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sanhao-global-experts

ppt-beautify

Save hours every week. This ppt beautify toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.

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 provided, so the description must carry the behavioral burden, but it mainly offers marketing claims. It does not disclose what the tool returns, whether it produces a prompt, a playbook, a file, or analysis, nor does it describe limitations or expected inputs.

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?

The description is short but front-loaded with fluff such as “Save hours every week” rather than a clear purpose. Marketing phrasing like “battle-tested prompt and operating playbook” reduces clarity instead of earning its place.

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 tool named ppt-beautify with sibling variants and no output schema, the description should explain the beautification workflow, expected output, and relationship to alternatives. Instead it provides a vague restaurant/brand-growth framing that leaves the tool’s actual behavior unclear.

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 has 100% description coverage for the single optional “query” parameter, so the baseline is 3. The description adds no additional meaning 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 largely restates the name with marketing language (“This ppt beautify toolkit”) and does not clearly state what operation the tool performs. It mentions a “prompt and operating playbook for restaurant/brand growth,” which is vague and does not clarify PPT beautification or distinguish it from sibling tools such as ppt-beautify-lite or ppt-beautify-pro.

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?

The description gives no when-to-use guidance, prerequisites, exclusions, or alternatives. “No setup, works in any LLM chatbot” is a deployment claim, not guidance for choosing this tool over the many sibling PPT and brand-growth 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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