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

Beyond annotations, it discloses the parallel fan-out across sources, soft-fail behavior for patents, expected empty results for fda_products in certain companies, the sources_used/sources_failed contract, and that resolved:false is a defined outcome. These are real behavioral details an agent needs to interpret results correctly.

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 front-loaded with its core purpose and examples, and every sentence carries useful information. However, it is a long single block of text that mixes source lists, return-field descriptions, and input guidance, which could be better structured with headings or a more scannable layout.

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?

For a tool with no output schema and high complexity, it covers all essential context: return fields (cik, company_name, recent_filings, fundamentals, etc.), source-failure behavior, no-data semantics, input variants, and what happens for private companies. An agent has enough to invoke it correctly and interpret its responses.

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 crucial semantics: type and value are interchangeable, value can be a ticker, zero-padded CIK, or company name, and names resolve via SEC EDGAR. This goes well beyond the raw schema and clarifies how the two parameters function together.

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 explicitly states the tool returns a 'full cross-source profile of a US public company in ONE parallel call' and leads with natural-language examples like 'Tell me about X' and 'research Acme.' It also distinguishes itself from chaining single-pack SEC/XBRL/news lookups, making its purpose unmistakable.

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 when-to-use condition: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also tells which input forms are accepted (ticker, zero-padded CIK, company name) and describes the private-company path, giving an agent enough to decide correctly.

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