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discover_nvidia_content

Find NVIDIA educational resources by content type and topic, returning ranked results with direct links.

Instructions

Discover specific types of NVIDIA content such as videos, courses, tutorials, webinars, or blog posts. This tool helps find educational and learning resources from NVIDIA's various platforms. Returns ranked results with relevance scores and direct links to the content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
content_typeYesType of content to discover: 'video' for video tutorials and demonstrations, 'course' for training courses and certifications (DLI), 'tutorial' for step-by-step guides, 'webinar' for webinars and live sessions, 'blog' for blog posts and articles
topicYesThe topic or technology to find content about (e.g., 'CUDA', 'Omniverse', 'AI')
max_resultsNoMaximum number of content items to return (default: 5)
date_fromNoOptional date filter in YYYY-MM-DD format. Only content published on or after this date will be included.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNo
summaryNo
contentNo
resource_linksNo
warningsNo
errorsNo
Behavior4/5

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

No annotations exist, so the description carries the full burden. It discloses the output format (ranked results with relevance scores and direct links), which is sufficient for a read-only discovery tool. It does not mention side effects or requirements.

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?

Three sentences, each serving a purpose: core function, use case, and return format. No extraneous information. Very concise.

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?

Given 100% schema coverage, an output schema, and the description covering return format, the tool is well-documented. It does not elaborate on pagination or default behavior for 'max_results', but the schema covers that.

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%, so the baseline is 3. The description adds minimal value beyond the schema; it lists content types already defined in the enum. No extra semantic detail is provided for parameters like 'topic' or 'max_results'.

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 starts with a specific verb 'Discover' and the resource 'NVIDIA content', clearly stating the tool's function. It enumerates content types (videos, courses, tutorials, webinars, blog posts) which distinguishes it from the sibling 'search_nvidia'.

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?

The description implies usage for finding educational content but provides no explicit guidance on when to use this tool versus the sibling 'search_nvidia'. No alternatives or exclusions are mentioned.

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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