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audit_cn_citability

Read-onlyIdempotent

Audit whether a website or page can be crawled, parsed, and cited by Chinese AI search platforms like Doubao and DeepSeek. Get a 0-100 score, A-F grade, and prioritized fixes for better AI visibility.

Instructions

审计一个网站/页面能否被中文 AI 搜索（豆包、DeepSeek、文心、Kimi 等）抓取、解析与引用。

一次抓取完成六层检查：可抓取（含中国爬虫矩阵与边缘层拦截实测）、可解析、可引用、
实体一致、分发、可信可自验；返回 0-100 分与 A-F 等级、逐项证据、优先修复清单。
用途场景：客户站点体检、上线前自检；传 compare_with 可做竞品对比（逐层与逐项差异）。
注意：只做确定性检查，不调用大模型；评分口径见 scoring_version。

Input Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes
`include_raw`	No
`compare_with`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 4, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the readOnlyHint/idempotentHint annotations, the description discloses that a single fetch performs six deterministic checks, includes real interception testing of Chinese crawler matrices, intentionally does not call an LLM, and reports according to scoring_version. These are useful behavioral traits not inferable from annotations alone.

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?

Compact, well-structured paragraphs front-load the core action, then layers, output, use cases, and caveats. No fluff; every clause adds operational detail.

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?

For a complex audit tool, the description covers the six check layers, the 0-100/A-F output, evidence and priority-fix list, compare_with mode, determinism/no-LLM behavior, and scoring-version reference. The only notable gaps are include_raw semantics and sibling-tool routing, which keep it from being fully complete.

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?

Schema description coverage is 0%, so the description carries the burden. It gives meaning to url (the site/page being audited) and compare_with ('传 compare_with 可做竞品对比（逐层与逐项差异）'), but leaves include_raw entirely undocumented, so an agent cannot tell whether raw means raw evidence, raw HTML, or raw response scores.

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 opens with a concrete verb-resource pair—'审计一个网站/页面能否被中文 AI 搜索…抓取、解析与引用'—and enumerates six specific check layers plus the score/grade output. This clearly differentiates it from inspection-style siblings like plan_fixes and score_visibility, even though those names aren't explicitly mentioned.

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

Usage Guidelines4/5

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

States explicit use scenarios ('客户站点体检、上线前自检') and describes the compare_with competitive-comparison mode. It doesn't name sibling tools as alternatives or list when-not-to-use cases, so it stops at clear context without exclusions.

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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