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

The read-only and non-destructive annotations are supplemented with meaningful behavioral details: the tool returns a long-run average comparison and above-average flag, is atomic and priced at $0.02 USDC, and provides a post-quantum signed settlement receipt with a verification URL. No contradiction with the annotations.

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 appropriately short and front-loads the core metric and use cases. Minor redundancy, such as restating the source ('Source: FRED / BEA') and listing the $0.02 price twice, prevents a perfect score.

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 no-parameter, read-only, non-destructive data tool with no output schema, the description is complete: it states the data point, source, analytical output, when to use it, cost, and verification mechanism. An agent has enough context to select and invoke the tool correctly.

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 zero parameters and full schema coverage, the baseline is 4. The description adds context about the output (comparison and flag) that helps an agent understand what the no-argument call returns, even though there is no parameter syntax to clarify.

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 specific resource (BEA personal saving rate from FRED) and the added analysis (long-run average comparison and above-average flag), which distinguishes it from most sibling benchmark tools. However, it does not explicitly name a sibling to contrast against, so it misses the full 5.

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?

Explicit use cases are provided: assessing household balance sheet health, consumption durability, and macro recession risk. This is clear guidance on when to call the tool, but there is no mention of alternatives or when not to use it, so it does not reach 5.

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