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Dub video

dub_video

Localize a finished video into another language WITHOUT re-rendering it: the spoken track is transcribed, translated, re-voiced and lip-synced back onto the SAME footage, so the visuals, timing and edit are untouched. Just pass the video and the language — the script is read off the source automatically (pass script only to override what it heard). Paid; returns the served URL of the localized video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesthe source video URL
voiceNooptional target voice preset, e.g. 'Aria' (warm female) or 'George' (confident male). Defaults to a voice matching the source speaker's register.
scriptNoOPTIONAL override for the original spoken words. Leave this out — the source video is transcribed automatically. Only pass it when you already know the exact script and the auto-transcript got it wrong.
languageYestarget language, e.g. 'Spanish', 'de', 'French (Canada)'

TDQS

A4.3/5.0
Behavior5/5

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

The description discloses key behavioral facts beyond the annotations: the operation is paid, it automatically transcribes the source audio, it re-voices and lip-syncs onto the same footage, and it returns a served URL. It also notes the script parameter overrides the auto-transcript. Since annotations only indicate a mutating, non-destructive operation, this description adds significant context about cost, process, and output, with no contradiction.

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 efficient and front-loaded with the core purpose, then adds usage and cost details. It is a bit dense but every sentence serves a purpose: it explains the process, the automatic transcription, the override, the paid nature, and the return value. It is well-structured, though slightly longer than strictly necessary.

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?

For a tool with four parameters and no output schema, the description covers the essential usage context: the input requirements (video, language), the automatic transcription, the override option, cost, and return format. It does not mention potential errors or prerequisites like supported video formats, but that is not critical. Overall, it is sufficiently complete for an agent to call it correctly.

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 schema already documents all four parameters well. The description reinforces the automatic transcription behavior and the script override, but this information is already present in the schema for each parameter. The description does not add new meaning beyond what the schema provides, so a baseline of 3 is appropriate.

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 ('localize'), resource ('finished video'), and the key distinction ('WITHOUT re-rendering it'), making it clear this is a dubbing tool rather than a general video editor. The mention of

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 gives clear context for using the tool: it is for localizing a finished video into another language. It instructs the agent to 'just pass the video and the language' and explains when to use the optional script override. It does not explicitly name alternative tools, but the 'WITHOUT re-rendering' phrasing implicitly contrasts it with editing tools, and the paid note adds a cost consideration. This is sufficient for routing, though explicit 'when not to use' guidance would be stronger.

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

A3.7/5.0
Disambiguation2/5

With 293 tools, the surface is enormous and many tools have overlapping purposes—multiple posting tools (post_to_meta, post_to_linkedin, schedule_post, etc.), multiple analytics tools per channel, and several search tools (search_meta_ads, search_instagram, search_reddit...). While each description is detailed, the volume makes it difficult for an agent to reliably distinguish between similar tools without careful reading, leading to frequent misselection.

Naming Consistency4/5

The naming is largely consistent with a verb_noun pattern (post_to_*, list_*, create_*, delete_*, update_*, manage_*). There are clear families for major operations. A few outliers like 'google_business_account', 'hermoso_capabilities', and 'store_get' break the pattern, but the overwhelming majority follow a predictable structure, making navigation somewhat easier.

Tool Count1/5

293 tools is far beyond any reasonable scope for a single MCP server, even for a comprehensive marketing platform. The calibration guide flags 50+ as an extreme mismatch, and this is nearly six times that threshold. Such a large surface overwhelms context windows, increases the probability of misselection, and makes it impractical for agents to learn or use effectively.

Completeness4/5

The tool set covers a vast domain: ad creation and rendering, posting across nine+ social channels, analytics and reporting, file management (Drive/OneDrive), competitor research, brand management, and more. It appears to provide CRUD and lifecycle coverage for most resources. While there may be minor gaps given the immense scope, the overall coverage is impressively comprehensive.