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

Annotations already establish readOnly/openWorld/idempotent behavior, and the description adds substantial context: the exact sources fanned out, what each returned section represents, that empty sections are real 'no data' not bugs, and that private companies return resolved:false with a notes line. It also documents soft-fail behavior for the USPTO source.

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 it is densely packed with necessary behavioral detail for a multi-source tool with no output schema. It front-loads the core purpose and usage rule before enumerating sources and return fields. A little more structural formatting would help, but every clause carries operational value.

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 thoroughly: cik, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, plus sources_used/sources_failed. It also covers input variants, edge cases, and failure semantics. Nothing critical is missing for an agent to invoke this correctly.

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 adds meaningful behavior beyond the schema by explaining that type accepts 'company' or 'ticker' interchangeably, that value can take three different shapes, and that names resolve via SEC EDGAR with resolved_from/resolved_to tracking. This is useful but partially overlaps with the schema text.

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 trigger phrases and states the exact job: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from single-pack SEC/XBRL/news lookups and from siblings like compare_entities or resolve_entity by describing its holistic, multi-source fan-out behavior.

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 gives explicit when-to-use examples ('Tell me about X', 'research Acme', 'brief me on Tesla') and states 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also explains the private-company and no-data edge cases so the agent knows what to expect.

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