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

Annotations already mark readOnly/openWorld/idempotent, and the description adds substantial behavioral context: fan-out across SEC, XBRL, USPTO, USAspending, FDA, DOL, GDELT/GNews, GLEIF; per-section return semantics; source_used/sources_failed; empty sections as real no-data; USPTO sunset soft-fail; and resolved:false for private companies.

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 but every part earns its place given the tool's complexity. The core purpose is front-loaded, followed by input rules and return-section details. It could be more readable with bullets or section labels, but it is not bloated or irrelevant.

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 and high multi-source complexity, the description thoroughly inventories every return section, explains expected no-data cases (e.g., fda_products), documents failure handling, and covers all accepted input shapes. Nothing essential is missing for an agent to invoke this tool correctly.

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?

While schema coverage is 100%, the description adds genuine meaning beyond the schema: type='company' and 'ticker' are interchangeable, value may be a ticker, zero-padded CIK, or company name, names resolve via SEC EDGAR, and private-company input yields resolved:false with an explicit notes line.

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?

Opens with concrete user phrasings ('Tell me about X', 'brief me on Tesla') and then states the action: 'full cross-source profile of a US public company in ONE parallel call.' This clearly identifies the verb, the resource, and the scope, and distinguishes it from narrow lookup or chaining tools.

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?

Gives an explicit routing rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also details accepted input forms and the private-company fallback, so an agent knows when this tool can satisfy a request and what happens if it cannot.

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