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Subtitles in up to 3 languages (up to 15 min) · $0.15

vngrd_subtitles

Broadcast-style subtitles for a video or podcast: transcribed, timed and translated into up to 3 languages, as SRT and WebVTT files ready to upload to YouTube, Instagram, TikTok or a player. Up to 15 minutes and 20 MB. Price: $0.15 USDC on Base, paid per call with x402 (send the payment in _meta["x402/payment"]; a call without it returns the payment requirements).

Input Schema

NameRequiredDescriptionDefault
audio_urlYesPublic https link to the video or audio file
languagesYesTarget ISO codes, e.g. ["en","it","es"]. The original language is always included.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Beyond the annotations, the description discloses the paid x402 flow, the specific _meta payment key, the per-call price, and what a call without payment returns. This is valuable behavioral context, though it does not say whether results return immediately or as a job that must be polled.

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 a tight, front-loaded block: capability and outputs first, limits next, payment mechanics last. Every sentence carries actionable information with no filler.

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

Completeness3/5

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

For a paid, open-world media-processing tool with no output schema, the description covers deliverables and pricing well. It omits the execution model (synchronous versus job-based, typical latency, or how to retrieve files), which matters given the presence of vngrd_job.

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 coverage is 100%, so both parameters are already documented, including the note that the original language is always included. The description adds little parameter-level meaning beyond what the schema provides, so the baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: transcribes, times and translates a video or podcast into up to 3 languages and returns SRT and WebVTT files. That clearly distinguishes it from a plain transcription sibling like vngrd_transcribe, though it never names the alternative explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives useful operational context (15-minute and 20 MB limits, target platforms, payment requirement) but no explicit guidance on when to choose it over vngrd_transcribe or other siblings, and no when-not-to-use conditions.

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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