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sanhao-global-experts

doc-convert-pro

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use doc convert pro 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

C2.2/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden and does not meet it. 'Ships as a full prompt kit with step-by-step instructions and a 30-day support promise' is sales copy rather than disclosure of what the tool returns, whether it mutates anything, or how the optional query scopes the analysis.

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 of promotional language, with the '30-day support promise' consuming space that should describe the tool's actual function. The content that is present is front-loaded on the wrong subject (restaurant/brand intelligence) rather than on document conversion.

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?

The tool is simple (one optional param, no output schema, no annotations), so the description could be fully adequate in one sentence, yet it leaves the core question unanswered: what does the agent get back when it calls this, and what does 'doc convert' mean here. The domain mismatch with the name makes the definition actively incomplete.

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 schema documents the single optional 'query' parameter at 100% coverage, so the baseline is 3 regardless of the description. The description adds nothing about how a query changes the generated output, but it does not need to given full schema coverage.

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 opens with 'AI-powered restaurant & brand intelligence pack', which has nothing to do with the name doc-convert-pro, and then claims it will 'generate a ready-to-use doc convert pro workflow'. It never states what operation the tool actually performs on a document, so an agent cannot distinguish it from the many other 'pro' workflow-pack siblings in the list.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no named alternative among the hundreds of siblings. The only hint is the marketing claim 'no prompt engineering needed', which implies a user who wants a packaged workflow but gives no selection 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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