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

With no annotations, the description carries the whole burden and does well: it discloses the roll-forward lifecycle behavior, that the response augments the standard probability shape with current_slug and rolls_to_next_at, and adds the transport/pricing details (GET endpoint, $0.02 via x402). It omits any auth/rate-limit detail beyond the payment mention.

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 with the core purpose, but the question 'Which party wins the next US presidential election?' is stated twice in adjacent sentences, which is pure redundancy. The lifecycle and response details are 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?

No output schema exists, so the description usefully compensates by describing the response shape (standard probability plus current_slug and rolls_to_next_at). Combined with the lifecycle explanation, an agent has enough to call it correctly, though it could note the probability payload fields.

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 and schema coverage is 100%, so there is nothing for the description to disambiguate. Baseline 4 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?

States a specific resource (live probability for which party wins the next US presidential election) with a clear action. The evergreen framing distinguishes it from the generic probability_get/probability_search siblings and from other evergreen markets like house-control or senate-control.

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?

Explains the context that makes this tool the right pick for a recurring question ('auto-resolves to the current market instance and rolls forward on resolution, so the answer is always about the next occurrence'). It does not explicitly name alternatives or state when-not to use it, so it stops short of a 5.

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