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mio_ai_video_background_remover

AI Video Background Remover — Remove or replace video backgrounds using AI. 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

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TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and discloses several behavioral traits: 'dispatches to our AI workers (Modal)', 'Credits per run vary', 'Files are deleted after processing', and audit trail availability. It also clarifies billing constraints (Day Pass/welcome credits excluded). This goes beyond typical descriptions, though it omits details about output delivery or processing time.

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 front-loaded with the primary purpose, then covers credit and privacy details. It contains five sentences, with the last sentence about workspace unlocking being somewhat tangential to tool usage but still relevant for cost expectations. Not overly verbose, but could be tightened by removing the final sentence.

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 no parameters, no output schema, and no annotations, the description covers the essential operational context: purpose, AI worker dispatch, credit model, file deletion, and auditability. However, it does not explain the expected output format or any prerequisites for using the tool, which are left implicit.

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 input schema has zero parameters, so the baseline is 4. The description mentions 'model and file size' as factors affecting credits, which is extra context but not directly describing parameters. Since there are no params, it does not need to compensate for schema gaps.

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 'Remove or replace video backgrounds using AI', providing a specific verb and resource. It distinguishes itself from sibling background remover tools by explicitly mentioning 'video', unlike image background removers like mio_ai_remove_background.

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?

Usage is implied through the tool name and description ('AI Video Background Remover'), but there is no explicit guidance on when to use this tool versus alternatives like mio_ai_remove_background or mio_ai_remove_background_pro. No exclusions or alternative tool references are provided.

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

C2.8/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as mio_ai_remove_background and mio_ai_remove_background_pro, mio_ai_video_subtitler and mio_video_auto_captions, and mio_ai_enhancer tools targeting similar media. Agents would struggle to pick the correct tool when several appear to do nearly the same thing.

Naming Consistency2/5

Naming conventions are mixed: most tools use a mio_ prefix with category, but some use action-based names (mio_image_compress), others use format-pair names (mio_image_avif_to_jpg), and a few use a different prefix (mioffice_list_tools, mioffice_pricing_info). The lack of a uniform pattern makes the tool set harder to navigate.

Tool Count1/5

With 134 tools, the server is massively over-scoped. Even for a broad workspace suite, this count exceeds practical limits and creates significant selection overhead for agents. The number is more appropriate for a full product catalog than an MCP tool surface.

Completeness3/5

The tool set covers a wide range of PDF, image, audio, video, scanner, and AI operations, so most common tasks are represented. However, there are notable gaps for a 'workspace studio,' such as no document creation or spreadsheet editing tools, and the redundancy between overlapping AI tools suggests the surface is not thoughtfully curated.

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