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

Annotations already declare the tool read-only and non-destructive, lowering the bar. The description adds meaningful behavioral context: it is a single premium call sourced from SEC EDGAR, returns JSON, and costs $0.20 via x402. It does not cover rate limits or auth details, but it goes beyond what annotations alone provide.

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 core purpose is front-loaded and the rest of the description packs useful details—metrics, source, format, and price—into one dense sentence. There is no filler, though the long metric list makes it slightly heavier than necessary.

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 takes on the job of explaining return values and does so at a useful level: it names the metrics compared, per-metric winners, the financial-health verdict, and the 'stronger financial profile' call. Minor operational details like error handling are absent, but they are not critical for this simple two-parameter read-only tool.

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 100%, and the schema already documents that a and b are company tickers or CIKs with examples. The description repeats 'Two tickers or CIKs' but adds no new parameter semantics beyond the schema, so the baseline 3 applies.

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 highly specific action: comparing two public companies head-to-head, and enumerates the exact metrics and verdicts produced. This clearly distinguishes it from single-company finance siblings like finance_company_360 or finance_health_scan, even without naming them.

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 use case is implied: use this tool when you need a side-by-side peer comparison of two public companies on revenue, net income, margins, growth, and financial health. It does not explicitly state when not to use it or name alternatives, so the guidance remains implicit rather than fully explicit.

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