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

With no annotations, the description carries the full burden. It discloses important behavioral traits: determinism ('Deterministic'), sourcing ('cites primary sources'), and a billing policy ('errors and unverified rules are never billed'). It also states the cost ($0.01/call). This goes beyond what schema provides and is valuable for agent decision-making.

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, front-loaded with the core purpose, followed by cost and reliability guarantees. Every sentence adds unique value with no redundancy or filler.

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?

For a tool with 8 parameters and no output schema, the description gives some context (rate table, previous month dependency, billing rules) but does not elaborate on how parameters interact or what the output format is. It is enough to understand the general purpose, but incomplete for a complex Japanese tax calculation without explicit documentation of edge cases or return values.

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 coverage is only 13%, so the description must compensate. It adds meaning by connecting the calculation to 'social insurance and withholding tax (official rate table, based on previous month salary),' hinting at the role of parameters like previous_month_after_si_yen. However, it does not explain individual parameters like age, dependents, or prefecture, leaving gaps that schema also does not fill for 87% of parameters.

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's function: 'Bonus net pay: social insurance and withholding tax (official rate table, based on previous month salary).' It identifies the specific resource (bonus net pay) and the key inputs (rate table, previous month salary), distinguishing it from sibling tools like jp_payroll_net which likely handles regular salary.

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 usage for bonus-related net pay calculations, but does not explicitly state when to use this tool over alternatives or when not to use it. It mentions a dependency on 'previous month salary,' which provides some context, but lacks explicit exclusions or alternative tool comparisons.

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