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 the auto-resolution/roll-forward behavior, the extra response fields (current_slug, rolls_to_next_at), and the transport (GET, $0.02 via x402). It stops short of stating read-only/reversibility guarantees or rate limits, but the behavioral picture is substantially richer than the structured fields.

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 mostly efficient, with the bracket metadata (HTTP verb, price, docs URL) earning its place. Minor redundancy: the question 'Who wins the next NBA Finals?' is stated twice in the opening two sentences.

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 0-param tool with no output schema, the description covers what the tool returns (standard probability shape plus current_slug and rolls_to_next_at), how it behaves over time, and how to reach it. Nothing essential is missing.

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?

Zero parameters, so the baseline is 4. The description correctly implies no inputs are needed and instead characterizes the output additions, which is the right use of the space.

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: Who wins the next NBA Finals?') and explains the evergreen mechanism that differentiates it from a dated market tool. The topic-specific naming plus the evergreen semantics let an agent distinguish it from siblings like probability_evergreen_superbowl-winner or probability_board_sports-nba.

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?

The description gives clear context for use — it is the stable URL for a recurring question that auto-resolves to the current market instance and rolls forward, so the answer is always about the next occurrence. It does not, however, explicitly name an alternative (e.g. probability_get or probability_board_sports-nba) or state when-not to use it.

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