screen_public_companies

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

With no annotations, the description carries the full burden. It discloses a key behavioral trait: 'Every record carries a verify_url to the filing the figure came from.' It also establishes the scope (all US public companies) and implies read-only screening. It does not mention rate limits or error handling, but for a read-oriented tool these are not critical. The description adds meaningful context beyond what annotations would 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 description is concise: the first sentence states the purpose, the second paragraph gives concrete use cases, and the third adds one valuable detail (verify_url). It is front-loaded and every sentence earns its place. No wasted words or repetition of schema information.

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 (7 params, no output schema), the description is fairly complete. It explains the tool's purpose, gives examples, and hints at output structure ('Every record carries a verify_url'). It doesn't detail all return fields, but that might be implied by the metric and ranking. The description is adequate for an agent to understand when and what to expect.

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 schema covers 100% of parameters with descriptions, so the baseline is 3. The tool description does not add extra parameter semantics beyond what's already in the schema. The examples like 'revenue over $100 billion' reiterate the metric and period parameters but do not add new meaning. Therefore, it does not exceed the baseline.

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 tool's function: 'Rank every US public company by a financial metric.' This is a specific verb+resource. It also distinguishes from siblings by emphasizing cross-company comparisons ('this compares all of them at once') and contrasts with SEC.gov/EDGAR. This differentiates it from company_financial_history, which likely focuses on individual company data.

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 gives clear context on when to use it: 'Answers questions sec.gov structurally cannot: which companies had revenue over $100 billion last year...' It implies this is for cross-company screening. However, it does not explicitly mention when not to use it or name alternatives like company_financial_history for single-company history, so it stops short of explicit exclusion. This earns a 4, not a 5.

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