maritime_compare_wages

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

No annotations are provided, so the description bears full burden. It discloses that the tool calculates mean and median wage differences, uses two data sources with specific time ranges, and reports a percentage difference. It also mentions that the origin filter is only effective with MDB records. It does not describe error handling or data availability scenarios, but overall it covers key behaviors.

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 moderately sized with a clear front-loaded purpose. It uses bullet points for parameters and tips, making it scannable. A few sentences could be trimmed, but overall it is efficient and well-structured.

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?

Given 8 parameters, no output schema, and no annotations, the description covers the tool's functionality, parameters, return format, and usage tips. It explains the data sources and filter limitations. It lacks details on error cases or extreme inputs, but provides enough for typical use.

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%, so the description must describe each parameter. It does so by listing each argument with a brief explanation (e.g., 'group1_start: Start year for first comparison group'). It also provides defaults and tips for source and output_mode, adding meaning beyond the schema's type information.

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 compares crew wage distributions between two time periods, calculates mean and median wages, and reports percentage difference. It distinguishes itself from sibling tools like maritime_compare_speed_groups by focusing on wages. The verb 'compare' and resource 'wage distributions' are specific.

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 tips for LLMs on data source selection and filter constraints (e.g., origin only works with source='crews'). However, it does not explicitly state when to use this tool over alternatives like maritime_crew_demographics or search_crew. It gives clear context for usage but lacks exclusion criteria.

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