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

Annotations already declare this tool safe (readOnlyHint, idempotentHint, destructiveHint false), so the description need not repeat that. It adds useful context about the data population and the counted attributes, but it does not describe the result shape or whether output is raw counts, percentages, or rates. Nothing contradicts the annotations.

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 dense sentence states the core purpose and lists the measured fields, followed by a brief license note. The list is necessary for scope precision, and the sentence is front-loaded with the query intent. Only the license line adds marginal value, but it is short.

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 parameterless, read-only statistics tool, the description adequately specifies the population and the variables being counted. However, there is no output schema and the description does not clarify whether the result is a single count, per-field counts, or a percentage/rate, which leaves some ambiguity for an agent selecting or invoking the 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?

The tool has zero parameters and the schema is empty, so parameter semantics are fully covered by the schema. The baseline for no parameters is 4; no additional explanation 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 conveys a specific aggregation resource: counts of live Korean ESL job adverts that disclose each listed employment term. The verb is implicit ('how many' = count), but the resource and scope are clear enough to distinguish it from salary_stats, which concerns salary amounts rather than disclosure presence.

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 explicit guidance on when to use this tool versus siblings like salary_stats, search, or fetch. The intended use can be inferred from 'how many ... state ...', but no alternatives or exclusion conditions are named.

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