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

No annotations are provided, so the description carries the full burden. It discloses the data source ('ProPublica Nonprofit Explorer'), the scope ('latest 990/990-EZ/990-PF filing, plus 5-year filing history'), and the specific data elements returned. This goes beyond a bare lookup and gives useful context, though it does not mention potential edge cases such as missing filings or 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?

Two concise, front-loaded sentences. The first sentence clearly states the purpose and the data fields, and the second provides the source. No redundant or filler language; every word earns its place.

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 low complexity (one parameter, no output schema), the description is complete. It lists the return values (revenue, expenses, etc.) and the history scope (5-year filing history), which is sufficient for a lookup tool. It doesn't describe the exact JSON structure, but that is not necessary given the context.

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 covers 100% of the single parameter ('ein') with a detailed description including format and examples. The tool description only mentions 'by EIN' without adding any semantic detail beyond the schema. Baseline of 3 is appropriate since the schema does the heavy lifting.

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 with a specific verb ('Get') and resource ('IRS Form 990 financial data for a US nonprofit by EIN'). It enumerates specific data fields (revenue, expenses, assets, liabilities, officer compensation, etc.) and distinguishes itself from sibling tools by explicitly targeting nonprofit tax filings, not corporate financials.

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 clearly implies when to use this tool: when you need IRS Form 990 data for a US nonprofit identified by EIN. It does not explicitly mention alternatives or exclusions (e.g., 'not for for-profit companies'), but the qualifier 'US nonprofit' makes the intended use case unambiguous. More explicit guidance on when not to use it would elevate this to a 5.

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