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

Annotations already mark the tool read-only, idempotent, and non-destructive, and the description adds substantial behavioral context far beyond that: it enumerates the fanned-out sources, return sections, soft-failure behavior for USPTO patents, expected-empty semantics for FDA products, sources_used/sources_failed meaning, name resolution via SEC EDGAR, and private-company handling with resolved:false. Nothing in the description contradicts the annotations.

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 dense and long, but the complexity of the tool justifies most of the length. It is front-loaded with the core purpose and usage directive, and nearly every sentence carries useful caveats or behavioral details. Some redundancy exists with the schema (e.g., type/value shapes are repeated), and bullet structuring could improve scannability, but it remains efficiently packed.

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?

Despite having no output schema, the description provides an exceptionally complete picture: input shapes, source fan-out, return field names, URI examples, soft-fail conditions, expected-empty sections, failure semantics, and private-company behavior are all covered. An agent has enough context to select and invoke this tool correctly and to interpret its outputs.

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 beyond the schema: it clarifies that type values are interchangeable, that value can be a ticker, zero-padded CIK, or company name, explains name resolution behavior, and notes person/place support is coming soon. This goes beyond the schema's own property 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 clearly states a specific verb and resource: it builds a full cross-source profile of a US public company in one parallel call, illustrated with concrete user phrasings. It distinguishes itself from the general practice of chaining single-pack lookups, though it does not name any sibling tool explicitly, so it stops short of full sibling differentiation.

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 gives explicit guidance: ALWAYS PREFER this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. It also explains what inputs are acceptable and what happens for private companies. It does not explicitly state when not to use it or name alternatives such as compare_entities or resolve_entity, so the exclusion criteria are only implicit.

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