no-api-media

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Check a looping video for a visible seam

loop_check

Verifies whether a background or product video will loop without visible jumps by comparing its first and last frames for structural similarity and reporting where motion fails to return.

Instructions

For a background-video or product-video meant to loop: compares its first and last frame with the same structural-similarity check media_optimize uses for quality loss, and reports whether it will look seamless on repeat. A low similarity means a visible jump or jerk when it loops; regenerate with a direction that explicitly brings the motion back to where it started.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "input_path": "<input_path>"
    },
    "name": "loop_check"
  }
}

Input Schema

Name	Required	Description	Default
`input_path`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.4.1Oct 25, 2026

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 behavioral burden and does well: 'compares' and 'reports' imply a read-only check, and it explains what low similarity means in practice. It does not explicitly state side effects, permissions, or expected output shape, leaving minor gaps.

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 compact and front-loaded: it starts with the intended use case, then explains the check, then interprets low similarity and remediation. Every sentence adds relevant information without repetition.

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 simple one-parameter check with no output schema, the description explains purpose, method, result interpretation, and remediation well. It remains slightly incomplete because the lone input parameter and exact return shape are not described.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the single input_path parameter, so the schema provides almost no semantic help. The description only indirectly indicates the input is a looping video and gives no path format, file constraints, or accepted video details.

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 and resource: it compares a video's first and last frame and reports looping seamlessness. It also differentiates the check from media_optimize by explaining that this is the loop-seam use of a similar similarity check.

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?

It clearly scopes use to background-video or product-video assets meant to loop, and it says what to do when similarity is low: regenerate with motion that returns to the starting point. It does not explicitly name exclusions or alternative sibling tools, so it is strong but not complete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.