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. The description does add a genuinely useful behavioral claim beyond the annotations: results come from a real algorithm engine, not LLM generation, which tells the agent the output is deterministic and trustworthy. It says nothing about what happens with an unsupported tool_id or missing params, which matters for a dispatcher.

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 short clauses, purpose front-loaded, no filler, and the trust signal is placed last where it reads as a qualifier rather than the headline. Minor redundancy with the annotation title ('细胞实验通用计算') is the only waste.

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 polymorphic dispatcher with an unconstrained nested params object and no output schema, yet the description never explains the per-tool_id parameter shape or what the returned calculation actually contains beyond '计算结果'. For a tool of this complexity, the definition leaves too much to trial and error.

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 nominally 100%, so the baseline is 3, and the description's enumeration of assay types does help the agent choose a tool_id. However, the 'params' property is a free-form nested object described only as '该工具所需参数', and the description does not explain which fields each tool_id requires — the highest-value information it could have added.

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 concrete verb and resource ('细胞实验通用计算') and enumerates the assay families it covers (CCK8/划痕/Transwell/克隆形成), which maps directly to the tool_id values. It does not, however, distinguish this generic dispatcher from the many specific sibling calculators (e.g. act_ic50_fit, act_qpcr_ddct) that an agent might otherwise pick.

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 gives an implied trigger — the user wants a cell-experiment calculation for CCK8/wound healing/Transwell/colony formation — which is usable guidance. There is no explicit when-not, no mention of which sibling to prefer for adjacent analyses, and the trailing '等' leaves the coverage boundary undefined.

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