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

Annotations already mark it read-only, idempotent, and non-destructive, but the description adds substantial behavioral detail: it fans out across multiple sources in parallel, soft-fails for the USPTO sunset, returns sources_used/sources_failed, and explains that an empty section is a real "no data" result. It also spells out the private-company resolution failure mode. These go far beyond the annotation hints.

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 it is front-loaded with user-intent examples and the core purpose, and every block covers a distinct aspect (inputs, fan-out sources, return fields, failure behavior). Some redundancy exists — CIK formatting and SEC EDGAR name resolution appear in both the schema and the description — but the density is justified by the tool's breadth.

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 lists all returned sections (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI) and the sources_used/failed fields. It also covers input resolution, empty-section meaning, and private-company behavior, leaving no critical calling detail unaddressed.

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 description coverage is 100%, so the schema already explains both parameters. The description repeats the same ticker/CIK/name guidance and adds examples, plus the note that 'company' and 'ticker' behave identically. This adds marginal convenience but does not materially extend the schema's semantics, hence the baseline 3.

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 leads with concrete example queries and a crisp definition: "full cross-source profile of a US public company in ONE parallel call." It names the exact resource (a company) and the verb (profile), and distinguishes itself from chaining single-pack lookups, making it easy to separate from siblings like resolve_entity or deep_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 says "ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view," which gives clear when-to-use guidance. It also sets expectations for edge cases (private companies, empty fda_products). However, it does not enumerate when to prefer sibling tools like compare_entities or deep_research, leaving a minor gap.

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