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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds genuine extra context: only 'live' (not expired) adverts are counted, and the data is CC BY 4.0 licensed, which matters for downstream attribution.

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?

A single dense sentence front-loads the scope and enumerates the measured fields, with the license tucked at the end. Slightly list-heavy phrasing but no wasted clauses.

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 return-value burden and does so: per field, the count that disclose it, the denominator, and the percentage. The one real gap is temporal scope — whether the figures are all-time, current, or over a window.

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?

There are zero parameters, so there is nothing for the description to disambiguate; the baseline applies. The enumerated metric list does clarify what the (absent) filters would otherwise have scoped.

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?

States a specific resource (live Korean ESL job adverts) and the exact measurement (count and percentage disclosing salary, hours, severance, pension, insurance, airfare, vacation, split shifts). A verb is implied rather than stated and it never names how it differs from the sibling salary_stats, so it falls short of full sibling differentiation.

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 domain ('live Korean ESL job adverts') implies when the tool applies, but there is no explicit when-to-use, when-not, or routing versus salary_stats and market_stats, which are the obvious overlapping siblings. The agent must infer the choice from the field list.

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