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savantcat

savantcat-answers

Official

self_check_list

Read-onlyIdempotent

Check if your AI customer service meets China's GB/T 47746-2026 standard by retrieving a 61-item self-assessment checklist with clause-level requirements and fixes.

Instructions

取 GB/T 47746-2026 的自查清单:企业对照检查自家 AI 客服是否达标。

返回**清单本体**(61 项:id / 条款 / 等级 / 是否一票项 / 要求 / 怎么补),
外加一票项速查与用法;「61 项怎么来的」那篇解释文随附在 explainer 字段。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds the content shape (61 items with id/条款/等级/一票项/要求/怎么补, plus a 一票项速查 and an explainer field), which is useful but largely restates return content that the output schema already carries.

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?

Front-loads the core purpose and the identity of the standard in the first clause, then enumerates the payload. Some of the bolded return-value detail could be trimmed since an output schema exists, but it is not bloated.

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 zero-parameter, read-only retrieval with an output schema and full annotations, the description supplies enough context (what the list is, what it contains, the explainer field) for correct invocation. The only gap is the absence of explicit sibling routing to standard_info/get_answer.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4; there is no parameter meaning the description needs to add, and it does not confuse the reader with any.

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?

States a specific verb+resource ('取 GB/T 47746-2026 的自查清单') and the user's goal (企业对照检查 AI 客服是否达标), so an agent knows exactly what it retrieves. It does not explicitly distinguish itself from siblings like standard_info, which could plausibly also cover the standard.

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 gives clear implied context — companies using it to self-assess compliance — but offers no explicit when-to-use vs when-not, and never names the sibling tools (get_answer, standard_info, etc.) as alternatives. Usage is inferable but not spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.