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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds a valuable caveat about cache lag ('cache may reflect prior quarter — verify against latest SEC filing for time-sensitive analysis'). It also discloses the data source (SEC EDGAR synced filings), which is beyond the annotations and helps set expectations about data freshness.

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 four sentences and front-loaded with the primary use case, then the return value, a caveat, and an illustrative example. Each sentence earns its place, though the example with specific numbers is slightly verbose for a tool definition.

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?

For a single-parameter, read-only tool with no output schema, the description is fairly complete: it states what data is returned, the source, the freshness caveat, and gives a concrete example. It does not cover all edge cases (e.g., parameter format, non-US companies), but given the tool's simplicity, the essential context is provided.

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?

With schema description coverage at 0%, the description must compensate for the undocumented 'company_name' parameter, but it only provides an example ('Salesforce FY2024') without explaining whether to pass a ticker, legal name, or how to handle fiscal years. The example could be misinterpreted as including the fiscal year in the parameter, but the schema only allows a single string for company_name.

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 clearly states the verb ('Returns') and the resource ('SEC EDGAR financial statement data — income statement, balance sheet, and key ratios') for public company financials. It distinguishes itself from sibling tools by focusing on public companies and SEC filings, and even includes specific use cases (comparable company analysis, M&A due diligence, investor brief).

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 'Use when pulling public company financials for a comparable company analysis, M&A due diligence, or investor brief,' giving clear context for when to use this tool. It does not name alternative tools or state when not to use it, but the use cases are specific enough to imply differentiation from other data sources.

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