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x402vid AI Intelligence & Channel Growth for YouTube Videos

Shorts Script Writer

shorts_to_script
Read-only

Shorts script writer: hook, beats, CTA from a topic (fast, pure AI).

Closes the loop with shorts_intelligence: winning patterns in, plug-and-play shoot sheet out (words + visuals + shot list).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesVideo topic for the script
x_paymentNoBase64 x402 payment payload (required — pass the X-PAYMENT value as an argument over MCP)
hook_styleNoOptional hook flavor (e.g. vs-battle, fear, curiosity)
duration_secsNoTarget length 15-90s (default 30)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds some behavioral context—'fast, pure AI' and 'words + visuals + shot list'—which clarifies the nature and shape of output. It does not contradict the annotations, but it also doesn't disclose details like authentication or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact at two sentences with the core purpose front-loaded. The second sentence adds workflow context. Minor promotional phrasing like 'fast, pure AI' and 'winning patterns in, plug-and-play shoot sheet out' could be tighter, but there is little redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, rich annotations, and a fully documented input schema, the description covers the essential workflow: turning a topic and winning patterns into a script with visuals and shot list. It does not mention the required x_payment payload, but that is clearly described in the schema. Overall, the description is sufficient for an agent to understand the tool's role.

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%, so the schema already documents topic, x_payment, hook_style, and duration_secs with helpful descriptions. The tool description mentions 'from a topic' and output format but adds no meaning for the parameters themselves, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Shorts script writer: hook, beats, CTA from a topic' identifies both the resource (a short video script) and the core deliverable (hook, beats, CTA). It references shorts_intelligence for workflow context, which helps distinguish it from other content tools, though it doesn't explicitly name a sibling alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Closes the loop with shorts_intelligence' and 'winning patterns in, plug-and-play shoot sheet out' imply that this tool is meant to be used after shorts_intelligence, using pattern data to generate a script. This is a useful context signal but does not explicitly state when to use it versus alternatives or when not to use it, so the usage guidance remains largely implied.

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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