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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral context beyond this: it enumerates the multiple data sources fanned out, explains that sources_used/sources_failed indicate real gaps rather than bugs, notes that a private company yields resolved:false with an explicit notes line, and clarifies expected empty sections for fda_products. This informs an agent about response semantics in a way annotations cannot.

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 information-dense, front-loading example user phrasings and the 'ALWAYS PREFER' directive before diving into data sources and return fields. Every sentence carries meaningful detail, though a single dense paragraph with semicolons is slightly harder to parse than structured bullets. It is appropriately sized for a tool with this complexity.

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 convey return structure, and it does: cik, company_name, resolved_from/resolved_to, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/sources_failed. It also covers input variants, name resolution, private-company behavior, and expected empty data sections. For a complex multi-source read-only tool, nothing essential is missing.

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 ticker/CIK/company-name resolution and the interchangeable type enum. The description adds concrete examples ('AAPL', '0000320193', 'Moderna'), restates that type values are interchangeable, and clarifies that names resolve via SEC EDGAR's company-name match. This is valuable reinforcement without fully replacing the schema, so it earns above 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?

The description states a specific action — producing a full cross-source profile of a US public company in one parallel call — with concrete example phrasings like 'Tell me about X' and 'brief me on Tesla'. It clearly distinguishes itself from chaining single-pack SEC/XBRL/news lookups, so an agent can tell this tool apart from siblings like query_resource or search_within.

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 to ALWAYS PREFER this tool over chaining single-pack lookups when a holistic view is requested, names the alternative pattern it replaces, and gives a rich set of trigger phrases. It also defines when it should not be used (private companies return resolved:false with notes) and clarifies that type accepts 'company' or 'ticker' interchangeably, leaving no ambiguity about when to choose this tool.

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