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

Beyond the readOnly/openWorld annotations, it discloses that every finding includes a citation and implication, that executive names are allowed only when cited and contact details are never included, and that risk analysis surfaces explicit unknowns. This gives an agent accurate expectations for output content and policy.

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 prose is dense but organized around dimensions, then depth behavior. It loses a point because the final depth sentence largely duplicates the depth parameter's schema description, which is redundant next to structured data.

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 complex research tool, it covers the input domain, the five research areas, output expectations (citations, implications, unknowns), and depth trade-offs. The presence of an output schema covers return structure, so nothing needed to select or invoke the tool correctly is missing.

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 the schema already documents domain, depth, and focus_topics adequately. The description adds no new parameter-level semantics; it merely restates the depth default from the schema.

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 opens with 'Exhaustive intelligence probe on a company' and enumerates five concrete research dimensions, giving a specific verb, resource, and scope. The dimensions and 'cited' framing differentiate it from narrower siblings like teardown_tech_stack or generate_swot_analysis, even without naming them.

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 provides internal depth-selection guidance ('Defaults to depth standard... request comprehensive...') but never states when to choose this tool over sibling research tools. There are no exclusions or alternative routing cues, so an agent gets no help choosing between get_deep_research and get_company_intelligence.

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