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

Annotations already establish readOnly, idempotent, and non-destructive behavior visa-vi hints. The description adds meaningful context beyond those hints: the statistics are computed from live listings, are licensed CC BY 4.0, and cover specific breakdowns. There is no contradiction with 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?

A single dense sentence front-loads the subject and source, then uses a colon-separated list to enumerate the statistics. Every element earns its place, including the license note.

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 covers scope, source, content, and licensing. It does not specify the exact output structure or statistical methodology, but the low complexity and strong annotations make this a minor, non-blocking gap.

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, so input ambiguity is minimal and the baseline is 4. The description compensates by detailing what output dimensions are included, which is useful given there is no output schema.

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 clearly identifies the resource: English-teacher salary statistics for South Korea, and enumerates the specific breakdowns and metrics included (median, quartiles, by region, effective pay, etc.). It lacks an explicit verb like 'returns' or 'provides', and it does not directly distinguish itself from the sibling disclosure_stats, which likely overlaps on disclosure rates.

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 description implies this tool is for aggregate salary statistics rather than individual listings or searches, but it never explicitly states when to choose it over alternatives like search_jobs or disclosure_stats. No exclusions or routing guidance is provided.

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