Multilingual word/char/sentence count (CJK-aware).
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": "text_count"
}
}| 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 behavioral burden. It usefully discloses CJK-aware multilingual counting, but it does not explain the return shape, how word/character/sentence boundaries are handled, or whether counts are returned together.
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 definition is a single front-loaded sentence with no wasted text. The parenthetical CJK qualifier is compact and relevant.
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 one-parameter counting utility, the description gives enough context to invoke it with text. However, because there is no output schema and the description does not specify the return structure, an agent cannot fully know how to interpret the result.
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 required parameter named text with no schema description. The description adds some semantic context by indicating multilingual and CJK-aware handling, but it does not explicitly describe the input parameter or its expected format.
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 states a specific verb-resource pair: counting words, characters, and sentences. It also adds a useful qualifier, multilingual and CJK-aware, that distinguishes it from generic text utilities. It does not explicitly distinguish itself from sibling estimate_tokens, so it stops short of a 5.
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 description says what the tool does but provides no guidance on when to use it versus alternatives such as estimate_tokens. There are no exclusions, prerequisites, or contextual triggers for selecting this 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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