aicut

Generate an explainer video

generate_explainer_video

Destructive

CREATES an explainer video: a narrated 9:16 motion-graphics video (animated numbers, cards, callouts, up to six voices, captions), 20 to 180 seconds, from the script JSON you write. READ get_recipe explainer BEFORE THE FIRST CALL: the format, rules, pictures and prices. AFTER: one call makes the finished video, no render step. Wait with wait_for_generation; when terminal get_video carries the file url. A failed explainer is refunded and has no retry. SPENDS TOKENS: price with estimate_only: true, state the price in the same message as your ask, wait for a go naming THIS purchase (SPENDING RULES: get_recipe spending-rules). idempotency_key: IDEMPOTENCY (this server's instructions).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "script": "<script>"
    },
    "name": "generate_explainer_video"
  }
}

Input Schema

Name	Required	Description
`script`	Yes	The script as a JSON object. Format, limits, voices and examples: `get_recipe` `explainer`. A script that breaks a rule is refused uncharged, naming the field.
`estimate_only`	No	Price only; creates nothing.
`idempotency_key`	No	Retry key (IDEMPOTENCY).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 3, 2026
- changedInput schema / properties / idempotency_key / description
```
Previous value: -"Retry-safety key (IDEMPOTENCY)."New value: +"Retry key (IDEMPOTENCY)."
```
AddedNov 3, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Goes well beyond the annotations by disclosing token spend, the need to state price before purchase, refund behavior for failed explainers, lack of retry, refusal of invalid scripts without charge, and absence of a separate render step. These are material behavioral traits for a destructive, open-world generation tool.

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 dense and front-loads the creation purpose, then follows the workflow in order. Almost every clause earns its place, though the ALL-CAPS directives and repeated recipe references make it slightly harder to scan than ideal.

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

Completeness5/5

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

For a complex, token-spending generation tool with no output schema, the description covers preconditions, pricing, approval, execution, waiting, retrieval, failure refunds, and idempotency. An agent has enough information to invoke it correctly and safely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds meaningful semantics: script format rules live in get_recipe explainer, estimate_only is for pricing without creation, and idempotency_key follows the server's idempotency instructions. The nested script object has no enumerated properties, so pointing to the recipe is especially useful.

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

Purpose5/5

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

States a specific verb and resource: creates a narrated 9:16 explainer video from a script JSON, with duration and feature scope. It distinguishes this from sibling generation tools by naming the exact output format and the recipe needed, so an agent can tell it apart from generate_video or generate_story_video.

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

Usage Guidelines5/5

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

Gives explicit sequencing: read get_recipe explainer before the first call, price with estimate_only true, wait with wait_for_generation, then retrieve the file with get_video. It also states the spending approval requirement and idempotency behavior, leaving little inference about when and how to invoke it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All aicut tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.