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generate_video

DestructiveIdempotent

Animate one uploaded photo. This spends credits. Get a quote first and confirm cost and visibility with the user. Retry with the same request_id and inputs.

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": {
      "asset_id": "<asset_id>",
      "prompt": "<prompt>",
      "is_public": "<is_public>",
      "expected_credits": "<expected_credits>",
      "request_id": "<request_id>"
    },
    "name": "generate_video"
  }
}

Input Schema

NameRequiredDescriptionDefault
promptYes
asset_idYes
is_publicYesUse true for public output. Private output requires paid access.
request_idYes
expected_creditsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already flag this as non-read-only, destructive, open-world and idempotent; the description adds the material fact that it spends credits and requires user confirmation of cost and visibility. It also explains the retry mechanism (same request_id and inputs), which gives the idempotentHint practical meaning. It stops short of saying what a failed or partial run consumes or what is returned.

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

Conciseness5/5

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

Four short sentences, each load-bearing: action, cost warning, required precondition, retry semantics. The cost warning is front-loaded right after the action, which is the right ordering for a paid operation.

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

Completeness3/5

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

With five required parameters, no output schema, and a destructive/paid operation, the description covers the workflow but not the failure and result story. It never says what comes back (a job or asset id), what happens if credits are insufficient, or what expected_credits must match, so an agent cannot fully predict the outcome of a call.

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 only 20%, so the description should carry more weight than it does. It adds real meaning for request_id (retry key) and is_public (visibility must be confirmed with the user), but expected_credits, asset_id and prompt get no explanation in either the description or the schema, leaving a required cost-bearing parameter unexplained.

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?

"Animate one uploaded photo" gives a specific verb (animate), a specific resource (a single uploaded photo), and an explicit cardinality limit. It implicitly separates itself from quote_generation by instructing the agent to get a quote first, though it never names that sibling directly.

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?

It prescribes a concrete ordering (quote first, then generate) and a mandatory human checkpoint (confirm cost and visibility with the user) before spending. That is explicit when-to-use and prerequisite guidance rather than implied usage.

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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