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

Annotations already declare readOnlyHint, idempotentHint, closed-world, and non-destructive, so safety needs no explanation. The description adds genuine context beyond that: the temporal range (2008–), the two currency representations, and the inclusion of employee counts, which tells the agent what the payload contains.

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 sentence, front-loaded with the core measure, with every clause (time range, geography, currencies, employee counts) carrying distinct information. Nothing is redundant.

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 one-parameter read-only lookup with no output schema, the description covers measure, scope, units, and payload contents well. It could note the return shape or ordering, but nothing essential to correct invocation is missing.

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 coverage is 100% and the region parameter already documents its slug format and example values from list_regions. The description's phrase 'Bulgaria, a NUTS2 region or an oblast' reinforces the accepted geographic granularity but adds no syntax or constraint detail the schema lacks, so the baseline 3 applies.

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 states a specific measure (average gross monthly wage), coverage start year (2008–), geographic scope (Bulgaria, NUTS2 region, or oblast), and units (euro and leva plus employee counts). The 'by region' framing implicitly separates it from get_activity_wages and get_occupation_wages, though those siblings are never named.

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 only implied: an agent can infer this retrieves wage statistics for a given region. There is no explicit when-to-use versus get_activity_wages/get_occupation_wages, and the list_regions prerequisite appears only in the schema, not the description.

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