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

The description goes far beyond the annotations by disclosing the multi-source fan-out, fallback chains, soft-failure behavior for USPTO patents, expected empty results for FDA products, and the resolved:false private-company path. It explicitly warns that an empty section means 'no data,' not a bug, which is valuable behavioral context.

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 lengthy but dense with necessary information, and it front-loads concrete examples and the core purpose. Each detail about return fields, failure modes, and input forms serves a purpose, though the single-paragraph structure could be better organized for scanability.

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 structure, and it does so thoroughly: it enumerates each returned section, the source behind it, URI format for filings, and the meaning of resolved_from/resolved_to. It also explains fallback behavior and expected empty results, making the tool safely callable.

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 already 100%, so the baseline is 3, but the description adds meaningful clarification: 'type' accepts 'company' or 'ticker' interchangeably, and 'value' can be a ticker, zero-padded CIK, or company name with resolution via SEC EDGAR. This enhances parameter understanding 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 uses specific verbs and a clear resource: 'full cross-source profile of a US public company in ONE parallel call.' It provides multiple query examples and explicitly states this tool should be preferred over chaining single-pack lookups, clearly distinguishing it from narrower siblings.

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 states when to use this tool: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also clarifies acceptable inputs, the meaning of empty sections, and the behavior for private companies, giving an agent clear decision rules.

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