get_metric

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

With no annotations, the description carries the full burden. It discloses that the returned definition includes caveats and warns about common misinterpretations (denominators, incomplete months), which is valuable context. However, it does not address error behavior, permissions, or side effects, though the 'get' verb implies a safe read operation.

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 core purpose is front-loaded in the first sentence, and the second paragraph adds meaningful guidance on why caveats matter. Every sentence earns its place; there is no fluff or repetition.

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?

The output schema covers return values, and the tool is simple. However, the 0% parameter coverage and lack of any pointer to list_metrics as the source for metric_id leave a gap in correctly invoking the tool. The caveat emphasis is helpful but does not compensate for the missing parameter guidance.

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 single parameter metric_id is not mentioned or explained in the description, and schema coverage is 0%. The description provides no guidance on how to obtain a valid ID, its format, or its relationship to the returned definition, leaving the agent completely dependent on the bare schema.

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 returns 'the full definition of one metric, including its caveats', identifying a specific resource and scope. This distinguishes it from siblings like list_metrics (which lists metrics) and query_metric (which queries values).

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 instruction to 'read the caveats before describing a number' implies this tool is the source for caveats, but the description never explicitly compares it to list_metrics, query_metric, or verify_answer, nor states when not to use it. Usage is implied but not directly guided.

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