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Wanhe Compliance — Chinese Content Compliance Checker

check_content

检查一段中文内容的广告法合规风险,返回逐条问题清单:问题类型 / 原文位置 / 命中文本 / 依据法条 / 修改建议。覆盖:绝对化用语(第9条)、医疗功效与疾病名(第17/18条)、保健功效、违规用语(免检/特供)、食品绝对化、虚假表述等高频规则。调用规则:同输入必同输出;未发现问题时明确说明,不虚报。限制:单次 2000 字符;本会话共 30 次。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes要检查的中文内容(≤2000 字符)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses determinism ('same input same output'), honest reporting behavior ('explicitly state when nothing found, no false reports'), and a per-session rate limit (30 calls) plus input size cap. These are meaningful operational traits beyond the schema.

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

Conciseness4/5

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

The action, output shape, coverage, rules, and limits are all present and reasonably front-loaded, with no filler sentences. It is dense but every clause carries information; the coverage enumeration is somewhat long but justified by scope definition.

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

Completeness4/5

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

With no output schema, the description compensates by describing the return format (per-item list of problem type / position / matched text / legal basis / revision suggestion), and covers limits and determinism. For a single-parameter read-only analysis tool this is nearly complete, missing only explicit sibling routing.

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

Parameters3/5

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

There is a single parameter with 100% schema description coverage, so the schema already documents the '≤2000 characters' text input. The description restates the 2000-char cap but adds no syntax, format, or encoding detail beyond what the schema provides, so the baseline 3 applies.

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

Purpose4/5

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

The description states a specific verb and resource — checking Chinese content for advertising-law compliance — and enumerates the exact rule categories covered (Article 9 absolute terms, Articles 17/18 medical claims, etc.), making the scope unmistakable. It does not explicitly name or contrast with the sibling check_ai_label, but the highly specific domain makes overlap implausible.

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?

It gives useful calling context (deterministic output, no false positives when nothing is found) and hard limits (2000 chars, 30 calls/session), which guide correct invocation. However, it never says when to choose this tool over the sibling check_ai_label or when-not to use it, leaving alternative selection to inference.

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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