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

The description discloses substantial behavioral detail beyond the annotations: it fans out across many sources, soft-fails on the USPTO patents API, treats empty sections as genuine 'no data', returns resolved:false for private companies, and explains the FDA biologics expectation. No statement contradicts the readOnly/openWorld/idempotent 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 long, but the tool is genuinely complex and the length is mostly earned: it front-loads usage examples and the ALWAYS PREFER guidance, then compresses return fields and source behavior into a compact semicolon-delimited list. A little redundancy with the schema keeps it from a perfect score.

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 so thoroughly: cik, company_name, filings, fundamentals, patents, contracts, FDA products, hiring, news, LEI, and sources_used/sources_failed. It also addresses edge cases like private companies, empty sections, soft-fails, and expected absences of data.

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?

The schema already covers parameter semantics at 100%, so the baseline is 3. The description adds value by confirming 'company' and 'ticker' are interchangeable, providing concrete accepted value shapes, and explaining how a private-company value behaves (resolved:false with a notes line). This is useful but somewhat redundant with the schema.

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 identifies a specific resource and action: building a full cross-source profile of a US public company in one parallel call. It uses multiple concrete user-phrase examples and explicitly contrasts itself with chaining single-pack SEC/XBRL/news lookups, making its scope unambiguous.

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 explicit when-to-use signals ('Tell me about X', 'research Acme', 'brief me on Tesla') and an explicit preference rule: ALWAYS PREFER over chaining single-source lookups when the user wants a holistic view. It also clarifies how private companies are handled, preventing false assumptions about failure.

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