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Glama

supported_platforms

List common video platforms and whether the installed yt-dlp includes an extractor for each, helping you decide if an unfamiliar host is supported.

Instructions

List the common tube platforms (YouTube, Vimeo, Dailymotion, Twitch, TikTok, ...) and whether the installed yt-dlp ships an extractor for each. Use before evaluating an unfamiliar host.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that the tool checks the installed yt-dlp's extractor support, which is a useful behavioral detail. However, it doesn't mention whether the tool performs network calls, caches results, or what the output format looks like. The output schema exists but the description doesn't add much beyond the basic behavior.

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 two sentences with no filler. The purpose is front-loaded, and the usage guidance is appended efficiently. Every word earns its place.

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 zero-parameter informational tool, the description is nearly complete. It states what is listed and when to use it. The only minor gap is not describing the output format, but the output schema exists and the tool is simple enough that this is not a significant omission.

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?

The tool has zero parameters, so the schema is trivially complete. The description adds value by explaining what the tool reports (platforms and extractor availability), which is the entire semantic content. Baseline 4 for zero params is appropriate.

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 clearly states the tool lists common tube platforms and whether the installed yt-dlp ships an extractor for each. It names specific platforms and the resource (yt-dlp extractors), making the purpose unambiguous and distinct from sibling tools.

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 'Use before evaluating an unfamiliar host,' providing clear context for when to use this tool. It doesn't explicitly name alternatives or exclusions, but the sibling tools are all different enough that no confusion arises.

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