fortune_ranking

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the data source ('Fortune's public ranking data'), the validation behavior, and the read-style nature of the operation ('Search... Returns rows'). It does not disclose error behavior, rate limits, or default/max result caps — though limits (default 100, max 1000) are present in the schema. Adequate but not rich for a tool with zero annotation coverage.

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?

Three sentences with no filler: the first states the verb and resource, the second scopes the data domain, the third describes the behavior. Information density is high and the core function is front-loaded.

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?

This is a 12-parameter tool with no annotations and no output schema, so a heavier lift is required. The description conveys the core capability and validation behavior, and the schema covers all parameters, but it doesn't describe return format or surface the discovery workflow (fortune-ranking-years/filters) that several parameters depend on. Acceptable for a query tool, but with clear gaps.

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 baseline is 3. The description adds context that filters/sorting/pagination are validated against a per-list filter inventory, which complements the filter and sort_by parameters, but it adds no per-parameter meaning beyond what the schema already documents.

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 verb and resource ('Search a Fortune ranking. Returns rows from a selected Fortune ranking list and year') and usefully scopes the data domain (Fortune 500 franchise including China 500 vs. award/culture rankings). It doesn't explicitly name a sibling to differentiate from, but the scope statement plus the schema's references to fortune-ranking-years/filters help an agent place this among the fortune_ranking_* family.

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 implies the workflow — filters and sorting are 'validated against that list/year's filter inventory,' hinting that the agent should discover valid values first. However, it never explicitly says when to use this tool versus fortune-ranking-filters or fortune-ranking-years; the guidance for those is buried in parameter descriptions rather than the main description.

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