Skip to main content
Glama

phone_videos

Read-only

Find iPhone AirDrop videos in your Downloads folder, check dates and lengths, optionally transcribe openings, and match clips to Takes sessions for import.

Instructions

The videos the user AirDropped from an iPhone that wait in ~/Downloads (AirDrop or iPhone recordings only; all=true for every video), oldest first, with length, recording time and, with listen=true, the first words said (Whisper, about 10 s per video). Also lists the newest sessions with the start of each script, so you can match each video to its session and import_take it with move=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
allNoEvery video in the folder, not only AirDrop/iPhone ones.
daysNoOnly files from the last N days. Default 14.
folderNoDefault ~/Downloads.
listenNoTranscribe the first 40 s of each video. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare it read-only and non-destructive, so the safety profile is covered. The description goes further by disclosing ordering (oldest first), the transcription cost/engine (~10 s per video, Whisper), and the fact that it also surfaces recent sessions for matching. It doesn't mention pagination or a cap on results, which is the only notable gap.

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?

Two sentences, front-loaded with the core resource and scaffolded with the flag-driven variations. The second sentence is dense and crams session-matching plus import_take into one clause, but nothing is wasted.

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?

With no output schema, the description carries the burden of describing returns, and it does: fields returned, ordering, and the paired session listing. It omits result-count limits and what the entry identifiers look like, which would have made matching/importing unambiguous.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema: the time cost and engine for listen=true and the downstream move=true behavior for import_take. That extra context about practical consequences of the flags edges it above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific resource — videos AirDropped from an iPhone sitting in ~/Downloads — and enumerates what comes back (length, recording time, transcribed opening words). It is clearly distinct from media-oriented siblings like list_broll or search_media. The verb is only implicit ('lists'), keeping it short of a clean 5.

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?

It gives conditional guidance for the flags (all=true for everything, listen=true to transcribe, import_take with move=true to pull a take in), which is genuinely useful. However, it never states when to prefer this over list_broll, search_media, or next_path, and there is no explicit 'use this when' framing.

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