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

While annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, the description goes far beyond them. It explains fan-out across sources, the meaning of sources_used/sources_failed, empty-section semantics, soft-fail behavior for the USPTO API, and the expected empty fda_products result for companies with only small-molecule drugs. This gives an agent accurate expectations about partial results and non-errors.

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 information-dense and front-loaded with invocation examples and the key 'one parallel call' value proposition. Every major clause adds behavioral or return-format detail; there is a little repetition of type/value semantics, but overall each sentence earns its place.

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?

Given there is no output schema, the description carries the full burden of explaining return shape. It enumerates the main output sections, gives URI examples, explains fallback chains, and clarifies failure vs. empty-result semantics. For a tool this complex, the description is remarkably complete.

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%, but the description adds meaningful nuance: zero-padded CIK format, company-name resolution via SEC EDGAR, interchangeable type values, and the private-company fallback. This is more than the schema alone provides, though the description does repeat some schema content.

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 states a specific purpose: producing a full cross-source profile of a US public company in one parallel call. It uses clear verbs ('tell me about', 'brief me on', 'profile') and distinguishes itself from single-pack SEC/XBRL/news lookups. This makes it identifiable against 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?

The description explicitly says to ALWAYS PREFER this over chaining single-pack lookups when the user wants a holistic view. It also notes that private companies yield resolved:false rather than failure. However, it does not explicitly state when to prefer a sibling tool such as compare_entities or deep_research, so the exclusion guidance is slightly incomplete.

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