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

With no annotations, the description carries the full burden and does substantial work: it discloses the paid-call model ($0.02 USDC on Solana), the fixed-snapshot data vintage, the null-result behavior when either tenor was unpublished, and the source feed and its redistribution terms. The main omission is any statement of what happens on dates outside the range (error vs. empty) and whether all pairs are always returned together.

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?

It is a single dense, run-on sentence of roughly 120 words that mixes pricing, output shape, null semantics, provenance, licensing, and date bounds without paragraph or bullet structure. The lead is well front-loaded with price and return payload, but the licensing clause ('commercial redistribution') does little for an agent deciding how to invoke the tool.

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 one-optional-parameter tool with no output schema and no annotations, the description supplies the return semantics (percentage-point spreads per named pair, null when a tenor is missing), the valid date window, the default, and the data vintage. Only the exact response envelope (field names, ordering, error behavior) is left undefined, which is a minor gap for a tool this simple.

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% for the single optional date parameter, so the schema already defines the format and default. The description adds value by restating the accepted window and default snapshot date in the same breath as the payload, tying the parameter to the returned data rather than repeating field names verbatim.

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: it returns interest-rate spreads, in percentage points, between listed tenor pairs for a requested date. The tenor pairs are enumerated, so an agent knows exactly what output to expect. It never names or contrasts itself with the obvious siblings (rates_curve, rates_history), so differentiation is left to inference.

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?

Usage is implied rather than stated: the price-per-call framing suggests batching all pairs into one call, and the snapshot range plus default date tell the agent what inputs are valid. There is no explicit statement of when to choose this over rates_curve or rates_history, and no exclusion guidance beyond 'dates after 2026-10-09 are not covered'.

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