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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely new behavioral facts beyond them: the data vintage (current to 2025-06-30), the exact bounded period coverage, and a per-call price of 5¢, which matters for a paid query. It stops short of describing response shape or pagination, though with no output schema that gap is modest here.

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?

Content is front-loaded: the measure, then coverage and currency, then price, then a pointer to the fuller dataset doc. Every sentence carries information and there is no filler; the only mild redundancy is restating the geographic and period coverage already implied by the opening sentence.

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?

For a three-optional-parameter read-only data tool with no required inputs and no output schema, the description supplies what an agent needs: what is measured, in what units, for which geographies and years, how current the data is, and what it costs. The remaining detail is deliberately delegated to the referenced /v1/datasets/antidepressant-use endpoint.

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 the baseline is 3, but the description adds value the schema does not: it establishes the authoritative valid range for `from`/`to` (financial years 2015-16 through 2024-25) and enumerates the measurable concepts behind the `fields` parameter (count, per 1,000 residents, prescriptions). That lets an agent constrain filters correctly without guessing at boundaries.

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 opens with a precise question — counts of people dispensed antidepressants, per 1,000 residents, plus prescriptions — and pins the geography (Australia plus all 8 states and territories) and time range (2015-16 to 2024-25). It never names the closest sibling (states_health_antidepressant_use), so the boundary between this national roll-up and the state-level tool is left implicit rather than stated.

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?

Usage is implied by the stated coverage (which geographies and which years), letting an agent decide fit, but there is no explicit when-to-use / when-not-to-use guidance and no routing to alternative tools for sub-state or non-antidepressant data. The price line is a cost signal, not usage guidance.

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