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

The annotations already indicate a safe read-only, idempotent operation, but the description goes far beyond that: it discloses the parallel fan-out across many sources, the USPTO soft-fail behavior, the 'empty section is a real no-data' contract, and the resolved_from/resolved_to behavior for name inputs. It also explains that fda_products showing none is expected for non-biologic companies, which prevents false interpretation.

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 earns its length for a tool with this many output sections and behaviors. It is front-loaded with trigger examples and the core 'one parallel call' value proposition, then enumerates output fields semicolon-separated. A small amount of redundancy exists (e.g., 'type' semantics reappear in the input schema), but the dense information is well organized and scannable.

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 burden of describing return shape, and it does so thoroughly: every output field (cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed) is explained with enough context to interpret results. It also covers edge cases like private companies, no-data sections, and the USPTO sunset. Nothing an agent needs to call or interpret the tool is missing.

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, but the description adds meaningful semantics: it gives concrete examples for each accepted shape, specifies zero-padding for CIKs, notes that names resolve via SEC EDGAR, and clarifies that 'type' is interchangeable regardless of which 'value' form is passed. The main gap is that 'person/place coming soon' is a minor future note rather than a behavioral requirement.

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 explicit trigger phrases and a specific verb+resource: 'full cross-source profile of a US public company in ONE parallel call.' It clearly differentiates itself from chaining multiple single-source lookups by framing itself as the holistic alternative. The output sections are enumerated, leaving no ambiguity about what the tool produces.

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.' It also provides concrete trigger examples and describes edge-case routing: private companies return resolved:false rather than a bare failure. This is strong when-to-use guidance with clear exclusions.

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