ask_nvidia

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

No annotations provided, so description carries full burden. It describes setup but not behavioral traits like read-only nature, latency, or side effects. Does not state that it is a safe query operation, leaving some uncertainty.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with main purpose, then prerequisites, overrides, and param descriptions in a clear, concise format with no wasted words.

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

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

Covers prerequisites, overrides, and param semantics. Has output schema (unseen) likely for answer. Could mention return format or error handling, but overall complete for a query tool with given context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but description adds meaning: question is 'Natural-language question about the NVIDIA AI stack', domain is 'Domain from list_domains() — auto-detected from question if omitted.' This significantly enhances understanding beyond the raw schema.

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

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

The description clearly states the verb 'ask' and the resource 'a natural-language question answered by Qwen grounded on the NVIDIA CKG.' It differentiates from sibling tools like list_domains and query_ckg by specifying the natural-language querying aspect.

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

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

Provides clear usage context: natural-language questions about the NVIDIA AI stack, prerequisites (Ollama with Qwen model), and environment variable overrides. Lacks explicit when-not-to-use or alternatives, but implicitly distinguishes from siblings.

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