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

No annotations exist, so description must carry full burden. It doesn't explicitly state this is a read-only operation or discuss side effects, authentication needs, or data freshness. The description adds value by explaining what returns, but lacks explicit safety or behavioral disclosures.

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?

Three sentences, front-loaded with purpose, then outputs, then usage advice. No fluff, every sentence 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 no parameters and presence of output schema, the description adequately explains the return values and usage context. It could detail update frequency, but for a simple getter it's sufficiently complete.

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 0 parameters and 100% schema coverage, the description adds no parameter info but doesn't need to. Baseline for 0 params is 4. The description focuses on output, which is appropriate.

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 gets live interest rates from the Federal Reserve (FRED), listing specific rates and mentioning cap rate calculation. This distinguishes it from siblings like 'get_cre_market_data' or 'get_inflation_data' which cover different domains.

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 to use it 'BEFORE any DCF model or loan underwriting', providing clear context. It also notes these are real-time numbers Claude cannot access, but doesn't mention when not to use it or give alternatives.

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