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sanhao-global-experts

xhs-case-kit

AI-powered restaurant & brand intelligence pack. Instantly generate a ready-to-use xhs case kit 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, yet it discloses almost nothing operationally: it does not say what the tool returns, whether it generates text or a plan, whether it writes anything, or how long output is. "Ships as a full prompt kit with step-by-step instructions and a 30-day support promise" is commercial copy rather than behavioral context an agent can act on.

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, none of which is front-loaded with a concrete capability statement; the opening is a category slogan and the closing ("30-day support promise") is pure sales copy that consumes space without informing invocation. Signal-to-filler ratio is poor for a definition of this length.

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 zero-required-param generator with no annotations and no output schema, the description should at minimum say what artifact is produced and what its sections look like. It instead describes a purchasable product bundle, leaving the agent unable to predict the result of calling it.

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 optional `query` parameter is documented in the schema as a scoping input, so the baseline is 3. The description adds nothing about how a query changes the output 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?

"Generate a ready-to-use xhs case kit workflow" mostly restates the tool name (xhs-case-kit) without explaining what a case kit actually is — a case-study post template, a workflow, or a research packet. The lead sentence, "AI-powered restaurant & brand intelligence pack," actively points in a different direction and gives no differentiation from close siblings such as xhs-template-kit, xhs-story-kit, or xhs-review-kit.

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 statement of when to use this tool, what input scenario suits it, or which sibling to pick instead (e.g., xhs-template-kit vs. xhs-sop-kit vs. xhs-column-kit). Usage can only be inferred from the name, and the marketing framing ("no prompt engineering needed") conveys 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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