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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is fully covered. The description adds only one trait beyond that — that the figures carry a freshness dimension — while the rest of the text restates return content that the existing output schema already documents.

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, zero filler. The content enumeration comes first and the usage cue is front-loaded as the final sentence, so an agent gets the payoff before the instruction.

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?

With a rich annotation set, no parameters and an output schema present, the description only needs to say what the tool is for and when to reach for it. It does that, but omitting any contrast with the sibling get_market_coverage leaves a real selection gap in a crowded family of coverage-related tools.

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 tool takes zero parameters, so there is no parameter semantics to explain; the baseline for a 0-param tool is 4. The description correctly implies the tool is parameterless by framing the output as a global dataset shape rather than something that is queried or filtered.

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 names a specific resource (dataset statistics) and enumerates exactly what is counted: instruments by pillar, category and risk, plus KYC-free instruments and freshness. It is clear what the tool returns, though it never distinguishes itself from the sibling get_market_coverage, which an agent could easily confuse it with.

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 gives one concrete use case ('ground a claim about coverage before making one'), which is better than nothing. However, it names no alternative and no when-not condition, and the potentially overlapping sibling get_market_coverage is not mentioned, so the routing decision is left partly to inference.

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