get_salary_statistics

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It honestly discloses the sampling bias and that sampling is done client-side, but does not mention potential side effects like multiple API calls (implied by sample_pages parameter) or error behavior. It conveys the most important limitation but lacks depth beyond that.

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 two sentences, with the primary purpose stated first, followed by the key limitation. It is concise, front-loaded, and contains no fluff while conveying the essential information in a compact form.

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?

The description explains the output (median, P25/P75, min/max), the method (sampling client-side), and the bias, which is sufficient for a simple estimation tool. It doesn't describe errors or detailed return formatting, but the schema covers formatting options. It could mention how to find role/area IDs, but the schema already points to get_professional_roles and get_areas.

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%, so the schema fully documents all parameters (raw, text, area_id, sample_pages, professional_role_id) with their meaning and hints on finding IDs. The tool description adds no additional parameter-level detail, so it meets the baseline without adding extra value.

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 the tool estimates salary distribution (median, P25/P75, min/max) for a professional role in a region, specifying the action (estimate), resource (salary distribution), and scope (role+region). It distinguishes itself from sibling tools like search_vacancies and get_vacancy by focusing on statistical salary estimates, not individual vacancies.

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 provides context that the estimate is based on a biased sample (only vacancies disclosing salary) and explicitly says it is 'not official market data', which implicitly guides when to use it (for quick estimates) and when not to (for authoritative figures). However, it does not name specific alternative tools, so it falls short of explicit when-to-use guidance.

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