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mcp-han

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check_text

Checks Chinese text for typography, punctuation, common typos, and proper noun casing. Specify rules or severity to focus checks; read-only and skips code and URLs.

Instructions

检查中文文本的排版、标点、常见错别字和专有名词大小写。

这是只读操作，不会修改任何东西。

Args:
    text: 要检查的文本。Markdown 也行；代码块、行内代码、URL、邮箱、
        HTML 标签和公式会被自动跳过。
    rules: 只跑指定规则，逗号分隔（如 "typo,pangu-space"）；用 "-" 前缀排除
        （如 "-dup-punct"）；留空表示默认规则集（18 条里除 quote-switch 之外的全部）。
    severity: 只看某个级别，逗号分隔，可选 error / warn / style。
    limit: 最多列出多少条问题，默认 30。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
limitNo
rulesNo
severityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does it well: it explicitly states the operation is read-only, will not modify anything, and automatically skips code blocks, inline code, URLs, emails, HTML tags, and formulas. It also reveals default rule behavior and the default issue limit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and read-only guarantee, then presents parameters as a clean Args block with concrete examples. Every sentence adds useful information, and the formatting makes scanning easy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter tool with no annotations, the description covers required and optional parameters, defaults, allowed severity values, rule syntax, and ignored content. Since an output schema exists, there is no need to explain return values; what an agent needs to invoke the tool correctly is present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description compensates thoroughly. For each parameter it adds meaning absent from the schema: text accepts Markdown and defines skipped elements; rules documents comma-separated inclusion, '-' prefix exclusion, and the default set; severity enumerates valid values; limit states default 30.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('检查') and resource ('中文文本'), and enumerates the exact scope: 排版、标点、常见错别字、专有名词大小写. It also notes the operation is read-only, which distinguishes it from sibling fix_text without requiring schema inspection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description establishes a clear context—this is a read-only checker that does not modify text—so an agent can infer it is for analysis rather than fixing. However, it never explicitly names or contrasts the sibling tools (fix_text, count_text, list_rules) or states conditions for choosing one over another; guidance remains implied.

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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