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

Annotations already convey read-only/idempotent behavior, but the description adds substantial context: it fans out across multiple sources, uses soft-fail semantics for the patents API sunset, treats expected empty FDA results as non-errors, and explains that sources_used/sources_failed distinguish real no-data from bugs. This goes well beyond the structured 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 front-loads purpose and the ALWAYS PREFER rule, then provides a dense but useful breakdown of sources, return sections, and failure modes. It is long, but nearly every clause adds behavioral context; bullet structure would improve scannability, but it is not padded with filler.

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 present, the description takes on the burden of explaining return values, and it largely succeeds: it enumerates cik, company_name, resolved_from/resolved_to, recent_filings, fundametals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also covers edge cases like private companies and expected empty sections, making it sufficiently complete for a complex multi-source 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 description coverage is 100%, and the schema already documents that both type values are interchangeable and that value can be a ticker, CIK, or company name. The description repeats these examples and adds resolved_from/resolved_to behavior, but that is output behavior rather than new parameter semantics. Therefore it stays at the baseline 3.

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?

Opens with concrete user phrasings and states the core function: 'full cross-source profile of a US public company in ONE parallel call.' It clearly identifies the resource and scope, and distinguishes itself from narrower single-source lookups by explicitly saying it should be preferred for holistic views.

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?

Gives an explicit when-to-use rule: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also defines acceptable input forms and what happens for private companies, so an agent knows both when to invoke it and what edge cases to expect.

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