salary_history

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns rates for each data version since 2020 and notes that the source only has the latest snapshot, which is a useful behavioral trait. However, it does not mention output format, ordering, error behavior, or limitations such as potential missing versions.

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?

The description is compact and well-structured: a one-sentence summary, a clarification about the data source, and a clearly formatted Args section. Every sentence adds value without redundancy or filler.

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 single-parameter tool with an output schema, the description covers the essential aspects: what the tool does, what parameter to provide, and a notable caveat about the source data. It does not explain the output structure, but the output schema presumably covers that. The only minor gap is the absence of guidance on handling missing subjects or unclear matches.

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 schema has no descriptions (0% coverage), so the parameter explanation in the description is essential. It specifies 'subject' as a full or partial name of a Russian region with concrete examples ('Иркутская' or 'Москва'), clarifying the matching behavior. This adequately compensates for the missing schema metadata, though it could also mention case sensitivity or formatting nuances.

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 states that the tool shows the dynamics of average monthly wages for a 1st-category construction worker by region, with a specific verb 'Показывает' (shows) and a defined scope: rate per data version since 2020. This differentiates it from siblings like salary_growth_ranking and dataset_versions by focusing on historical version-over-version values.

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 explains that the source only contains the latest upload and that dynamics are not present there, indicating this tool is needed to see historical version data. However, it does not explicitly compare against alternatives like salary_growth_ranking or provide clear conditions for when to prefer one tool over another.

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