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research_youtube

Queue YouTube videos for transcription and insight extraction to support research analysis.

Instructions

Queue a YouTube video for research. Midos will transcribe and extract insights.

Args: url: YouTube URL to research priority: Priority: 'high', 'normal', 'low'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
priorityNonormal

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that 'Midos will transcribe and extract insights,' which hints at asynchronous processing, but doesn't clarify whether this is a fire-and-forget operation, how results are delivered, what authentication is needed, or any rate limits. The description is insufficient for a mutation tool with zero annotation coverage.

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?

The description is appropriately sized and well-structured with a clear purpose statement followed by a parameter section. Every sentence adds value, though the 'Args' formatting could be slightly more integrated with the main description text.

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

Completeness3/5

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

Given that an output schema exists (which should document return values), the description doesn't need to explain outputs. However, for a tool that queues asynchronous processing with no annotations, the description should provide more behavioral context about how to access results, expected timing, or error handling. The parameter documentation is good, but overall completeness is only adequate.

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 description explicitly documents both parameters in the 'Args' section, providing clear semantics for 'url' and 'priority' with its allowed values. Since schema description coverage is 0% (no parameter descriptions in the schema), the description fully compensates by explaining what each parameter means, earning a high score despite the schema's lack of documentation.

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 clearly states the tool's purpose with a specific verb ('Queue') and resource ('YouTube video'), and explains what happens after queuing ('Midos will transcribe and extract insights'). However, it doesn't differentiate this tool from its many siblings, which appear to be unrelated to YouTube research based on their names.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, constraints, or relationships with sibling tools. While the priority parameter suggests urgency levels, this doesn't constitute usage guidance for tool selection.

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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