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

Annotations already declare readOnly/idempotent/non-open-world, so the bar is lower, yet the description adds real value: 'quarterly figures bundled with the server, not live quotes' sets data-freshness expectations, and 'Averages across banks, never any one lender' clarifies the aggregation semantics. It could still note the data vintage/as-of date handling, but the extra context is substantive.

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?

Front-loaded with the data source and what is returned, then the optional comparison, then usage examples. Every sentence carries information, though the final example-query sentence is slightly long and could be trimmed without loss.

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?

With no output schema, the description correctly carries the return semantics ('change from the previous quarter and from a year earlier', dollar gap on comparison) and the optional-input coupling (comparison needs loan_type). It is essentially complete for a read-only reference lookup, with only minor gaps around data vintage.

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% so baseline is 3, but the description goes beyond the schema by explaining the comparison mode (offered rate vs. average, 'gap in dollars') and enumerating the loan kinds in prose matching the enum. It doesn't add per-parameter detail on amount/months formatting beyond what the schema states.

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 states a specific verb and resource: 'The latest Federal Reserve (G.19) average interest rates at commercial banks' for named loan products. It scopes it against siblings with 'Averages across banks, never any one lender', which distinguishes it from lender/offer-specific tools like compare_loan_offers and refinance_check.

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 gives concrete when-to-use triggers ('what is the average car loan rate', 'have personal loan rates gone up', 'is 9% high for a car loan') and notes the optional comparison flow. It does not explicitly exclude or route to a named alternative (e.g., use compare_loan_offers for multiple offers), so it stops short of a full when/when-not guide.

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