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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds valuable context beyond that: deterministic computation, caller-supplied data, 'result unverifiable', and the paid cost of $0.002 per call. It does not contradict the annotations.

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 compact and front-loaded with the core function, followed by usage restrictions and cost. Every sentence carries useful information and there is no redundant phrasing.

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 description provides purpose, restrictions, determinism, and cost, but with no output schema it leaves return-value semantics underspecified. It also does not state what descriptive statistics are produced or how metric_fields must relate to observations, both of which an agent would need for correct invocation.

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?

Schema description coverage is 0%, so the description must compensate. It identifies 'observations' as caller-supplied observations and 'metric_fields' as explicitly named numeric fields, which adds basic meaning. However, it does not clarify how metric_fields map to observation keys, what shape observations must take, or what value constraints apply beyond the 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 states a specific verb ('computes'), resource ('descriptive benchmark statistics'), and scope ('caller-supplied observations and explicitly named numeric fields'). This clearly differentiates the tool from the control-plane and verification siblings while matching the benchmark data feed family.

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?

It explicitly states the intended domain ('reliability quality / result unverifiable') and lists prohibited use cases (legal, identity, sanctions, fraud, contractual, regulatory). It does not name alternative tools, but the when-not guidance is strong enough to steer an agent away from misuse.

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