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wenyi3370-lgtm

chuance-policy-mcp

verify_law_article_tool

Verify Chinese law article citations by retrieving the authoritative full text and returning the exact article wording and source.

Instructions

核验"《某法》第X条":抓取权威全文,返回该条完整原文 + 来源。

Args: law_title: 法律全名,如 "中华人民共和国个人信息保护法"(书名号可省)。 article_no: 条号,支持中文或数字,如 "五十五"、"55"。

Returns: {matched, law_title, article_label, article_text, source_url, source_title, publish_date, disclaimer, retrieved_at}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
law_titleYes
article_noYes
Install Server

TDQS

A4.1/5.0
Behavior3/5

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 core behavior: fetching authoritative full text and returning the original article text plus source. However, it does not describe failure behavior when the law or article cannot be found, matching nuances for article number formats, or any network/authority dependencies.

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 compact and well structured: a one-sentence purpose, followed by clear Args and Returns sections. Every portion adds useful information, and the purpose is front-loaded.

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 two required parameters and no output schema, the description provides a Returns field list that gives the agent a good sense of the result shape. It is mostly complete, though it could briefly explain the meaning of fields like matched or disclaimer, or describe what happens on no-match, for full completeness.

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?

The schema has 0% description coverage, but the description fully compensates by explaining both parameters in detail: law_title expects the full law name with an example and notes that 书名号 是可省的; article_no supports Chinese or numeric forms with concrete examples. This is exactly the kind of semantic detail an agent needs.

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, '核验', and a specific resource, 《某法》第X条, while making clear the deliverable is the complete article text plus source. This clearly distinguishes it from sibling tools like search_gov_policy, fetch_page_text, and batch_verify_citations, which serve different purposes.

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 implies the tool is for verifying an exact law article by fetching authoritative full text, but it does not explicitly state when to use this tool versus the siblings. It lacks guidance on exclusions such as 'use search_gov_policy for policy search' or 'use batch_verify_citations for multiple citations at once.'

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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