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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses the full fan-out source list, the exact return sections (filings, fundamentals, patents, contracts, fda_products, hiring, news, LEI), and the sources_used/sources_failed mechanism. It explicitly pre-empts misinterpretation by saying an empty section is a real 'no data', not a bug, and describes GDELT→GNews fallback and name resolution behavior. No contradiction with the 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 front-loaded with user intents and the core 'ONE parallel call' value proposition before the dense source/return list. Every clause carries useful information, so there is no filler. The lack of line breaks or section headers makes it harder to scan, but for a tool this complex the density is justified.

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 in detail: cik/company_name, resolved fields, up-to-5 filings with URI templates, fundamentals fields, patents, contracts, FDA products, hiring, news, and LEI. It also explains sources_used/sources_failed, no-data semantics, and the private-company behavior, leaving no major ambiguity for an agent selecting or invoking the tool.

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%, so the baseline is 3; the description then adds meaningful nuance: examples for ticker/CIK/name, zero-padded CIK expectation, name resolution via SEC EDGAR, type='company'/'ticker' interchangeability, and resolved_from/resolved_to when a name is passed. That pushes it above baseline, though much of it repeats or slightly extends the schema descriptions rather than replacing them.

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 phrasings ('Tell me about X', 'brief me on Tesla') and a specific promise: 'full cross-source profile of a US public company in ONE parallel call.' It names the resource (US public company) and the action (cross-source profiling), which clearly distinguishes it from single-source or comparison tools. The line against chained single-pack SEC/XBRL/news lookups further clarifies its distinct role.

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 says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving both the trigger condition and the alternative to avoid. It also explains accepted input shapes and the private-company fallback (resolved:false with notes), so an agent knows what to expect for edge cases. It could name sibling tools like deep_research or compare_entities, but the guidance is already unambiguous for the intended use case.

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