Skip to main content
Glama

ae_build_youtube_edit

Analyze a transcript to plan or build a YouTube edit in After Effects. Choose clean, retention, or story mode; get an editorial plan for approval or generate the edit directly.

Instructions

Analyze a transcript and optionally build a YouTube edit in After Effects. In approval mode it returns a full editorial plan until approved=true; in autonomous mode it builds immediately. Use clean, retention, or story mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo
pathNoAbsolute media path to import
approvedNoRequired in approval mode to mutate AE
comp_nameNoYouTube Edit
frameRateNo
review_idNoApproved review item id; alternative to approved=true
transcriptNo
footage_nameNo
transcript_pathNo
Behavior3/5

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

With no annotations provided, the description carries the full burden. It usefully reveals that approval mode returns an editorial plan until approved=true and that autonomous mode builds immediately. However, it does not disclose mutation side effects, required project state, or what happens to existing After Effects compositions.

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 short sentences front-load the core action, then add behavior and mode options. Every sentence earns its place, and there is no redundant filler.

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

Completeness2/5

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

For a tool with 9 parameters, low schema coverage, no output schema, and no annotations, the description is too thin. It leaves out how inputs are resolved, what output is returned, and what prerequisites are needed before building, making it insufficient for reliable autonomous invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (33%), so the description must compensate. It mentions transcript and the three modes, and it references approval flow, but it does not explain important parameters like comp_name, frameRate, footage_name, transcript_path, or the relationship between transcript and transcript_path. Most parameter meaning is left undefined.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a clear action ('Analyze a transcript and optionally build a YouTube edit in After Effects') with a specific resource and platform. It is understandable on its own, but it does not distinguish itself from closely related sibling tools like ae_build_smart_edit or ae_create_editorial_plan.

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?

It explains approval mode versus autonomous mode and says to use clean, retention, or story mode, which gives context for how to run the tool. However, it does not specify when to prefer this tool over alternative build/planning tools, nor does it give exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HeroicSwan/after-effects-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server