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

Beyond the supplied annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=false), the description adds crucial billing context: $0.01/call via x402 USDC or card key, first 25 free, failed calls free. It also explains that repeats are not free, aligning with idempotentHint=false. It does not describe rate limits or full response shape, so a 4 is appropriate.

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 definition is front-loaded with the core resource and data elements, then usage, then pricing. It is dense but every sentence contributes: dataset identity, fields, use cases, example, pricing, and safety note. Slight redundancy in repeating the date range and default, but overall efficient.

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 read-only single-parameter tool with full schema coverage and clear annotations, the description is complete: it states what is returned, when to use it, the cost model, and that the snapshot’s record date appears in the answer. No output schema exists, yet the description adequately explains the return contents.

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 coverage is 100%, and the schema already documents `days` as 1-365 with default 30. The description repeats the range and adds an example (`days=30`), but does not add meaningful semantics beyond what the schema provides. Baseline 3 is correct when 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 names the exact dataset (Treasury Debt to the Penny) and specifies the returned quantities: total public debt outstanding, debt held by the public, intragovernmental holdings, changes over 1/30/365 days, and a daily history. It clearly distinguishes this from siblings like econ_gdp, econ_inflation, and econ_treasury_rates by focusing exclusively on national debt figures.

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?

It explicitly states when to use it: 'when an agent needs the current US federal debt figure, its trend, or a daily series for a chart or brief.' The example `days=30` reinforces the typical call. However, it does not name an alternative or state when not to use this tool, which keeps it from a 5.

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