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by io.github.theguysaccount
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Turn a video file on this computer into a change list

convert_local_video
Read-only

Use when the user gives you a video FILE on their computer (a screen recording .mov/.mp4/.webm, a Loom or QuickTime download) that you cannot watch. This server cannot read local files, so this tool returns the exact one-line curl command that uploads the file and prints the change list as Markdown; run it with your shell tool. The result lists every change asked for, with the words said, where on screen, how to check it, a screenshot link of that moment, and the timed transcript.

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": "convert_local_video"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesPath of the video file on the user's computer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

The description adds substantial behavior beyond the annotations: the server cannot read local files, the tool returns a one-line curl command instead of processing directly, the agent must run it with a shell tool, and the result includes changes, spoken words, screen locations, verification steps, screenshot links, and a timed transcript.

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 front-loaded with the usage trigger, then explains the mechanism and result. It is dense but every sentence provides actionable information without filler.

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?

With one parameter and no output schema, the description supplies the missing context an agent needs: why the tool exists, what it returns, how to execute the returned command, and what the final change list contains.

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

Parameters3/5

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

Schema coverage is 100%, and the schema already defines the single `path` parameter as the local video file path. The description adds examples of acceptable source types and formats, but does not explain path formatting, absolute versus relative paths, or other invocation details beyond the 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 scope: a video file on the user's computer that the agent cannot watch, and explains that the tool returns a curl command that uploads it and prints a change list. This clearly distinguishes it from handling a video link or retrieving an existing change list.

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 gives explicit when-to-use guidance: use when the user provides a local video FILE such as a screen recording, Loom, or QuickTime download. It does not explicitly name the alternative tool for video links or state when not to use this tool, but the local-file condition is clear.

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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