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 that the tool auto-resolves to the current market instance, rolls forward on resolution, and adds current_slug and rolls_to_next_at to the standard response. It also surfaces transport and cost (HTTP GET, $0.02 via x402) and a docs link, though rate limits and error behavior are unstated.

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 restates the same question twice ('Live probability: Will the US enter a recession this year?' and then 'a recurring question: Will the US enter a recession this year?'), which is pure redundancy. The remaining content is front-loaded and useful, but the duplication costs it.

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 zero-param, no-output-schema, no-annotation tool, the description supplies the rolling-instance semantics, the two added response fields, cost, and docs. An agent has enough to call it correctly; only return-shape detail and error handling are absent.

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, which is the baseline-4 case; there is nothing for the description to disambiguate. The schema's additionalProperties:false and 100% coverage mean no semantic gap exists.

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?

Names a specific verb and resource ('Live probability: Will the US enter a recession this year?'), so the agent knows exactly what it fetches. However, it never distinguishes itself from the ~26 sibling probability_evergreen_* questions or from probability_get, leaving the agent to infer it must pick by slug from the name alone.

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?

'Stable evergreen URL for a recurring question' plus the roll-forward behavior implies the use case: call this when you want the recurring question rather than a fixed market instance. But no alternative is named and there is no explicit when-not-to-use, so the guidance stays implied.

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