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