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 genuinely new behavioral context: mention_count is a heuristic copied from the source JSON rather than true hit counts, and the tool does not fabricate categories or counts — a substantive data-fidelity guarantee that prevents misreading results.

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 short sentences, front-loaded with the purpose and followed by the two caveats that matter most. No filler, though the phrase "the JSON cut" is left undefined and slightly compresses what could be a clearer provenance statement.

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 description carries the burden of explaining results; it names categories and mention_count but leaves the response structure, ordering, typical cardinality, and what qualifies a category as "hot" unspecified. Adequate for a one-optional-parameter read tool, but not fully self-contained.

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 coverage is 100% and the single `observed` parameter is fully documented in the schema, including the format and the omit-for-latest default. The description adds nothing about the parameter, 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?

"Return hot demand categories recorded on a public baseline" gives a specific verb (return) and resource (hot demand categories) with a stated data source. It is clear enough to distinguish from mutation-oriented or listing siblings, but it never explicitly contrasts itself with 'deltas' or 'latest_brief', which sound adjacent.

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?

There is no when-to-use or when-not-to-use guidance and no mention of the sibling tools (deltas, latest_brief, list_observed_dates) that an agent would need to choose between. Only the schema's "omit for the latest committed cut" hints at usage, and that is parameter-level, not tool-level.

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