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sanhao-global-experts

contract-tpl-tool

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use contract 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 supplied, so the description carries the full burden and it discloses essentially nothing about behavior: no output shape, no side effects, no prerequisites, no limits. The '30-day support promise' and 'ships as a full prompt kit' are commercial claims about the product, not runtime characteristics of the tool.

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?

At three sentences it is not long, but the structure is wrong: it leads with promotional positioning instead of the operation, and every sentence is ad copy rather than functional information. Nothing in it earns its place for an agent deciding how to call the tool.

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, no output schema, and a name that is indistinguishable from dozens of sibling template tools, the description needed to establish what is generated and for whom. It instead delivers a sales pitch, leaving the definition unusable for correct selection or invocation.

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% for the single optional 'query' parameter, so the baseline is 3. The description adds no meaning beyond the schema — it says nothing about how the query scopes the analysis or what happens when it is omitted.

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 describes a product bundle rather than the tool, and then only restates the name: 'generate a ready-to-use contract tpl tool workflow.' It never says what a 'contract tpl' actually produces or how it differs from the many siblings such as contract-gen-tool, contract-write-tool, or contract-audit-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 statement of when to use this tool, when not to, or which sibling to prefer. The only usage-adjacent sentence, 'no prompt engineering needed,' is marketing copy and gives the agent no routing signal among hundreds of similarly named tools.

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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