brain_ask

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

With no annotations provided, the description carries the full burden. It transparently describes the retrieval, synthesis, grounding, and citation behaviors, as well as the verify audit option. However, it does not mention potential limitations (e.g., could be slow with verify, might not find relevant excerpts) or side effects, which would have made it more transparent.

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 concise and well-structured with clear 'Behavior' and 'Usage' sections. It conveys all necessary information without redundancy or excessive length.

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 adequately differentiates brain_ask from the sibling brain_search and explains the verify option. It covers the tool's purpose and usage context well. However, it does not mention any edge cases (e.g., what happens if no relevant excerpts are found) or input/output examples, which would make it complete.

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 schema describes only the verify parameter ('audit the answer against the sources'), while the question parameter has no description in the schema. The tool description implicitly clarifies that 'question' is a natural-language query, but the descriptions are minimal and do not add much beyond the schema. Parameter semantics are adequate but not enriched.

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's function: asking a question, retrieving relevant excerpts, synthesizing an answer grounded only in those excerpts, and providing source citations. It explicitly contrasts with brain_search, making the purpose distinct and specific.

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 gives explicit usage guidance: prefer brain_ask over brain_search when synthesis or explanation is needed, and set verify=true when accuracy matters more than speed. This provides clear when-to-use and trade-off direction.

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