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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety and closed-world scope are covered by structured fields. The description adds that the result contains severity and mechanism, which is useful, but it says nothing about behavior when a drug is unknown or ambiguous (no match, error, or empty result).

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 pipe-delimited layout is easy to scan, and the USE WHEN clause is front-loaded ahead of aliases and returns. The repeated bilingual title at the start is mildly redundant with the tool name and title fields, but nothing is verbose.

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 simple two-argument read tool with annotations and no output schema, the description covers purpose, trigger and return shape adequately. The notable omission is input expectations for drug naming, which materially affects a correct call, plus the handful of near-neighbor pharmacology tools it does not help disambiguate.

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%, but the field descriptions are only '药物 A' and '药物 B', so the schema itself adds little. The description does not specify whether names should be generic or brand names, Chinese or English, or what format is accepted, leaving the key semantic question unanswered.

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 ('Drug-drug interaction check') and states the scope ('interaction severity and mechanism'), which lets an agent distinguish it from neighbors like toxicity_predict, toxicology_assess or pk_pd_assess. It never explicitly names which sibling to use instead, so differentiation is implicit rather than stated.

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?

'USE WHEN: can these two drugs be used together?' gives a concrete triggering question, and the ALIASES list helps matching ambiguous user phrasing such as 配伍禁忌 or 能不能一起用. There are no exclusions or alternative-tool routing (e.g. when to prefer pk_pd_assess for dosing questions), 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.