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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds useful behavioral context by explaining that results come from a curated knowledge base of practitioners, books, and research and are returned as summarised, cited insights. It does not contradict the annotations and provides value beyond them.

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?

Two concise sentences front-load the core domain and topic scope, then describe the output format. Every sentence earns its place with no filler or 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?

Given the robust annotations, complete parameter schema, and a simple research-query tool, the description includes everything an agent needs to select and call it correctly: what topics it covers and what kind of response to expect. The lack of an output schema is mitigated by the explicit 'summarised, cited insights' phrasing.

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%, so all three parameters (email, query, top_k) are already documented structurally. The description adds no parameter-level detail beyond the task context, which is acceptable given the baseline for high schema coverage.

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 states exactly what the tool does: answer entrepreneurship questions covering starting, validating, funding, and scaling a business by returning summarised, cited insights from a curated knowledge base. This clearly distinguishes it from the many sibling specialist tools by scoping it to the entrepreneurship domain.

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?

It gives clear usage context by enumerating the business lifecycle topics the tool covers (starting, validating, funding, scaling), so an agent can match user intents to this specialist. It doesn't explicitly state when not to use it or name alternatives, but the domain framing is strong enough without exclusions.

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