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

Even with readOnlyHint, idempotentHint, openWorldHint, and destructiveHint already in annotations, the description adds substantial behavioral context: the USPTO PatentsView API sunset and soft-fail behavior, FDA results being limited to biologics, empty sections being a real 'no data' rather than a bug, and sources_used/sources_failed semantics. This goes far beyond what annotations alone convey.

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 nearly every clause adds necessary information for a tool with no output schema and many return sections. It is front-loaded with user-phrasing examples and the core purpose, and the later sections are organized by source. The length is earned, though it could benefit from light formatting to make it 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 full burden of explaining return values, and it does: it enumerates cik/company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also covers error-like outcomes (private companies, empty sections, API sunset), making it complete for an agent to invoke confidently.

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?

Although schema coverage is 100%, the description adds meaning beyond the schema: it clarifies that 'company' and 'ticker' are interchangeable, explains that value can be a ticker, CIK, or name, and specifies how name resolution works via SEC EDGAR. It also gives concrete examples and describes the private-company resolved:false behavior.

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 concrete natural-language triggers ('Tell me about X', 'research Acme', 'brief me on Tesla') and then states the exact function: 'full cross-source profile of a US public company in ONE parallel call.' It clearly names the resource (US public company) and the scope (multiple cross-sources), and distinguishes itself from chaining single-pack lookups.

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 gives an explicit directive: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also handles exclusions and edge cases: private companies return resolved:false rather than a bare failure, and person/place queries are marked as coming soon. This is clear when-to-use and when-not-to-use guidance.

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