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video_editor_request_upload

Get a PRESIGNED upload URL for a large local file — no size limit, no base64. Returns { upload_url, file_url }. Steps: (1) call this with filename + content_type; (2) HTTP PUT the raw file bytes to upload_url (header Content-Type: ); (3) call video_editor_add_reference(project_id, url=file_url) to register it in the library, then video_editor_add_clip to place it. Use this instead of video_editor_upload_file whenever a file may exceed a few MB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYesFile name incl. extension, e.g. "scene.mp4".
content_typeNoMIME type, e.g. video/mp4, image/png, audio/wav.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (only destructiveHint=false), the description discloses the full behavioral contract: the returned object shape, the requirement to HTTP PUT raw bytes, the matching Content-Type header, and the follow-up registration steps. It also clarifies key traits like 'no size limit' and 'no base64,' which are not visible from the schema or annotations. This is exemplary transparency for a tool with minimal annotation coverage.

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?

The description is compact and front-loaded with the core purpose and return format, then gives a clear numbered sequence and an explicit alternative. Every sentence adds information; there is no filler or repetition of the schema.

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?

Despite having no output schema, the description explicitly lists the returned keys and all follow-up steps needed to use the uploaded file. It covers the complete workflow, the alternative tool, and the practical size threshold for selection. Nothing essential is missing for an agent to invoke and integrate this tool correctly.

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. The description adds extra meaning by saying to call with filename + content_type and by specifying that the content_type must be reused in the HTTP PUT header. This goes slightly beyond the schema's MIME-type example, earning a 4.

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?

The description states a specific action and resource: getting a presigned upload URL for a large local file. It explicitly distinguishes itself from the sibling video_editor_upload_file by referencing size limits and base64, and it names the returned fields. An agent can confidently identify what this tool does without ambiguity.

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?

The description gives explicit when-to-use guidance: use this instead of video_editor_upload_file whenever a file may exceed a few MB. It also provides a numbered workflow connecting this tool to video_editor_add_reference and video_editor_add_clip, so the agent knows the expected sequence. This is strong routing and usage context.

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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