Save hours every week. This short video script toolkit gives you a battle-tested prompt and operating playbook for restaurant/brand growth. No setup, works in any LLM chatbot.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Optional user query to scope the analysis. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden and largely drops it. It never says what the invocation returns (a ready script? a prompt the caller pastes elsewhere?), whether any external state or auth is touched, or how long output typically is; "battle-tested prompt and operating playbook" is the only hint at the return shape and it is ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, but all three are marketing copy ("Save hours every week," "battle-tested," "No setup") rather than a front-loaded statement of function. Brevity here is under-specification, not conciseness; the first sentence in particular earns no place in a tool definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is low-complexity (one optional param, no output schema), so the description should at minimum state what the caller receives and who the audience is. It gestures at restaurant/brand growth but leaves the return contract and the distinction from a crowded field of script-generation siblings entirely unaddressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 schema already explains its meaning. The description adds nothing about how scoping the analysis changes output, which is the baseline-3 case where structured fields do the work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The text calls itself a "short video script toolkit" with a "prompt and operating playbook for restaurant/brand growth," which restates the name and adds a domain hint, but supplies no verb describing what invoking the tool actually does (generate a script? return a prompt template? score one?). Against ~20 near-identical siblings such as short-video-script-pro, short-video-script-master, dy-script-kit, and video-shot-script-master, there is no differentiation whatsoever.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use guidance, no preconditions, and no named alternative. "No setup, works in any LLM chatbot" is a sales claim rather than routing information, and it arguably misdescribes an MCP tool as a chatbot prompt, leaving the agent unable to choose this over any sibling script 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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