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

With no annotations, the description carries the full burden and does well: it discloses evergreen semantics, auto-resolution to the current instance, roll-forward on resolution, and the added response fields current_slug and rolls_to_next_at. It also exposes the transport and cost (GET /v1/evergreen/..., $0.02 via x402), which is a real behavioral trait. It stops short of error/rate-limit or freshness behavior, so not a 5.

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 and the endpoint/billing footer is a reasonable convention, but the question 'Will the Fed cut rates at its next FOMC meeting?' is stated twice in consecutive sentences, which is pure redundancy in an otherwise short description.

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 no-argument tool with no output schema, the description covers what is needed: what question it answers, that it always targets the next occurrence, and the two non-standard response fields. Missing only freshness/polling expectations, which would round it out.

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?

The tool takes zero parameters, so the baseline is 4 per the rubric; there is nothing for a caller to supply. The description instead usefully frames the return payload by naming the two extra fields, though that is return rather than input semantics.

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 a specific resource and outcome: the live market probability that the Fed cuts rates at its next FOMC meeting. The 'cut' framing and the evergreen/roll-forward explanation let an agent distinguish it from the sibling probability_evergreen_fed-next-meeting-hike and from generic probability_get lookups without opening a schema.

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 implicitly conveys when this is the right tool — a recurring question you want auto-rolled forward rather than a specific dated market — but never states that explicitly or names an alternative (e.g. probability_board_fed, probability_calendar_fed, or the hike counterpart). The agent must infer the selection rule.

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