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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds useful behavioral context about what data is returned (medians in two contract types, national comparison, top-demand occupations), but says nothing about data freshness, coverage limits, or error behavior when an unknown city is supplied.

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?

Two sentences: the first is a dense, front-loaded enumeration of the metrics returned, the second is a concise English summary. No filler, no repetition of the tool name, and the most important information comes first.

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 read-only, single-parameter, no-output-schema tool, the description is largely complete: it tells the agent what the tool returns and what input shape to expect. It only falls short on how this tool relates to its salary-focused siblings, which is the one missing piece an agent would need for disambiguation.

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?

Schema description coverage is 100% and the single parameter has a clear description with example values ('Kraków', 'gdansk'), so the baseline is 3. The tool-level description reinforces that the parameter scope is a Polish city, which is modest added value. With one parameter and full schema coverage, a 4 is appropriate.

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 specific resource (city salary data in Poland) and enumerates the concrete metrics returned: offer count, medians (UoP/B2B), pay relative to the national average, and in-demand occupations. This is much more than a restatement of the name. However, it does not explicitly distinguish itself from siblings like get_salary or get_rankings, which likely return overlapping salary data.

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?

Usage is implied: fetch city-level salary aggregates. But there is no explicit when-to-use guidance, no mention of when to prefer get_salary or get_rankings instead, and no stated condition that selects this tool over its siblings. The agent must infer the boundary from the description's content alone.

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