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

Beyond the readOnly/idempotent annotations, it discloses fan-out behavior across multiple APIs, the return structure, and two failure/fallback behaviors: patents 'soft-fails until reactivated' after USPTO sunset, and news uses 'GDELT→GNews fallback.' It also states that names are not supported, preventing false expectations.

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 but well-organized: examples first, then purpose, usage guideline, return details, and parameter format. Every sentence contributes critical information—no filler—and the structure front-loads the most important usage guidance.

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?

There is no output schema, but the description enumerates all return fields (cik, company_name, recent_filings with URIs, fundamentals, patents, news, LEI), making the tool's output fully self-describing. It also covers input constraints, usage context, and behavioral nuances, making it complete for an agent.

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 coverage is 100%, and the description repeats the value format (ticker or zero-padded CIK) but adds no substantive new meaning beyond the schema. It does provide concrete examples ('AAPL', '0000320193') and the 'names not supported' constraint, but these are also present in the schema. Baseline 3 applies because the schema fully describes the parameters.

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 multiple natural-language examples and immediately defines the tool as 'full cross-source profile of a US public company in ONE parallel call.' It explicitly lists the data sources (SEC EDGAR, XBRL, USPTO, news, GLEIF) and the returned fields, clearly distinguishing it from single-source lookups like the sibling SEC/news tools.

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 provides explicit guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also gives an exclusion for name inputs with a clear alternative: 'names not supported (use resolve_entity first if you only have a name).'

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