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

Beyond the readOnly/idempotent annotations, the description discloses the parallel fan-out across EDGAR, XBRL, USPTO, news, and GLEIF, the exact return fields (cik, recent_filings, fundamentals, patents, news, LEI), the 'up to 5' filing limit, the sort order for fundamentals, and even the USPTO API sunset/soft-fail behavior. This is rich, honest behavioral context.

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 longer than ideal but every sentence carries substantive information: example queries, scope, return summary, and key caveats. It is front-loaded with the most important usage cues and then flows into return details. It could be tightened into bullets, but it is not bloated.

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 must explain what the tool returns, and it does so thoroughly: cik/company_name, recent_filings with URIs, 10-K fundamentals, patents with a sunset caveat, news fallback chain, and LEI. Combined with the parameter constraints and alternative guidance, this gives an agent everything needed to invoke the tool and interpret the result.

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 input schema already documents both parameters at 100% coverage, so the baseline is 3. The description adds value by giving concrete examples ('AAPL', '0000320193'), emphasizing the zero-padded CIK format, and reiterating that names are not supported. This goes slightly beyond the schema but does not add deep new semantic detail for every parameter.

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 user phrasing ('Tell me about X', 'research Acme') and states a specific action: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from sibling tools by naming 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups' and by pointing to resolve_entity for name-only inputs.

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 explicitly tells when to use the tool ('when the user asks for a holistic view') and when not to use it ('names not supported — use resolve_entity first'). It also frames this as the preferred alternative to chaining multiple single-purpose lookups, giving practical decision guidance.

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