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AbyAbyss

ffmpeg-mcp-video-editor

by AbyAbyss

Build an SRT file

build_srt

Turn timed text segments into a valid SRT subtitle file. Sorts cues, drops empty entries, truncates conflicting overlaps, and wraps long lines for clean captions.

Instructions

Turn a list of timed text segments into a valid SRT subtitle file.

Pure text handling — no ffmpeg call, so this answers immediately. Segments are sorted, empty ones dropped, and overlapping cues truncated so they do not fight each other on screen. Long lines are word-wrapped. Feed the result to burn_captions, or edit it first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
segmentsYesTimed text, in any order.
max_linesNo
output_pathNoWhere to write the .srt file; defaults to the workspace.
max_chars_per_lineNoWrap cues to this width. Null leaves the text unwrapped.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
durationYesEnd time of the last cue, in seconds.
cue_countYes
output_pathYes
content_previewYesFirst few cues, for a quick sanity check.
Behavior5/5

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

The description goes well beyond annotations by disclosing key behaviors: 'Pure text handling — no ffmpeg call', 'Segments are sorted, empty ones dropped, and overlapping cues truncated', and 'Long lines are word-wrapped.' This provides important behavioral context that annotations (only basic hints) do not cover.

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 concise yet highly informative. It starts with a clear purpose, then efficiently lists behavioral traits and a downstream usage hint. Every sentence adds value with no redundancy or filler.

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

Completeness5/5

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

Given the presence of an output schema and parameter descriptions, the description covers the essential aspects: input handling (sorting, dropping empty, truncating overlap), text wrapping, and the tool's lightweight nature. It also provides workflow context by referencing burn_captions, making the tool's role in the ecosystem clear.

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?

The schema already covers most parameters (75% description coverage), and the description adds behavioral meaning to segments (sorting, truncation) and wrapping for max_chars_per_line. However, it does not explain max_lines beyond the schema's title/default, which is a minor gap given the description's focus on text formatting.

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 action: 'Turn a list of timed text segments into a valid SRT subtitle file.' It uses a specific verb and resource, and distinguishes itself from siblings like burn_captions and auto_caption by emphasizing pure text handling and no ffmpeg call.

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 context for when to use this tool: when you have timed text segments and need an SRT file. It also suggests a downstream workflow with burn_captions ('Feed the result to burn_captions, or edit it first'). However, it does not explicitly name alternatives or state when not to use it.

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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