brave_answers

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

No annotations are provided, so the description bears full responsibility. It discloses the use of an OpenAI-compatible endpoint and live web grounding, but fails to mention any behavioral traits like rate limits, authorization requirements, or whether the operation is read-only. The description is insufficient for full transparency.

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 at two sentences, with no filler. It front-loads the core purpose and immediately explains the technical mechanism.

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?

With no output schema, the description should explain the return format or structure of the answer. It does not, leaving agents uncertain about what to expect. The description is adequate for a very simple tool but incomplete for full 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 description coverage is 100%, with both parameters (query and model) adequately described in the schema. The tool description adds minimal value beyond restating that it uses AI grounding, so the baseline score of 3 is appropriate.

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 returns direct AI answers grounded in Brave Search, using an OpenAI-compatible endpoint. It distinguishes from sibling search tools like brave_web_search by emphasizing answer generation rather than raw results.

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 mentions it is 'best for concise answer generation with live web grounding,' which implies a specific use case. However, it does not explicitly state when not to use it or suggest alternatives, leaving some ambiguity about when to choose this tool over others.

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