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

Annotations already cover readOnly/idempotent/destructive/openWorld. The description adds real value beyond them: 'provenance-backed' signals sourcing, and the explicit disclaimer that values are historical observations, not a forecast, recommendation, or real-time quote, is a meaningful freshness/limitation disclosure an agent needs.

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?

Two sentences, front-loaded with the composition of the pack, then the use cases and the disclaimer. Efficient, though 'provenance-backed' is slightly jargon-y filler.

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 usefully enumerates what the pack contains (policy rates, full curve, two headline spreads) and its historical nature. Adequate for a zero-required-param, read-only aggregator, though it doesn't describe return shape or units.

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 description coverage is 100%, so the schema fully documents both the date pattern and the response_format enum. The description adds no syntax or format detail beyond that, so the baseline 3 applies.

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 uses a specific verb ('Combine') and enumerates the exact resource components: H.15 policy/reference rates, the complete nominal Treasury curve, and the 10y-2y/10y-3m spreads. It implicitly distinguishes itself from the single-facet siblings (rate_history, yield_curve, rate_spread) by being the aggregator, though it never names them.

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 explicit trigger phrases ('summarize the current rate environment', 'build a Federal Reserve rates evidence pack') and positions itself as a 'direct-Board macro leg alongside other datasets'. This is clear when-to-use guidance, but it names no alternatives or when-not conditions.

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