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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the burden is lower. The description adds two useful traits the annotations lack: the data is restricted to 'live' adverts, and the scope is Korean ESL postings. It does not disclose the shape or granularity of the numbers, which is a gap given there is no output schema.

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 front-loaded sentence plus a license tag; no filler. It is slightly awkward as a question rather than a declarative statement, which costs a point.

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 stat tool the description does enumerate the exact attributes measured, which partially substitutes for the missing output schema. However it never says whether results are counts, percentages, or broken out by time period, leaving the return shape ambiguous.

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, so the baseline of 4 applies. Schema coverage is 100% and there is nothing for the description to disambiguate.

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 names a concrete resource: disclosure counts for eight specific attributes across live Korean ESL job adverts. That is enough for an agent to know what comes back, but it never states the operation as a verb (list/aggregate?) and does not distinguish itself from salary_stats or market_stats.

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 statement, no alternatives named among the six siblings, and no condition that selects this tool over salary_stats or market_stats. The agent must infer routing from the topic alone.

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