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Subtitle Toolkit

convert_subtitle

Convert subtitle text between formats. Reads SRT, WebVTT, ASS/SSA, YouTube SBV and TTML/DFXP; writes SRT, WebVTT, ASS, CSV or plain text. Format is auto-detected unless from is given.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesTarget format. `text` = plain transcript, one line per cue, no timecodes.
fromNoSource format (default "auto" = detect).
dedupeNoOnly for to="text": collapse consecutive identical lines (rolling-caption transcripts repeat lines). Default false.
contentYesThe full subtitle file text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It accurately describes the conversion action, lists the formats, and notes auto-detection behavior. It does not mention potential edge cases like unsupported features or error handling, but for a pure conversion tool the core behavior is transparent. The description adds value beyond the schema by summarizing the read/write capabilities.

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?

Two sentences with zero filler. The purpose is front-loaded with a verb and resource, and the format list is compact yet complete. Every sentence earns its place, and the auto-detection note is a meaningful addition rather than repetition.

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 tool has 4 parameters, all documented in the schema, and 2 enums. There is no output schema, but the description implies the return is the converted subtitle text. For a conversion tool of this simplicity, the description plus schema covers all necessary information. The only minor gap is not explicitly stating the return format, but it is easily inferred.

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 100%, so the baseline is 3. The description reinforces the `from` default ('Format is auto-detected unless `from` is given') and names the output formats, but it does not elaborate beyond what the schema already documents. Since the schema fully defines each parameter, the description adds only marginal semantic value.

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 states a specific verb ('Convert'), the resource ('subtitle text between formats'), and enumerates both input and output formats, making the tool's scope unmistakable. It clearly distinguishes itself from siblings like retime_subtitles or clean_subtitles, which address different concerns, without ambiguity.

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 that this tool is for format conversion, and the auto-detection note implicitly tells an agent when to use the `from` parameter. It does not explicitly name alternative tools for other operations, but the purpose is specific enough that an agent can infer the right selection. No exclusions are stated, but the context is sufficient for correct routing.

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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