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

Annotations only declare safe read-only behavior; the description adds substantial behavioral detail beyond that: it NEVER substitutes periods, NEVER returns 0 for missing data, NEVER lets YTD answer quarterly, and NEVER converts currency. It also discloses data provenance, status semantics, and response contents including concept, accession, restatement trail, and contract version.

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 dense and fairly long, but it is front-loaded with the core purpose and examples before moving to behavioral guarantees and status semantics. Nearly every sentence adds distinctive information, though some stylistic repetition and capitalization could be trimmed without losing meaning.

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?

Despite having no output schema, the description compensates by detailing exactly what every answer carries, enumerating all non-answer statuses, and describing source behavior and restrictions. Combined with the fully documented 9-parameter schema, an agent has enough context to select and invoke the tool 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?

The input schema has 100% parameter description coverage, so the schema already explains period, company, attribute, and other parameters. The description reinforces key ideas like filer-defined fiscal years and the ambiguity handling for company names, but it mostly restates or complements rather than adding substantially new parameter-level meaning.

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?

States a specific resource and scope: 'financial facts for a US public company for an EXPLICITLY NAMED reporting period,' with concrete examples. It also differentiates itself from entity_profile / get_company_financials by emphasizing deterministic period-matched facts rather than latest figures.

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?

Explicitly instructs 'PREFER OVER entity_profile / get_company_financials whenever the period matters' and explains why those alternatives may return the wrong period. It also enumerates non-answer statuses such as unavailable, unsupported, ambiguous, and conflicting, which clarify when this tool is and isn't appropriate.

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