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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds real value beyond that: it discloses the return shape ('counts and the date of the newest listing, no job names'), which prevents an agent from expecting a listing payload.

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?

Front-loads the core capability, then usage, then return shape — a sensible information order. The middle sentence is long and enumerates dimensions with some redundancy, but every clause describes a real facet of the output.

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 and does so ('counts and the date of the newest listing, no job names'). An agent has enough to call it and interpret the response, though exact field names or count granularity are unspecified.

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 there is nothing for the description to disambiguate; baseline applies. The schema already enforces an empty object with additionalProperties false.

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?

Opens with a specific verb and resource ('Counts of the open jobs on Seoulstart Jobs') and immediately enumerates the exact breakdowns returned. This clearly separates it from siblings like search_jobs, which returns individual listings rather than aggregate counts.

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?

Gives concrete triggering questions ('how many English-speaking jobs there are in Korea, or which visa routes and roles are common'), which is strong positive guidance. It does not explicitly name search_jobs as the alternative for per-job results, so the exclusion side is left implicit.

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