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

Annotations already indicate read-only, open-world, idempotent, non-destructive behavior, and the description adds substantial behavioral detail beyond that: 'empty section is a real "no data", not a bug', `sources_used`/`sources_failed` semantics, resolved:false handling for private companies, and the interchangeability of `type` values. This is exactly the kind of runtime behavior an agent needs to interpret results correctly.

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 front-loaded with the core purpose and a strong routing directive, then covers inputs, outputs, and edge cases in a logical order. It is long and dense, with a run-on fan-out sentence, but every sentence contributes meaningful information and none is 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?

Given the tool's complexity, the absence of an output schema, and the broad multi-source behavior, the description is remarkably complete. It enumerates the data sources, key returned fields, URI format for filings, the meanings of `sources_used`/`sources_failed`, input flexibility, and failure modes. An agent has enough information to select and invoke this tool correctly without needing to inspect further documentation.

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?

The input schema already provides 100% coverage of the two parameters, including the exact accepted value shapes. The description adds value by giving examples, reinforcing that `value` may be a ticker, CIK, or company name, and explaining name resolution and private-company edge behavior. That goes beyond the schema without being redundant.

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 an explicit, specific purpose: 'full cross-source profile of a US public company in ONE parallel call.' It is packed with concrete invocation examples ('research Acme', 'brief me on Tesla') that make the tool's intent unmistakable. It also differentiates it from single-source SEC/XBRL/news lookups as the holistic alternative.

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?

The description explicitly says to prefer this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. It also clarifies acceptable inputs (ticker, CIK, company name) and the private-company fallback, so an agent knows exactly when this tool applies and how to invoke it.

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