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

Annotations already mark this as read-only, idempotent, open-world, and non-destructive, and the description complements them richly. It details the fanned-out data sources, soft-fail behavior for the USPTO API sunset, expected empty sections like FDA products for companies with only small-molecule drugs, and the resolved:false path for private companies.

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 front-loaded: examples and the preference directive appear first, followed by organized behavioral and return-value details. It is somewhat run-on as a single paragraph, but each segment adds genuinely useful information for a complex multi-source tool.

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 return values, and it does so thoroughly: it enumerates cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also covers input edge cases and expected empty results, making the tool safely invocable and interpretable.

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 'type' and 'value' already have detailed descriptions. The description restates that 'type' accepts the same shapes either way and that 'value' can be a ticker, CIK, or company name, but adds little beyond the schema aside from minor context like resolved_from/resolved_to and 'person/place coming soon.'

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 clearly states the tool produces a 'full cross-source profile of a US public company in ONE parallel call' and opens with concrete user-phrase examples. It distinguishes this tool from chained single-pack lookups and makes its scope (US public companies, tickers/CIKs/names) 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?

There is an explicit preference directive: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' This gives a clear context for use, though it does not name specific sibling tools or provide explicit when-not-to-use guidance beyond that.

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