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@runapi.ai/luma-mcp

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modify_video

Create and poll a Luma video modification task on RunAPI using a prompt and source video URL; get task ID, status, and output URLs.

Instructions

Create a Luma task on RunAPI (modify video). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptYesDeclared type: string.
watermarkNoDeclared type: string.
timeout_msNo
callback_urlNoDeclared type: string.
poll_interval_msNo
source_video_urlYesDeclared type: string.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed8 schema fields changedv0.2.0
    • changedInput schema / additionalProperties
      Previous value: -falseNew value: +{}
    • addedInput schema / properties / callback_url / description
      Added value: +"Declared type: string."
    • removedInput schema / properties / model / enum
      Removed value: -[
-  "luma-modify-video"
-]
    • addedInput schema / properties / poll_interval_ms / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / prompt / description
      Added value: +"Declared type: string."
    • addedInput schema / properties / source_video_url / description
      Added value: +"Declared type: string."
    • addedInput schema / properties / timeout_ms / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / watermark / description
      Added value: +"Declared type: string."
  2. Changed5 schema fields changedv0.1.7
    • addedInput schema / properties / callback_url
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / prompt / type
      Added value: +"string"
    • addedInput schema / properties / source_video_url / type
      Added value: +"string"
    • addedInput schema / properties / watermark
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / required
      Added value: +[
+  "prompt",
+  "source_video_url"
+]
  3. First observedv0.1.4

TDQS

C2.8/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose the return shape (task id, status, output URLs), which matters since no output schema exists. However, it omits async/long-running behavior, callback vs polling semantics, cost implications, and whether the task is reversible or consumptive.

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?

Two tight sentences with the action front-loaded and the return values appended. Nothing is wasted, though the content is thin rather than merely concise.

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?

For an async task-creation tool with 8 parameters, no annotations, and no output schema, the description partially compensates by naming the return fields. It still leaves authentication, cost, model selection, and polling behavior unexplained, which is a meaningful gap.

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

Parameters2/5

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

The description adds no meaning for any of the 8 parameters. Schema coverage of 75% is inflated by placeholder descriptions like 'Declared type: string', so watermark, callback_url, model, timeout_ms, and poll_interval_ms are effectively undocumented in both places.

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

Purpose3/5

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

States a verb+resource (create a Luma task for modifying video) and names the backend, but 'modify video' is vague about what transformation actually occurs. It does not distinguish itself from the sibling get_task, which is the natural follow-up for the returned task id.

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?

There is no guidance on when to call this versus get_task, check_pricing, or login, nor on prerequisites such as needing an authenticated session. The `wait` parameter implies synchronous polling but the description never explains when to set it.

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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