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netcafe-translate

by com.ainetcafe

Translate subtitles, timeline untouched

translate_srt
Read-onlyIdempotent

Translate an .srt subtitle file into another language while keeping every timestamp and cue number byte-identical. Cues are anchored by index and refilled in code, so the timeline cannot drift — the usual failure mode when you hand a whole .srt to a model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoTarget language, e.g. "English", "日本語".
srtNoThe .srt file content.
urlNoOr a link to the .srt file.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description reveals the internal anchoring and refilling mechanism, guaranteeing no timeline drift. This is significant behavioral context that explains how the tool achieves its promise and what to expect.

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, front-loaded with the main action and key guarantee. The second sentence adds valuable context without being verbose. Every word earns its place.

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?

For a subtitle translation tool with an output schema and good annotations, the description is complete. It explains the core feature, the technical approach, and the benefit over naive translation, leaving no critical gaps.

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?

The schema already covers all three parameters with descriptions, so the baseline is 3. The description does not add further semantic detail about the parameters themselves, just the overall file type. This aligns with the schema coverage of 100%.

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 verb 'Translate' and resource '.srt subtitle file', with the specific constraint of keeping timestamps and cue numbers byte-identical. This distinguishes it from sibling tools like translate_text and translate_pdf, which handle different input types.

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 context is clear: use this tool when you have an .srt file and need to preserve the timeline. It also warns against the common failure mode of handing a whole .srt to a model, which implies when this tool is preferable. However, it doesn't explicitly name alternatives or state exclusions, so a 4 is appropriate.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: plain text, PDF, SRT, JSON, grammar checking, and job polling. There is no meaningful overlap, and the descriptions explicitly call out when to use one over another (e.g., translate_text vs translate_pdf).

Naming Consistency5/5

All tools follow a clear verb_noun pattern in lowercase snake_case: check_grammar, check_job, translate_i18n_json, translate_pdf, translate_srt, translate_text. The two verbs (check_ and translate_) correspond to their functional groups, making the naming predictable and easy to navigate.

Tool Count5/5

Six tools is a well-scoped count for a translation-focused server. Each tool has a distinct purpose and earns its place; the set is neither bloated nor too thin.

Completeness4/5

The surface covers the core translation formats (text, PDF, subtitles, i18n JSON) plus async job status and grammar checking. Minor gaps exist, such as support for other document formats (e.g., DOCX) or a language-list endpoint, but these are not essential to the apparent purpose.

Resources