query_traces

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

With no annotations provided, the description must carry the burden of behavioral disclosure. It explains the return data (trace data with latency and span details), which is helpful. However, it does not explicitly mention that the operation is read-only, nor does it discuss any limitations such as sampling, pagination, or required permissions. The description is adequate but not comprehensive in disclosing behavioral traits.

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 composed of three short, purposeful sentences: the action, the output, and the use case. It is front-loaded with the core verb and resource, contains no redundant information, and every clause earns its place. This is an excellent example of concise, well-structured writing.

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?

Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description provides enough context: it identifies what the tool does, what it returns, and a typical use case. It doesn't enumerate the required time range or filter syntax, but those are already detailed in the schema. The description is complete enough for an agent to select and invoke the tool correctly.

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 input schema has 100% parameter description coverage, so each parameter is already fully documented. The description does not add meaning beyond the schema, instead focusing on the tool's purpose and output. Per the rubric, baseline 3 is appropriate when the schema does the heavy lifting, and the description doesn't compensate with extra parameter context.

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 tool's function: 'Query Datadog APM traces for a service.' It specifies the resource (APM traces), the scope (for a service), and the output (trace data with latency and span details). This distinguishes it from sibling tools like query_metrics or search_logs, which operate on different data types.

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 provides a clear use case: 'Useful for performance debugging.' This gives context on when to use the tool. It doesn't explicitly name alternatives or state when not to use it, but the sibling tools are so distinct that the intended usage is clear. A brief exclusion would make it perfect, but the current guidance is sufficient.

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