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jikime

YouTube Toolbox

get_video_details

Extract detailed information from YouTube videos to analyze content, retrieve metadata, and access video data for research or integration purposes.

Instructions

Get detailed information about a YouTube video

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
video_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information' but doesn't specify what that includes (e.g., title, duration, view count), whether it requires authentication, rate limits, or error handling. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence earns its place by conveying essential information, achieving ideal conciseness.

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 the tool's low complexity (1 parameter, no nested objects) and the presence of an output schema (which should define return values), the description is minimally complete. However, with no annotations and low schema coverage, it lacks details on behavioral aspects like authentication or error cases. For a basic read tool, it's adequate but leaves room for improvement in contextual richness.

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?

The input schema has 1 parameter with 0% description coverage, so the description must compensate. It implies the parameter is a 'video_id' for a YouTube video but doesn't clarify format (e.g., YouTube URL vs. ID string), validation, or examples. Since schema coverage is low, the description adds minimal value beyond what's inferred from the schema property name, meeting the baseline for adequate but incomplete parameter semantics.

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 verb ('Get') and resource ('detailed information about a YouTube video'), making the purpose unambiguous. It distinguishes this tool from siblings like 'get_video_comments' or 'get_video_transcript' by focusing on general video metadata rather than specific aspects. However, it doesn't explicitly differentiate from 'get_video_enhanced_transcript' which might also provide detailed information, keeping it from a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_related_videos', 'get_trending_videos', and 'search_videos', there's no indication that this is for retrieving metadata of a specific known video ID versus browsing or searching. No exclusions or prerequisites are mentioned, leaving usage context implied at best.

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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