Skip to main content
Glama

contact-sheet

Sample frames across a composition's duration and composite them into a single labeled thumbnail grid for a one-image overview of motion, timing, and easing.

Instructions

See a composition's whole timeline at a glance: render N frames sampled across the duration and composite them into ONE labeled thumbnail grid, returned as a single image. Use this to perceive motion, timing, and easing cheaply (one image instead of many). Select the comp by name or 1-based index, or leave empty for the active comp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compNoComposition name or 1-based index. Omit to use the active comp.
countNoHow many frames to sample across the duration (default 9).
maxWidthNoWidth of the whole grid image in pixels (default 1024).
timeoutMsNoWait time in ms (default 90000).
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the process: sample frames across the duration, composite them into a labeled grid, and return a single image. It also addresses comp selection (name, 1-based index, or active comp). It does not mention timeout or resource implications, but the behavior is well-articulated.

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 two sentences, front-loaded with the core value proposition ('See a composition's whole timeline at a glance'), followed by the method and selection instructions. Every sentence earns its place with no redundancy.

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?

No output schema or annotations exist, so the description must cover the return value and key behaviors. It does so by stating the output is a single labeled image and explaining comp selection. The remaining parameters are well-documented in the schema, and the use case is clear. Minor gaps like timeout behavior are not critical for invocation.

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 coverage is 100%, so the baseline is 3. The description adds minimal meaning beyond the schema: it reiterates the comp selection options and clarifies '1-based index', but does not elaborate on count, maxWidth, or timeoutMs. This is sufficient since the schema already documents each parameter.

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 tool's function: rendering N frames from a composition and compositing them into a single labeled thumbnail grid. It uses a specific verb (render/composite) and resource (composition timeline), distinguishing it from sibling tools like see-frame or get-layer-clip-frames.

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 usage context ('Use this to perceive motion, timing, and easing cheaply') and explains the advantage of one image over many. It does not explicitly name alternatives or state when not to use it, but the guidance is sufficient for an AI to choose appropriately.

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/omar-hesham/after-effect-mcp-with-claude'

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