mcp-tools-for-agents

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cut_video

Cuts a video segment between specified start and end seconds, saving a new file while leaving the original unchanged. Use re-encoding for frame-exact cuts or background execution for long videos.

Instructions

Corta o trecho entre start e end (segundos) e salva um novo arquivo.

O original não é modificado. Por padrão copia os streams sem re-encodar, o que é rápido mas corta no keyframe mais próximo. Use reencode=true para corte exato no frame. Para vídeos longos use background=true e acompanhe com job_status.

Args: path: Vídeo de origem, relativo ao workspace. start: Início do trecho em segundos. end: Fim do trecho em segundos. reencode: Re-encoda para corte exato (mais lento). 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>",
      "start": "<start>",
      "end": "<end>"
    },
    "name": "cut_video"
  }
}

Input Schema

Name	Required	Description	Default
`end`	Yes
`path`	Yes
`start`	Yes
`reencode`	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

A4.7/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses that the original is not modified, that streams are copied without re-encoding by default, that this cuts at the nearest keyframe, that reencode=true gives exact cuts, and that background=true returns a job_id tracked via job_status. These are genuine behavioral traits beyond what schema types express.

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 well-structured and front-loaded: core behavior first, then key behavioral tradeoffs, then a compact parameter list. Every sentence earns its place, and the Args section is justified given the 0% schema coverage. Nothing is redundant or padded.

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 5-parameter tool with no annotations, the description is nearly complete: it covers the operation, non-destructive behavior, encoding tradeoffs, job mode, and all parameter meanings, and an output schema exists so return values need no elaboration. Minor gaps remain—no mention of output file naming/location or error edge cases like start > end—but these don't block correct invocation.

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 compensate, and it does completely: all 5 parameters are documented with semantics—path relative to workspace, start/end in seconds, reencode for exact cut (slower), background returning a job_id. The 'Args' block adds real meaning beyond the bare schema property names and types.

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 opens with a specific verb and resource: 'Corta o trecho entre start e end (segundos) e salva um novo arquivo', which precisely states that this tool trims a video segment and writes a new file. This clearly distinguishes it from siblings like extract_audio (audio extraction), extract_frame (single frame), concat_videos (joining), and detect_scenes (scene detection), so an agent can discriminate without inspecting schemas.

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 strong usage context: it explains the default fast path (copy streams, cuts at nearest keyframe), when to switch to reencode=true (exact frame cut, slower), and when to use background=true (long videos) with job_status for monitoring. It lacks explicit exclusions naming sibling alternatives, but the parameter-mode guidance is clear and actionable.

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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