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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior, so the bar is raised. The description adds substantial operational nuance beyond that: parallel fan-out across sources, USPTO soft-fail behavior, empty FDA sections being expected rather than errors, private-company resolved:false handling, and the meaning of sources_used/sources_failed. This is exactly the kind of behavioral context an agent needs.

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 dense with high-value information and is front-loaded with trigger phrases and the core purpose. It could be tightened slightly—some input-form examples repeat in the later value explanation—but nearly every sentence earns its place given there is no output schema to document the complex return shape.

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 multi-source tool with no output schema, this description is remarkably complete. It enumerates every result section, explains empty-section semantics, documents failure modes, covers private-company behavior, and even mentions the USPTO API sunset. An agent has enough context to invoke it correctly and interpret partial or empty results.

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 3. The description goes further by explaining that type accepts 'company' or 'ticker' interchangeably, that value can be a ticker, zero-padded CIK, or company name, and that name resolution now works via SEC EDGAR's company-name match. This adds real semantic detail beyond the schema's terse parameter 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 concrete trigger phrases and a specific verb+resource: 'full cross-source profile of a US public company in ONE parallel call.' It also explicitly contrasts itself with chaining single-pack lookups and lists the exact sources it fans out across, so an agent can distinguish it from siblings like resolve_entity or compare_entities.

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 explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear when-to-use rule. It further clarifies acceptable inputs (ticker, CIK, or company name), how ambiguous inputs resolve, and what happens for private companies, making invocation conditions unambiguous.

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