adzuna_salary_histogram

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds value by noting that the API does not guarantee band order but this tool sorts it, and by explaining the error handling ('On failure, an Error... string'). This provides important behavioral details beyond 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?

The description is concise and well-structured: a one-line summary, followed by a clear explanation of the output, a bulleted Args section, and a return format description. It is front-loaded with the purpose and every sentence adds value. No redundant or vague statements.

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 covers the tool's purpose, parameters, output formats, error handling, and a notable sorting behavior. It mentions the response format options (markdown and JSON) and explains the histogram structure. Given that an output schema exists, it is not necessary to detail the return structure further. However, it could be more explicit about the supported country codes and the category parameter's source (adzuna_list_categories), which are only in the schema.

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 0% for the tool's single `params` parameter, but the description compensates by listing each nested field (country, what, location0/1/2, category, response_format) with brief explanations. While the schema itself has good inline descriptions, the description organizes them clearly and reinforces the semantics. A slight gap is not providing examples of valid inputs, but overall adds meaningful 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 verb 'Get' and the resource 'distribution of advertised salaries for a role and/or location'. It explains the output structure (salary band lower bound to vacancy count). The title from annotations ('Get salary distribution') aligns with this. Among siblings, it distinguishes itself from adzuna_salary_history (historical trends) and adzuna_estimate_salary (single estimate) by focusing on current distribution.

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 explicit use cases: 'Use it to sanity-check a salary expectation or to see where a target figure sits in the market.' This gives clear context for when to use the tool. However, it does not mention alternative sibling tools or explicitly state when not to use it, which would improve clarity further.

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