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publish_restaurant

店主想让 AI 找到、推荐自己的餐厅,或要上架、推广、收录一家店时使用。 发布一家店。必填:name、city、address、cuisine;建议填 lat/lng、hours、人均、intro、sourcing、dishes。 source 说明信息来源:own_store 主人自己的店 / authorized 店主授权 / public_fact 公开事实。 同名且 100 米内(或同一地址)视为重复,会返回已有店铺,请改用 update_restaurant。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeYes
agent_keyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses duplicate detection and the fallback behavior (returns the existing store), and clarifies the source values. However it says nothing about authentication/permissions for the agent_key parameter, whether the write is reversible, or any rate limits, which leaves meaningful behavioral gaps.

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?

Four short lines, each earning its place: usage trigger, core action + required/recommended fields, enum semantics, and the duplicate rule. The usage guidance is front-loaded before the mechanics, which is the right ordering.

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 nested-store publish tool with no annotations and no output schema, the description covers the essentials an agent needs: required fields, recommended fields, source provenance, and duplicate handling that affects the outcome. It falls short only on agent_key auth context and coordinate-system guidance.

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 reported at 0%, but the description lists the required fields (name, city, address, cuisine), enumerates recommended fields (lat/lng, hours, 人均, intro, sourcing, dishes), and explains the source enum semantics. That partly compensates, but the agent_key parameter and the coord_system enum are never addressed in the description.

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+resource (发布一家店 / publish a store) and immediately distinguishes it from the sibling update_restaurant. The opening line also scopes the audience and intent (店主要上架/推广/收录), so an agent can tell it apart from claim_restaurant or update_restaurant without opening a schema.

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

Usage Guidelines5/5

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

It gives an explicit when-to-use trigger in the first sentence and an explicit when-not-to-use rule: if the name collides within 100m or the same address, it is a duplicate and the caller should switch to update_restaurant. This is direct routing to the correct sibling.

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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