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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: the exact day-by-day formula, the fact that the start date is excluded, the output fields, and a direct REST fallback with a warning not to guess another API path. This is strong but not exhaustive; it does not discuss failure modes or edge cases like invalid dates.

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 longer than average but well-structured with clear sections: usage, exclusions, computation, examples, outputs, formula, REST fallback, and docs. It front-loads the most important decision information. Some redundancy with the schema exists, but the added examples and formula justify the length.

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 is highly complete for a tool of this complexity. It covers when to use it, when not to use it, the exact computation method, input examples, output fields, a REST fallback, and documentation links. With an output schema present, the listed outputs are a bonus rather than a necessity. Nothing an agent needs to invoke this tool correctly is missing.

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 repeats the parameter names and types and provides complete JSON examples, but it does not add significant semantic detail beyond what the schema already documents. The examples are useful but not transformative.

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: it 'adds or subtracts working days' for UK divisions, with a defined date range and bank-holiday scope. It clearly distinguishes itself from sibling tools like add_china_working_days, check_uk_working_day, and count_uk_working_days by focusing on UK working-day arithmetic for deadlines.

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 gives explicit when-to-use guidance ('Use this when you need a deadline a stated number of UK working days...') and explicit when-not-to-use exclusions ('Do not use this when you need calendar days, a local/employer/market calendar, a non-UK jurisdiction or a result outside 2024-2028'). It does not name specific alternative sibling tools, but the exclusions are clear enough for an agent to route correctly.

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