Count words, sentences, paragraphs, and reading time, then check character limits for platforms like X, WeChat, and SMS to see if the text fits.
统计字数、段落、句子、预计阅读时长，并检查常见平台的字数限制。
具体平台（小红书、公众号、短信、X）的超限情况会一起返回。
Args:
text: 要统计的文本。
platforms: 只看指定平台，逗号分隔，如 "xhs_title,mp_digest"；留空表示全部。
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| platforms | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the disclosure burden. It states that per-platform limit status will be returned together with the stats, which is useful, but it does not mention side effects, permissions, error behavior, or the exact output structure. For a read-only counting tool this is adequate but not rich.
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 functionality is front-loaded in the first sentence, followed by a brief note on the included platforms and a compact Args section. Every sentence adds information; there is no filler or repetition.
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?
The description provides enough for correct invocation: required text, optional platform filtering, and the general nature of the returned data. The output schema covers the return shape. The only minor gap is that the full list of valid platform codes is not enumerated, only examples.
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 0%, so the description compensates fully: 'text' is defined as the text to count, and 'platforms' is explained as an optional comma-separated filter with an example ('xhs_title,mp_digest') and a clear default ('empty means all'). This exceeds what the schema alone provides.
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 clearly states the tool's function: counting characters, paragraphs, sentences, reading time, and checking platform-specific length limits. It is distinct from fix_text and list_rules, and the counting focus differentiates it from check_text, though no sibling is explicitly named.
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 intended use is implied by the purpose: call this when a text's statistics or platform-limit status is needed. There is no explicit guidance on when not to use it or which sibling tool to prefer, leaving the comparison to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.