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by meomeo-dev

ffmpeg__burn_subtitles

Permanently embed SRT or ASS subtitles into a video by re-encoding it with ffmpeg's subtitles filter. Supports custom styling via force_style overrides.

Instructions

Hard-burn SRT or ASS subtitle file into a video using the ffmpeg subtitles filter. @remarks Consumes .ass files produced by the ass bundle (ass__create_template). Re-encodes the video track. Returns JSON in stdout with output_path and applied parameters. @param input_path Source video path. @param subtitle_path Subtitle file path (.srt or .ass). @param output_path Destination video path with burned-in subtitles. @param force_style Optional ASS/SSA style override string (for example Fontsize=24,PrimaryColour=&HFFFFFF&). Applies to both SRT and ASS inputs. @param __mcp_response_mode Optional response mode: content (default) or structuredContent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_pathYes
force_styleNo
output_pathYes
subtitle_pathYes
__mcp_response_modeNocontent
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose that the video track is re-encoded and that JSON is returned, which are important behavioral facts. Yet it omits details about file overwriting, codec implications, or failure modes, leaving notable gaps for a mutation-like tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well structured with a concise summary followed by @remarks and @param details. It is not overly terse, but each sentence adds value. It could be tightened slightly without losing essential information, so it earns a 4 rather than a 5.

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?

The description covers the operation, parameter meanings, consumption of ass__create_template output, re-encoding behavior, and return format. There is no output schema, so mentioning the JSON stdout is helpful. However, it lacks examples of complete usage or edge-case behavior, leaving a small but acceptable gap.

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

Parameters5/5

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

Schema coverage is 0%, but the description compensates fully by documenting all five parameters in @param lines. It goes beyond the schema by clarifying formats, providing an example for force_style, and explaining the response mode options. This is exactly what the description should do.

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 and object: 'Hard-burn SRT or ASS subtitle file into a video using the ffmpeg subtitles filter.' This clearly distinguishes it from sibling tools like mixing audio or applying color LUTs. It states exactly what operation is performed and on which resource.

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?

It provides useful context: 'Consumes .ass files produced by the ass bundle (ass__create_template)' and mentions re-encoding and the output format. However, it does not explicitly contrast with alternative ffmpeg tooling or say when NOT to use it, so it stops short of a 5.

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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