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mio_ai_talking_head

AI Talking Head — Bring a portrait and a speech recording together in a talking video. Check the audio limit, then generate and review the animation.. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description must carry the full burden; it usefully discloses credit variability by model/file size, Day Pass exclusions, and post-processing file deletion with a retention link. It says nothing about run duration, async/polling behaviour, or failure handling for what is clearly a long-running generation job, which are the operational traits an agent most needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded, but the remainder is bloated marketing copy: credit-pack policy, the absence of per-workspace subscriptions, and a pricing link that duplicate what mioffice_pricing_info presumably covers. Multiple sentences do not earn their place in a tool definition.

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 zero-parameter, no-output-schema tool, the description explains what goes in and that a review step follows, but it never says how inputs are actually supplied or how the resulting video is returned, so the agent cannot form a complete invocation picture.

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 declares zero parameters, so per the baseline this scores high; the description partially compensates by naming the two required inputs (portrait, speech recording), though it gives no format or size constraints for either.

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 first sentence gives a specific verb-and-resource: combine a portrait plus a speech recording into a talking video. That clearly separates it from siblings like mio_ai_text_to_video or mio_ai_cartoon_filter, though it never names an 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 implies a workflow ('Check the audio limit, then generate and review the animation'), which tells the agent there is a validation step before generation, but it never states when to choose this over sibling video tools or what conditions make it unsuitable.

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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