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

Even with readOnly/idempotent annotations already present, the description adds valuable behavioral detail: parallel fan-out across sources, soft-failure for the PatentsView sunset, empty sections meaning genuine 'no data', and a resolved:false path with an explanatory note for private companies. No contradiction with annotations; this is the kind of disclosure that lets an agent set correct expectations.

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 long, but the complexity of a multi-source fan-out tool justifies the length, and the opening sentence front-loads the core purpose. Some repetition through example phrasings keeps it dense but not wasteful.

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 to lean on, the description carries the full burden and delivers: it enumerates every returned section, defines success and failure semantics, and notes expected edge cases like FDA products for small-molecule-only companies. For a complex tool with many sources, an agent has almost everything needed to call and interpret it correctly.

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%, so the baseline is met; the description goes further by giving concrete value examples, clarifying that 'company' and 'ticker' are interchangeable, and describing name resolution via SEC EDGAR. This reduces ambiguity around the 'value' parameter beyond the schema's own descriptions.

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 a clear, specific verb-plus-resource statement: it produces a 'full cross-source profile of a US public company' and maps several user phrasings to the tool. It distinguishes itself from chaining single-pack lookups, though it does not name sibling tools like deep_research or compare_entities directly, so differentiation is implicit rather than explicit.

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 explicitly tells the agent to 'ALWAYS PREFER' this tool over chaining single-source lookups when the user wants a holistic company view, and it explains acceptable input shapes. It handles the private-company case, but it does not explicitly carve out when to choose a named sibling such as deep_research or resolve_entity.

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