framesail

Create project

create_project

Create a project. The description (the video concept/topic) seeds script generation, so write a meaningful one. Pass video_format='portrait' for a vertical video — every shot, overlay, and the export are then composed for a 9:16 frame. The response's web_url is the project's page in the web app — share it so the user can follow along.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`title`	Yes	Project title shown in the app
`channel_id`	Yes	ID of the channel to create the project in, from list_channels or create_channel
`description`	No	The video concept/topic; seeds script generation, so make it specific and meaningful
`video_format`	No	Output frame shape: 'landscape' (16:9, the default — YouTube and long-form) or 'portrait' (9:16 — Shorts, Reels, TikTok). Fixed once the storyboard is generated, so pick it up front.	landscape

TDQS

A4.2/5.0

Behavior4/5

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

The description discloses key behavioral traits beyond the annotations (which are all false): the description seeds script generation, video_format='portrait' composes everything for 9:16, and the response includes a shareable web_url. This provides useful context without contradicting the annotations.

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?

Three sentences deliver purpose, parameter advice, and response usage with no filler. Every sentence earns its place and the key information is front-loaded in the first sentence.

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 no output schema, the description appropriately highlights the web_url return value. It also covers the behavioral consequences of the description and video_format parameters. It relies on the schema for channel_id sourcing, which is acceptable, but could have mentioned prerequisites in the description itself.

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?

Although the schema already documents all 4 parameters (100% coverage), the description adds practical semantics: write a meaningful description because it seeds script generation, and the video_format choice is fixed once the storyboard is generated. This goes beyond the schema descriptions.

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 opens with a clear verb+resource: 'Create a project.' It then elaborates on the implications of the description parameter (seeds script generation) and the video_format parameter, which clearly distinguishes it from siblings like update_project, delete_project, and get_project.

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

Usage Guidelines3/5

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

The description implicitly indicates this is the entry point for a new project by explaining that the description seeds script generation and that video_format must be chosen up front. However, it does not explicitly contrast with alternatives like update_project or generate_script, so the guidance remains implied rather than explicit.

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

A3.6/5.0

Disambiguation3/5

Several tool families overlap in purpose, such as await_jobs/get_workflow_status/get_pipeline_progress, update_segment_content/update_segment_prompts, director_note/project_director_note, and scan_script/rescan_voice_blocks. The descriptions do a good job distinguishing them, but an agent must read carefully to avoid misselection, and there are more than a couple of confusable pairs.

Naming Consistency4/5

The set overwhelmingly follows a verb_noun snake_case convention with clear prefixes like get_, list_, set_, update_, create_, and delete_. Minor exceptions such as director_note, project_director_note, browse_audio_library, and whoami keep it from being perfectly consistent.

Tool Count1/5

At 72 tools, this is far beyond the 50+ extreme range and creates a heavy navigation burden for an agent. Even though the pipeline is complex, this many tools is not well-scoped for an MCP surface.

Completeness4/5

The surface covers the full script-to-export pipeline: styles, assets, voices, storyboards, segments, scenes, and rendering all have substantial lifecycle support. Some gaps exist—no delete_channel, delete_segment, delete_voice_block, or delete_provider_key—but most missing operations can be worked around through existing tools.

Resources

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