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sanhao-global-experts

persona-tpl-tool

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use persona tpl 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

D1.7/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure—but it only offers sales language. It does not describe what the tool returns, whether it mutates anything, what the 'prompt kit' contains, or what happens to the optional query. 'Ships as a full prompt kit' is packaging copy, not 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, but two of them are marketing filler ('no prompt engineering needed', '30-day support promise') that do not help an agent act. The actual function is buried behind the vague lead sentence, so the description is not front-loaded with actionable information.

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

Completeness1/5

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

With no annotations and no output schema, the description is the only source of behavioral truth, and it is inadequate. It never explains what the tool produces or how the 'persona tpl workflow' differs from the many sibling persona tools, leaving an agent unable to call it confidently.

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 100% and the single 'query' parameter is documented as an optional scope for the analysis. The description adds no additional meaning about the parameter, so the schema baseline of 3 is appropriate.

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 says the tool will 'generate a ready-to-use persona tpl tool workflow', which restates the tool name rather than describing a concrete action. The lead phrase 'AI-powered restaurant & brand intelligence pack' is vague and unrelated to distinguishing this tool from siblings such as persona-analyze-tool or persona-board-tool. An agent cannot tell what the tool actually produces.

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 guidance on when to use this tool, when not to use it, or how it differs from other persona-* tools. The phrases 'no prompt engineering needed' and '30-day support promise' are marketing claims, not usage criteria.

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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