video_editor_create_project
Create an AI Studio video project. Returns project_id.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| description | No | ||
| aspect_ratio | No |
Create an AI Studio video project. Returns project_id.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| description | No | ||
| aspect_ratio | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only destructiveHint=false, so the description is responsible for additional behavioral context. It adds the return value 'Returns project_id,' which is a useful behavioral disclosure not present in the schema. However, it does not mention side effects (e.g., whether a project is persisted, whether it can be modified later, or any rate limits). This falls short of rich behavioral transparency, but the return-value note earns a middle score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, but this is under-specification rather than appropriate conciseness. It front-loads the action correctly, but with three parameters and zero schema descriptions, a single sentence is not appropriately sized. The lack of parameter guidance and usage context makes the brevity counterproductive, so it does not earn credit for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a 3-parameter tool with no schema descriptions, no output schema, and only a bare annotations object, the description is incomplete. It explains the basic action and return value but lacks parameter semantics, usage conditions, and any indication of the project's lifecycle or integration with sibling tools. An agent would be uncertain about how to correctly invoke the tool with meaningful inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for explaining what parameters do. It does not mention 'name', 'description', or 'aspect_ratio' at all. The enum for aspect_ratio is visible in the schema, but the meaning of valid values (e.g., whether they define the canvas or output format) and any default behavior are omitted. This is a significant gap for a tool with three potentially optional parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Create an AI Studio video project.' This clearly differentiates from siblings like video_editor_create_video (creating a video) and video_editor_add_clip (adding content). The resource 'video project' is distinct and the concise phrasing leaves no ambiguity about the tool's core action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no context cues, prerequisites, or exclusions, such as 'use this before adding clips' or 'for an existing project, use video_editor_add_clip instead.' An agent must infer the appropriate usage solely from the tool name, which is insufficient for correct selection among 21 siblings.
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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