get-metrics

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

No annotations are provided, so the description carries full burden. It only describes basic functionality and parameter usage, lacking disclosure of behavioral traits like pagination, rate limits, or output format. This is a significant gap for a search tool.

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?

Two sentences with no fluff. Front-loaded with purpose, followed by usage examples. Every sentence earns its place.

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 one-parameter tool with no output schema, the description is nearly complete. However, it omits behavioral details like pagination or result limits, which would help an agent anticipate behavior.

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 property 'q' has no description (0% coverage). The description adds meaning: 'searches metric names' and provides an example. This compensates well, though more detail (e.g., wildcard support) would be beneficial.

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?

Description clearly states it searches for Datadog metrics by name pattern, with examples like 'what CPU metrics exist'. This distinguishes it from other metric-related sibling tools like get-metric-metadata (specific metadata) and query-metrics (time series data).

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?

Provides clear context with examples of when to use it (discovery of metrics), but no explicit exclusions or alternatives. The examples imply usage scope, making it functional but not fully comprehensive.

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