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

The annotations already state readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. Beyond that, the description discloses what the response will report: the direction of the recommendation, the savings amount, and the cliff-point warning. It still does not state assumptions such as how default deductions of 0 affect the result, but it adds real behavioral value on top of the 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 one front-loaded sentence that states the comparison first, then the outputs, then the cliff-point warning, with no filler. It is dense but readable; splitting it would slightly improve scannability, but nothing needs to be cut.

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 deterministic four-parameter calculator that has an output schema, the description covers the purpose, the comparison basis, and the key return highlights, so an agent can call it confidently. The only gap is that it does not state the default-deduction assumptions or limitations such as jurisdiction or tax year, but the schema and annotations cover most of that.

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 100%, and every parameter already has a Chinese description covering units and defaults, so the schema handles this dimension well. The tool description adds no parameter-level meaning beyond that; it only restates the two taxation methods at a conceptual level. A baseline 3 is appropriate.

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 names a specific verb and resource (compare the tax totals of the two statutory bonus taxation methods) and states exactly what the result contains: which method is cheaper, the yuan amount saved, and whether the bonus falls into a rate-cliff 'blind zone'. This makes it clearly distinguishable from siblings such as calculate_income_tax or calculate_salary_take_home.

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?

It makes the usage context clear: the comparison is between the '全年一次性奖金单独计税' and the '并入综合所得计税' methods, which tells an agent the scenario this tool covers. However, it never names an alternative or an exclusion; for example, it does not say to use calculate_income_tax for non-bonus income, nor that it only handles annual bonuses.

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