query_ckg

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

With no annotations, the description carries full burden. It discloses traversal depth range and partial match support, but does not mention behavioral aspects like idempotency, rate limits, or whether the tool modifies data. It is adequate but could be more thorough.

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?

The description is extremely concise: one line for purpose followed by clear, scannable argument descriptions. Every sentence adds value with no redundancy.

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?

The description covers input parameters thoroughly and mentions the relationship to list_domains. Since an output schema exists, omission of return details is acceptable. It could mention potential failure cases, but it is mostly complete for a traversal tool.

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?

The input schema has 0% description coverage, yet the description compensates fully by explaining each parameter's meaning, constraints (partial match, depth range 1-5, default 3), and providing concrete examples. This adds significant value beyond the 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 tool traverses the NVIDIA knowledge graph from a concept, specifically focusing on prerequisites and dependents. This precise verb+resource combination effectively distinguishes it from sibling tools like search_concepts (broader search) and get_prerequisites (only one direction).

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?

The description implies usage by mentioning concept (with partial match) and domain (from list_domains) but does not explicitly state when to use this tool over alternatives or when not to use it. Guidance on exclusions or comparison with sibling tools is missing.

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