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

Annotations already declare readOnly/openWorld/idempotent non-destructive. The description goes far beyond by detailing the fan-out across sources, the meaning of empty sections (real 'no data' not bugs), the USPTO PatentsView sunset soft-fail, the expected empty FDA products for small-molecule companies, and the return of sources_used/sources_failed. This is rich behavioral context not present in 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 every sentence adds value—trigger examples, fan-out list, return fields, caveats, and edge cases. It front-loads the purpose and usage, then structures the rest with semicolons. It could be tightened, but the density justifies its length for a complex tool.

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 burden of explaining return structure, and it does: it lists all key fields (cik, company_name, recent_filings, fundamentals, patents, etc.), explains sources_used/failed, and covers behavioral edge cases like private companies and empty FDA sections. An agent has everything needed to interpret and call the tool correctly, with no major gaps.

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 description coverage is 100% and already documents both `type` and `value` with the same interchangeability and accepted shapes. The description restates that 'type' accepts either value and mentions name-resolution via SEC EDGAR, but adds little beyond the schema. With full coverage, baseline 3 is appropriate; the restatement is helpful but not novel.

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 precise verb+resource: 'full cross-source profile of a US public company' via one parallel call. It explicitly lists example triggers ('Tell me about X', 'research Acme') and distinguishes itself from chaining single-pack lookups, making its purpose unambiguous and differentiated from siblings like deep_research or resolve_entity.

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 concrete trigger phrases, explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' and covers edge cases like private companies (resolved:false with a notes line). This provides clear when-to-use and implicitly when-not-to-use guidance, though it could name an alternative tool explicitly (e.g., for single filings).

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