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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful context: the SEC EDGAR aggregate source, the Sloan accruals academic model, and per-call pricing, but it doesn't disclose output format, update cadence, or rate limits. This is adequate but not rich.

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?

Four short sentences with the core deliverable front-loaded and the source, audience, and price in logical order. No filler, though pricing could arguably live outside the description.

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 low-complexity, read-only benchmark lookup with one required enum parameter, the description covers what it returns, the data source, the intended use case, and cost. The main gap is that the optional revenue_recognition_model parameter is not explained, but the schema's enum values are self-explanatory and no output schema exists to demand more.

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 0%, so the description needed to carry the parameter burden. It maps 'sector' with 'by sector' and loosely signals revenue recognition via the metric name, but it never explains the optional revenue_recognition_model parameter or how selecting a model changes results. The enum values are left entirely to the schema.

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 names a specific deliverable — earnings quality and financial statement risk benchmarks — and lists the exact metrics (accruals ratio, cash conversion, revenue recognition risk) and the key dimension (by sector). This is specific enough to distinguish it from the many other benchmark tools in the sibling list.

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 names the target users and scenario: CFOs, auditors, and analysts assessing financial reporting risk before M&A or investment. It doesn't explicitly rule out alternatives, but it gives clear context for when the tool is appropriate.

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