mcp-tools-for-agents

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detect_scenes

Detect scene changes in a video and return the time intervals of each scene, helping you decide where to cut. Use background mode for long videos to run as a job.

Instructions

Detecta mudanças de cena e devolve os intervalos de cada cena.

Use para decidir onde cortar. Percorre o vídeo inteiro, então em vídeos longos prefira background=true.

Args: path: Vídeo, relativo ao workspace. threshold: Sensibilidade entre 0 e 1. Menor detecta mais cenas. background: Executa como job e devolve job_id.

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": {
      "path": "<path>"
    },
    "name": "detect_scenes"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes
`threshold`	No
`background`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

A4.6/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses that the tool scans the full video, that long videos should use background mode, and that background=true returns a job_id. It does not mention blocking behavior or side effects, but the core behavioral profile is clearly conveyed.

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 well-structured: a one-line function statement, a usage hint, and a concise parameter list. Every sentence earns its place and the most important guidance is front-loaded.

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

Completeness5/5

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

For a 3-parameter tool with no annotations and an output schema available, the description is complete enough: it covers purpose, parameter semantics, and the important background-job path. The mention of job_id also informs the agent that follow-up with job_status/job_result may be needed, which fits the sibling set.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must fully document parameters. It does: path is relative to the workspace, threshold is a sensitivity value between 0 and 1 with lower values detecting more scenes, and background executes as a job returning job_id. This adds meaning well beyond the raw schema.

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 action ('detect scene changes'), the resource (video), and the return value (scene intervals). The stated purpose 'decide where to cut' clearly differentiates it from siblings like cut_video and probe_video.

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 explicitly says to use it 'para decidir onde cortar' and advises using background=true for long videos because it scans the entire video. It gives clear context but does not explicitly mention when not to use it or name alternative tools.

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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