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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context beyond that: it discloses the breadth of the returned metric set, the 'ONE category' scope, and the ability to query at any depth. It doesn't cover error or fallback behavior when no category identifier is provided, but that's a minor gap given the annotation coverage.

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?

Three tightly structured sentences: core purpose, detailed metric inventory, and concrete example user queries. Every sentence earns its place, and there is no redundant or filler content.

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, the metric enumeration in the description compensates well by telling the agent what kinds of data will come back. The main gap is that no parameters are required in the schema, but the tool logically needs category_id or category_name; the description implies this but doesn't state it explicitly.

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. The description adds no additional parameter-level meaning beyond what the schema already provides; it restates the one-category scope and metric families, but doesn't clarify whether category_id and category_name can be used together or whether at least one is required.

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 uses a specific verb and resource: 'Return the full metric set for ONE category at any depth.' It clearly distinguishes itself from sibling category tools by emphasizing that it returns the full metric bundle for a single category, including demand, competition, and Amazon presence metrics.

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?

The description explicitly lists trigger phrasings like 'show me the metrics/stats for category X' and 'how big is the X category,' which gives clear usage context. It does not explicitly contrast with related sibling tools such as evaluate_category_for_private_label or category_top_growers, so exclusion guidance is only implicit rather than direct.

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