veritasgraph_query

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

No annotations provided. Description adds context about output (citations, reasoning path) and multi-hop traversal, but doesn't disclose potential side effects, required permissions, or behavior for empty graphs/ambiguous questions.

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?

A single sentence that is front-loaded with the key outcome. However, it could be split into a brief overview followed by output details for better readability.

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?

No output schema exists, so description should explain return format. It mentions citations and reasoning path but not structure (text, JSON). Missing error scenarios and behavior for edge cases.

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 100% with descriptions for all 4 parameters. The tool description does not add further meaning beyond what is already in the schema, so baseline score applies.

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 a question' and output: 'graph-grounded, multi-hop answer with verifiable citations and reasoning path.' It distinguishes from siblings like veritasgraph_search_entities, which likely retrieves entities without multi-hop reasoning.

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?

No explicit when-to-use or when-not-to-use guidance. Implied usage for multi-hop queries, but doesn't mention alternatives for simpler queries (e.g., search_entities) or graph exploration (get_graph).

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