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

Annotations already declare readOnly/openWorld/idempotent safety, and the description adds rich operational context: source fan-out, USPTO sunset soft-fail, expected empty sections for certain companies, resolved:false behavior for private companies, and type interchangeability. No contradictions with annotations.

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 nearly every clause carries substantive information about scope, sources, output sections, or failure modes. It is front-loaded with user intents and the core capability. It could be slightly tightened, but the density is justified by the tool's complexity.

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, the description provides an unusually complete map of response sections, sources, fallback behavior, and special cases like no-data sections. Missing details like exact date ranges are minor given the high complexity and the depth already present.

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% and both parameters are documented, so the baseline is 3. The description adds practical semantics: zero-padded CIK format, ticker/company/CIK equivalence, SEC EDGAR name resolution, and concrete examples that help construct correct values.

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 a specific verb and resource: build a full cross-source profile of a US public company in one parallel call. It distinguishes itself from chaining single-pack SEC/XBRL/news lookups and names its broad input types. An agent can confidently select this tool for holistic company research.

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 gives trigger phrases like "Tell me about X" and "research Acme" and instructs ALWAYS PREFER over chaining single-pack lookups for holistic views. It does not enumerate explicit 'when not to use' conditions, but the holistic-view framing provides clear context.

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