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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered and the description need not restate it. What the description leaves out is the behavior an agent actually needs: what each tool_id computes, what 'params' must contain per assay, and what the result looks like beyond the placeholder 'RETURNS: 计算结果'. Nothing here contradicts 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 piped, front-loaded layout is scannable and the USE WHEN clause comes early. However, the long bilingual alias list and the zero-information 'RETURNS: 计算结果' line consume tokens without adding decision value, and the bilingual duplication of the title is redundant.

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 dispatcher over four distinct computations with an opaque nested params object and no output schema, so the description carries the full burden of explaining per-assay inputs and outputs. It does not: an agent can choose a tool_id but cannot reliably construct a valid 'params' payload or know what comes back.

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?

Although nominal schema coverage reads 100%, the critical 'params' property is an unconstrained nested object described only as '该工具所需参数', and the description does not compensate by listing which fields each tool_id requires. The agent knows to pick cck8/wound-healing/transwell/colony but has no information about the payload, so the description adds almost no semantic meaning for the higher-risk parameter.

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 that the tool performs cell-assay calculations and enumerates four concrete assay types (CCK8, wound healing, Transwell, colony formation) via the tool_id selector, which distinguishes it from the statistics and imaging siblings. It never states the verb explicitly (compute what: viability %, migration area, colony count?), so purpose is clear but not fully pinned down.

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 'USE WHEN' clause gives explicit triggering conditions naming the exact assay scenarios, and the tool_id enumeration tells the agent how to route within the tool. There is no when-not guidance and no mention of alternatives (e.g. ic50_fit, tumor_growth_inhibition, or stats_toolbox for downstream analysis), which keeps it below a 5.

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