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

With no annotations the description carries the full burden, and it delivers meaningful behavior: auto-resolution to the current market instance, roll-forward on resolution, and a response that adds current_slug and rolls_to_next_at. It also exposes transport and cost (HTTP GET, $0.02 via x402), though permissions and rate limits 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?

Front-loaded with 'Live probability:' and the HTTP/cost block is clean, but the recurring question is stated twice in near-identical words, which is wasted space in an otherwise compact definition.

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-argument GET with no output schema and no annotations, the description covers the behavioral essentials (auto-resolution, roll-forward, extra response fields) and the endpoint/cost. It is complete enough to call correctly, with only auth and return-shape details left implicit.

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 there is nothing for the description to disambiguate; the baseline of 4 applies. The schema is trivially complete and the description introduces no parameter confusion.

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 verb and resource ('Live probability' for a precisely named recurring question, 'the next major hurricane (Cat 3+) make US landfall'). It is clearly a distinct member of the probability_evergreen_ family, though it does not name or route against a sibling tool by name.

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?

Usage is implied by the 'stable evergreen URL... always about the next occurrence' framing, which signals when this beats a specific dated market. But it never explicitly says when to use this versus probability_get, probability_search, or the other evergreen variants, and gives no exclusions.

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