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sanhao-global-experts

stock-board-tool

Turn expertise into output. This stock board tool prompt pack helps restaurant and brand teams produce professional results in minutes. Includes the complete prompt, usage guide, and edge-case handling.

Input Schema

NameRequiredDescriptionDefault
queryNoOptional user query to scope the analysis.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.1/5.0
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 disclosure burden, yet it says nothing about whether the tool is read-only, what it returns, or what permissions it needs. The mention of 'complete prompt, usage guide, and edge-case handling' hints at the payload contents, but that is a sales claim rather than a behavioral trait 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 of which none are front-loaded with the tool's actual function; 'Turn expertise into output' and 'produce professional results in minutes' are filler that carry no operational information. The text is short but under-specified rather than concise.

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 no statement of what the tool produces, an agent has no basis to decide when to call it or what to expect back. For a tool that supposedly generates a substantive artifact, the description is critically 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?

There is a single optional parameter ('query') with 100% schema description coverage, so the schema already explains it. The description adds no meaning about how the query scopes the analysis, which is the relevant gap, but baseline 3 applies when the schema does the documentation work.

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 never states a verb+resource for the tool itself; it describes a 'prompt pack' that 'helps restaurant and brand teams produce professional results in minutes.' Nothing indicates what a 'stock board' actually is or how it differs from stock-analyze-tool, stock-diag-tool, or stock-formula-tool. This is marketing copy that restates the title rather than defining the operation.

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 and no mention of alternatives among the many stock-* and board-* siblings. The only audience signal is 'restaurant and brand teams,' which does not tell an agent when this tool is the right choice over stock-analyze-tool or stock-tpl-tool.

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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