檢查一段文字的 AI 生成特徵（常用語、排版、個人經驗用語、句長一致性），回傳 0～1 分數。僅供參考。
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"text": "<text>"
},
"name": "check_ai_text"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose the output shape (0–1 分數) and an important behavioral caveat that the result is advisory only ('僅供參考'), which is genuinely useful. It stops short of stating accuracy limits, language assumptions, or input-size constraints.
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 compact sentences with the purpose and the inspected signals front-loaded, followed by the score range and the advisory caveat. Nothing is padded, though the parenthetical signal list is dense for a short description.
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 single-parameter analysis tool with no output schema, the description covers input intent, the analysis dimensions, the return range, and the advisory caveat. That is nearly enough for an agent to call it correctly, missing only input format/length caveats.
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?
There is one parameter ('text') with 0% schema description coverage, and the description only implies it is the text being analyzed. The description explains what the tool looks for in that text, which adds some meaning, but gives no format, length, or language guidance for the input.
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 (檢查) and resource (一段文字的 AI 生成特徵) and even enumerates the signals inspected (常用語、排版、個人經驗用語、句長一致性). That is well above a vague purpose statement, though it does not contrast itself with the sibling tools.
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 statement of when to reach for this tool versus the siblings (get_taiwan_post, search_human_opinions, etc.), nor any exclusions. '僅供參考' is an interpretive caveat about the result, not usage guidance for selecting or applying the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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