Skip to main content
Glama

Gemini Generate Video Tool

gemini_generate_video_tool

Create AI videos from text prompts via Veo, returning an operation ID to poll for results. Generate video clips programmatically with optional negative prompts.

Instructions

Generate a video using Veo. Returns an operation ID to poll.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the video to generate.
_aspect_ratioNoVideo aspect ratio (currently unused).16:9
negative_promptNoWhat to avoid in the video.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden. It usefully discloses the asynchronous contract (returns an operation ID rather than a finished video), but omits generation latency, whether the operation is billable, or any limits on prompt length or output duration. The async disclosure is real added value, but substantial behavioral gaps remain.

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?

Two terse sentences, front-loaded with the action and followed immediately by the return contract. No filler, no repetition of the title.

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?

An output schema exists, so return values need not be explained, and the description appropriately just flags the operation ID. However, for an async generation tool the description should point at the companion polling tool (gemini_check_video_tool) to complete the workflow; without it the agent must infer the next step.

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 prompt, negative_prompt, and the defaulted _aspect_ratio are already documented in the schema. The description adds no format, length, or stylistic guidance for the prompt beyond what the schema says. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb and resource ('Generate a video using Veo') and distinguishes itself from the many image-generation siblings by naming the modality. It also notes the async return shape ('operation ID to poll'), which is more than a tautology. It stops short of naming the sibling tool an agent should call to poll.

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 when-to-use guidance: nothing tells the agent when to pick this over gemini_generate_image_tool or gemini_imagen_generate_tool, nor the prerequisites for a valid prompt. The only implied usage cue is that the result must be polled, but the tool to poll with is not identified.

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