get_company_deep_dive

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

With no annotations, the description carries the full burden. It discloses that the tool 'Fetches deeper details' and gives examples of the content, implying a read-only operation. However, it does not describe the return format, pagination, or any other behavioral constraints, leaving some ambiguity for a fetch tool.

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 a single sentence that front-loads the core action and resource, with examples adding valuable specificity. No wasted words or redundant information.

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?

For a simple tool with one enum parameter and no output schema, the description is mostly complete: it states the purpose, scope, and typical use cases. It could be more explicit about the returned data's structure, but the examples partially compensate.

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%: the only parameter 'company' is fully described with an enum and explanation. The description adds no extra parameter-level detail beyond the tool's overall purpose, so the baseline of 3 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 explicitly states the verb 'Fetches' and the resource 'deeper details on specific companies Matt has worked at', with concrete examples (Nomad Go scaling details, TUNE Payout Structures) that clarify scope. This clearly distinguishes it from sibling tools like query_resume_history, which is for general history.

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 when to use the tool: when specifics on one of Matt's past companies are needed, as opposed to general history (query_resume_history) or scheduling (send_scheduling_email). It does not explicitly mention alternatives or exclusions, but the 'specific companies' phrasing offers clear context.

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