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Upload a video for reconstruction

workspace_upload_video

Upload a local video file to start a 3D reconstruction job and receive an immediate job ID for tracking. Ideal for turning video captures into scannable scenes.

Instructions

Upload a local video file (.mp4/.mov/.avi/.mkv/.webm, ≤1 GB) into the account and start a reconstruction job. Returns {job_id, scan_id} immediately (202); follow with workspace_job_wait. The scene appears in workspace_list_scenes when the job is done.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute path of the local video file
labelNoHuman label for the scene (X-Scene-Label)
sourceNoSet ONLY for depth-camera footage (X-Demo-Source provenance tag)
Install Server

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden and does it well. It discloses that the upload starts an asynchronous reconstruction job, returns immediately with a 202, and that the scene only appears later. It also specifies file format and size constraints, which is useful for anticipating failures.

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 tight sentences with no fluff. The core action, constraints, immediate return value, and follow-up steps are all packed efficiently into a compact description that front-loads the most important information.

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?

For a tool with no annotations and no output schema, the description is remarkably complete: it explains the input constraints, the immediate return payload, the next step (workspace_job_wait), and the eventual observable outcome (scene in workspace_list_scenes). An agent has enough context to invoke it correctly and know what happens afterward.

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 the baseline is 3. The description adds value by stating the acceptable video formats and the 1 GB limit for the path parameter, but does not go beyond the schema in explaining label or source semantics. Baseline is appropriate.

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 clearly states the specific action: uploading a local video file into the account and starting a reconstruction job. It distinguishes this tool from its siblings like workspace_upload_recording and workspace_upload_splat by explicitly focusing on video files and reconstruction, including supported formats and size limits.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context on how to use the tool: upload a video, receive job_id and scan_id immediately, then follow with workspace_job_wait, and later check workspace_list_scenes. It does not explicitly mention when to use this tool over other upload variants, but the sequencing and expected workflow are clear.

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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