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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, and the description adds substantial behavioral context on top: the full list of fan-out sources, what each return section contains, USPTO sunset soft-fail behavior, that empty fda_products is expected for non-biologic companies, that sources_failed distinguishes 'no data' from bugs, and that private companies return resolved:false with a notes line. This goes far beyond what annotations alone convey.

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 earned: it packs a large amount of return-structure and edge-case information into organized clauses, with the core purpose and usage guidance front-loaded. It is dense rather than wordy, though a few details (e.g., repeating that type accepts either value) are slightly redundant with the schema. For this tool's complexity, the length is justified.

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 carries the full burden of explaining what the tool returns, and it does so thoroughly: it enumerates every major result field (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), explains source-failure semantics, describes input resolution behavior, and covers the private-company failure mode. An agent has enough context to call this correctly for a wide range of user requests.

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 already 100%, but the description enriches the parameters considerably: it gives valid example shapes for ticker, CIK, and company name, explains that names resolve via SEC EDGAR, notes resolved_from/resolved_to for name lookups, and clarifies that type='company' and type='ticker' behave identically. This materially helps an agent choose correct inputs beyond the bare 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 concrete user phrasings and a crisp statement: 'full cross-source profile of a US public company in ONE parallel call.' It names the exact resource domain (US public companies) and the exact deliverable (profile), and it contrasts itself with single-pack SEC/XBRL/news lookups. This makes the tool's purpose and its differentiation from more narrow search tools immediately clear.

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 to 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a clear when-to-use condition. It does not name sibling alternatives like compare_entities or deep_research, nor does it give when-not-to-use exclusions, so it falls just short of the strongest guidance.

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