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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds real behavioral context beyond that: the 90-day window, the exclusion of already-answered topics, and the aggregate output shape (distinct requester counts, countries).

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, front-loaded with the core definition before the usage hint. Every clause carries information: scope, time window, output fields, and purpose. No padding.

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?

There is no output schema, so the description correctly carries the burden of describing returns (topics, distinct requester counts, countries) and the 90-day scope. It omits any mention of ordering or volume limits, a minor gap for a short read-only list tool with fully documented parameters.

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 100%, so both filters (q, country) are already documented in the schema. The description adds nothing about filtering behavior, so the baseline of 3 applies.

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?

States a specific verb ('Lists') plus a narrowly scoped resource: unanswered topics requested in the last 90 days, with request counts and countries. This scope is distinct enough from siblings like search_data or browse_marketplace that an agent can recognize it without ambiguity.

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?

'Useful to see what data is missing, or what a dataset in the marketplace could supply' implies the intended use case, hinting at a relationship with browse_marketplace. However it never states when to prefer this over alternatives (e.g. report_data_issue for logging a gap) or any exclusions, leaving routing to inference.

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