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

With no annotations, the description carries the burden and does meaningful work: it discloses a k-anonymity behavior ('every bucket covers at least 3 farms and names none') and that results are dated and cited, which an agent could not infer from the schema. It omits auth requirements, rate limits, and return shape, keeping it below 5.

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?

Front-loads the core purpose in the first clause and the return contents (low/median/mean/high, counts, as-of dates) before the sibling routing. Two sentences with little waste, though the parenthetical list is slightly dense.

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 no output schema and no annotations, the description supplies the return fields, the aggregation granularity, and the privacy floor, which is sufficient for correct invocation. Missing only operational details like pagination or error behavior, minor for an aggregate read tool.

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 parameters are already documented in the schema (good slug, province slug/code/name). The description only adds that omitting province yields national scope, which the schema already implies. Baseline 3 is appropriate.

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 (aggregate) and resource (price statistics for a good), names the data source, and explicitly differentiates itself from get_farm by noting that single-farm prices come from that sibling. An agent can distinguish it from every sibling without opening a schema.

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 routes the agent to get_farm for single-farm prices and specifies the geographic scope (national or one province), giving clear context for when this tool applies. It stops short of explicitly stating when-not to use it (e.g. for live listings or non-price queries), but the alternative is named with its selecting condition.

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