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

Annotations already declare readOnly, idempotent, closed-world, and non-destructive, so safety is covered. The description adds real context beyond them: the counts are scoped to *published* entities and the response includes a data-freshness timestamp, telling the agent what the payload actually contains.

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?

One sentence, front-loaded with the primary outcome (counts) and ending with the secondary one (last changed). No filler, no restatement of the title.

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 zero-parameter, read-only aggregate with no output schema, the description covers what is returned and its freshness dimension. Minor gaps remain — the timestamp format and whether counts are global or scoped — but nothing blocks correct invocation.

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?

The tool takes zero parameters, which is the baseline-4 case; the description correctly signals a no-argument aggregate call rather than leaving the agent guessing at hidden filters.

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?

Names a specific verb (get) and a precise resource: aggregate counts of published AI image tools, places, and categories plus a last-changed timestamp. That count-oriented payload implicitly separates it from the list_* and search_listings siblings, which return items rather than totals, though the description never states that contrast explicitly.

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 only implied: an agent can infer this is the summary/counts tool rather than a listing tool, but there is no explicit 'use this when you need totals or freshness' guidance and no statement of when not to use it.

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