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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the return payload (pinyin, meaning, HSK level, link), which is genuinely useful given there is no output schema, but it says nothing about match behavior (exact vs fuzzy), what happens when the word is not found, or any auth/rate considerations.

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 tight sentences: the first establishes the action and scope, the second establishes the return. Zero filler and the essential information is front-loaded.

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 one-parameter tool with no output schema, the description covers both input expectations and return fields, which is close to sufficient. The only meaningful omission is not-found/fuzzy-match behavior, which matters for a dictionary lookup but is not required to call the tool correctly.

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 description coverage is 100% for the single parameter, and the description merely restates the same three accepted forms (Chinese word, pinyin, English word) already documented in the schema. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb+resource ("Look up a Chinese word... in the HSK Studio dictionary") and names the accepted input forms, so the agent knows exactly what this does. It does not explicitly differentiate itself from siblings like list_words_by_level or get_reading, but the singular 'word lookup' framing makes the distinction reasonably inferable.

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?

There is no when-to-use or when-not-to-use guidance and no named alternative, despite several siblings (list_words_by_level, list_readings, check_text_level) that an agent could plausibly confuse with a lookup. Usage is only weakly implied by the verb 'look up'.

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