Clears the learning record for a specific Chinese idiom, including draw count, mastery status, and notes, while leaving the dictionary entry unchanged. Use it to restart progress tracking for that idiom.
清空某个成语的学习记录（抽中次数、状态、备注），词库本身不受影响。
Args: word: 成语原文
| Name | Required | Description | Default |
|---|---|---|---|
| word | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds real value beyond the annotations by enumerating exactly what is destroyed (抽中次数、状态、备注) and what is preserved (词库本身); that is precisely the 'what gets destroyed' context the rubric credits. Gaps remain: irreversibility/undo, and behaviour when no record exists. Note the annotation pair itself is internally inconsistent (readOnlyHint=true alongside destructiveHint=true); the description agrees with destructiveHint, so the conflict appears to lie in the annotations rather than in the description.
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 main clause is front-loaded and the destructive scope is stated in the first sentence with zero preamble. The trailing Args block largely restates the schema and is the only mild redundancy.
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 one parameter, an output schema, and annotations present, the description covers purpose, destroyed/preserved data, and the argument's meaning. It still omits whether the reset is reversible and what the tool does when the idiom has no learning record, which matter for a destructive operation.
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 0% (the only property has no description), so the description must carry the parameter, and it does add meaning with 成语原文 (the idiom string itself). It does not clarify matching rules — exact string vs fuzzy, case/whitespace, or what happens with an unknown word — leaving the 0%-coverage gap only partly closed.
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: 清空某个成语的学习记录, and immediately bounds the scope with 词库本身不受影响, which separates it from the word-bank-level siblings (search_idiom, draw_idiom). It does not name the near-neighbour it is distinguished from (update_status, add_note), so an agent must infer the granular-vs-wholesale split.
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 is only implied: clearing a whole learning record suggests use when an idiom should be re-learned from scratch, versus the granular siblings update_status and add_note. No explicit when-to-use/when-not, no prerequisites (e.g. must the record already exist), and no alternatives are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.