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

The description goes beyond the readOnlyHint/idempotentHint annotations by disclosing specific behavioral traits: returns both canonical series, component values, percentage-point and basis-point spreads, pagination, provenance, and exact hosted coverage. It also specifies 'aligned business dates,' which informs the data returned. There is 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 concise—five sentences with no fluff—and front-loads the core action and return values. The usage examples, alias note, and disclaimer each add distinct value. Every sentence earns its place, and the structure is logical: what it does, what it returns, when to use it, and an important caveat.

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 that there is no output schema, the description adequately explains return values (canonical series, component values, spreads, pagination, provenance, coverage). With readOnly annotations already covering safety, the description provides all necessary details for an agent to call the tool correctly, including aliases and business-date alignment. No critical information is missing.

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 all seven parameters are documented. The description adds meaningful semantics beyond the schema by stating that Treasury aliases like '10y' and '2y' are accepted for series_a and series_b, and by explaining the 'aligned business dates' context that affects date parameters. This is valuable supplementary information that aids correct invocation.

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 begins with the specific verb and resource: 'Calculate a time series of one Federal Reserve Board H.15 rate minus another on aligned business dates.' It clearly defines the operation (spread calculation) and distinguishes from sibling tools that handle single rate history or yield curves. The inclusion of concrete examples like '10-year minus 2-year Treasury spread' and 'prime minus fed funds' further clarifies the tool's scope.

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 provides explicit when-to-use guidance via 'Use this for...' with three concrete examples, and explicitly states 'Not a forecast or trading signal,' which is an exclusion. However, it does not directly contrast with sibling tools like fed_board_h15_rate_history or fed_board_h15_yield_curve, so while the usage is clear, it lacks an explicit when-not-to-use statement referencing alternatives.

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