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AbyAbyss

ffmpeg-mcp-video-editor

by AbyAbyss

Extract a filmstrip

extract_filmstrip
Read-onlyIdempotent

Sample frames from a video into a tiled contact sheet to quickly survey footage and identify key moments.

Instructions

Tile several frames into one contact sheet, to survey footage at a glance.

The fastest way to find out what is actually in a clip — where the good moments are, where the camera settles, which shots are worth cutting to. Answers immediately: each frame is a separate fast seek, so the cost tracks the number of frames, not the length of the video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoNull samples to the end of the file.
countNoHow many frames to sample.
startNo
columnsNoTiles per row.
input_pathYesVideo to sample.
tile_widthNoWidth of each tile.
output_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
timesYes
columnsYes
output_pathYes
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description goes beyond by disclosing a performance behavior: 'each frame is a separate fast seek, so the cost tracks the number of frames, not the length of the video.' This is useful behavioral context not present in structured fields, earning a 4.

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 three sentences, each earning its place: purpose, use case, and cost behavior. It is front-loaded with the core action and avoids any fluff or repetition of schema details.

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?

For a read-only, idempotent tool with an output schema, the description provides the key decision factors: what the tool does, when to use it, and how it behaves (cost model). It does not explain return format, but the output schema covers that. The only minor gap is not explicitly describing default behavior for output_path, but the schema default handles that. Overall complete enough.

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 71%, and most parameters (count, columns, tile_width, end, input_path) have individual descriptions with defaults and ranges. The tool description itself adds no parameter-level meaning beyond the schema, so it does not compensate for the few undocumented parameters (start, output_path). This aligns with the baseline 3 for high coverage.

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 specific verb-resource pairing: 'Tile several frames into one contact sheet' which exactly states the tool's function. It also explicitly differentiates from sibling tools like extract_frame by focusing on 'several frames' and 'survey footage at a glance', making the purpose unmistakable.

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: 'The fastest way to find out what is actually in a clip — where the good moments are, where the camera settles, which shots are worth cutting to.' This tells the agent when to use the tool, though it does not explicitly name alternatives or state when not to use it. The strong use-case framing earns a 4.

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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