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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so safety is covered; the description goes beyond them by disclosing fuzzy-matching behavior and the exact return contents (definition, other-language term, close matches, links). It does not mention rate limits, but none appear relevant for a static 70-term glossary.

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?

Two sentences, zero filler, with the core capability and the bilingual scope front-loaded before the matching and return details. Every clause carries information an agent can act on.

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?

With only two simple parameters and no output schema, the description compensates by enumerating the return payload (definition, cross-language term, close matches, links), leaving no significant gap for correct invocation.

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 lang is enum-documented, so the baseline is 3; the description adds real meaning about the term parameter by noting English or Chinese input, pinyin matching and misspelling tolerance, which tells the agent what forms are acceptable.

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?

Specific verb (looks up) plus resource (trading term in a bilingual glossary) with concrete scope (~70 terms) and representative examples like "R multiple" and "止损". It is cleanly distinguishable from the sibling calculate_* tools because it retrieves definitions rather than computing values.

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 matching description (names, abbreviations, pinyin, misspellings tolerated) clearly signals the situations this tool handles and implicitly when it is the right choice versus the calculator siblings. It stops short of an explicit when-not-to-use or named alternative, so it is strong but not exhaustive.

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