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Export project

export_project

Kick off a video export of the project. Returns immediately with an export_id; the export pipeline runs in the background. The user can find the rendered video in the Exports tab in the editor.

Defaults: 1080p / 30fps / no captions / English. Pass overrides only when needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fpsNoFrames per second (default 30)
captionsNoBurn subtitles into the video (default false)
project_idYesThe project ID to export
resolutionNoOutput resolution (default 1080p)

TDQS

A4.4/5.0
Behavior4/5

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

Annotations indicate no read-only or destructive behavior, and the description adds value by clarifying the asynchronous nature ('returns immediately... background'), the defaults for resolution, fps, captions, and language, and where the user finds the result. This goes beyond annotations to explain the background pipeline behavior.

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 extremely concise—two short sentences plus a defaults summary. Each sentence provides essential information (async behavior, where to find output, defaults, guidance on overrides) with no filler. It is front-loaded with the main action and outcome.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters and no output schema, the description covers the core behavior, defaults, and async feedback mechanism. It could mention what happens on error (e.g., if export fails) or the output schema (export_id type), but this is minor. The context is mostly complete for a tool with 100% schema coverage.

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 value by stating defaults for all optional parameters (1080p, 30fps, no captions) and advises passing overrides only when needed, which prevents agents from redundantly specifying defaults. It also mentions language (English) as a hidden default, which is not in the schema.

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 it kicks off a video export of a project, distinguishing it from other tools like 'get_project' or 'update_project'. It uses specific verbs ('kick off') and resources ('video export of the project'), and mentions the asynchronous return of an 'export_id', which differentiates it from synchronous operations.

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 provides clear context on when to use this tool (to start an export) and notes that overrides are only needed for non-default values. However, it does not explicitly mention when not to use it or alternatives among the 39 sibling tools, such as 'estimate_duration' which might be used first to check feasibility.

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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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is notable overlap between remove_elements and remove_from_project(target='element'), which both remove elements from a clip. This duplication could cause an agent to misselect. Otherwise, tools like add_clips, add_elements, add_audio, and analyze_audio are well-differentiated.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern (e.g., add_clips, create_project, get_clip, update_elements). There are no camelCase or mixed conventions. Even compound names like voiceover_batch and auto_sync fit the pattern. This makes the tool set predictable for an agent.

Tool Count2/5

With 40 tools, the set is significantly larger than the 3-15 range that typically earns its place. While the domain of video creation is broad, several tools seem redundant (remove_elements vs remove_from_project) or narrowly scoped (get_design_guide, get_element_schema), inflating the count. The number feels heavy for the apparent scope.

Completeness4/5

The tool surface covers most lifecycle operations: create, read, update, delete for projects, clips, elements, audio, articles, and clueprints. Minor gaps exist, such as no explicit tool to delete a voiceover (only mute via update_clips) and no folder management beyond listing. Overall, agents can accomplish full workflows with few workarounds.