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sanhao-global-experts

review-summary-tool

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use review summary tool workflow - no prompt engineering needed. Ships as a full prompt kit with step-by-step instructions and a 30-day support promise.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.8/5.0
Behavior1/5

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

No annotations are supplied, so the description must carry the full burden of behavioral disclosure, and it does not. Nothing is said about whether the tool reads or writes, what it produces (a summary? a prompt kit? instructions?), how long output is, or what the optional query does; the "ships as a full prompt kit" claim is about the product bundle, not tool behavior.

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

Conciseness2/5

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

Three sentences, most of them marketing padding ("no prompt engineering needed," "30-day support promise"), and the only capability-bearing phrase is buried in the middle. The defining information is absent while low-value promotional copy fills the space.

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

Completeness2/5

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

For a one-optional-parameter tool with no output schema, the description still needs to state what the output looks like and when to reach for it; it states neither. The product-pitch sentences do not compensate, leaving the definition materially incomplete for an agent.

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?

The single optional `query` parameter is fully documented in the schema (100% coverage), so the schema does the work and the baseline of 3 applies. The description adds nothing about scoping or format beyond the schema, but the coverage is high, so no penalty is warranted.

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

Purpose2/5

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

The description calls itself an "AI-powered restaurant & brand intelligence pack" and a "review summary tool workflow," which mostly restates the tool name in marketing language rather than naming a concrete verb and resource combination. It never says what the tool actually does with a query, what it returns, or how it differs from the many sibling review tools (review-audit-tool, review-reply-tool, review-check-tool).

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

Usage Guidelines1/5

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

There is no when-to-use guidance, no when-not-to-use guidance, and no sibling alternative named. Phrases like "no prompt engineering needed" and "30-day support promise" are purchase incentives, not invocation guidance, so an agent has nothing to route on.

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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