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

Beyond the readOnly/idempotent annotations, the description discloses fan-out behavior across eight sources, soft-failure of USPTO patents, expected empty fda_products for non-biologic companies, and sources_used/sources_failed semantics. This is exactly the operational detail an agent needs to interpret empty results as real 'no data' rather than bugs.

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 and dense, but it is front-loaded with the core promise and 'ALWAYS PREFER' guidance before enumerating outputs and edge cases. The example list could be trimmed, yet nearly every clause carries operational value.

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?

There is no output schema, so the description rightly takes on the burden of describing the returned fields: cik, resolved_to, recent_filings with URIs, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI. It also covers input constraints, failure modes, and source-status reporting, making it complete for safe invocation.

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 adds meaningful value by explaining that type accepts 'company' or 'ticker' interchangeably, that value can be a ticker, zero-padded CIK, or name, and that name resolution goes through SEC EDGAR. This goes beyond the schema's basic field 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 user phrasings and states the core purpose: 'full cross-source profile of a US public company in ONE parallel call.' It names specific sources and output sections, making the tool's scope unmistakable and distinguishing it from single-source lookups.

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,' naming the alternative and the triggering condition. It also clarifies accepted input forms and what happens for private companies, so an agent knows when to expect a resolved:false result.

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