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

Beyond annotations (readOnly, idempotent, etc.), the description discloses important limitations: it is 'reference math' only, does not include demon/goblin modifiers, and assumes independent legs. These caveats add behavioral context that the annotations do not capture, and there is no contradiction with the readOnlyHint.

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?

Every sentence earns its place: the opening phrase sets expectations, the return content is listed, the optional parameter is explained, examples are included, and the caveats are clearly marked with 'NOTE.' The structure is front-loaded with the core function and progressively adds detail without redundancy.

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?

Given the tool has one optional parameter, no output schema, and several sibling tools, the description is quite complete. It explains the return values (payout schedule, breakeven, expected_return, is_plus_ev) and important assumptions. It could be slightly more precise about the exact structure of the returned payout schedule, but overall it covers the essential context.

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 schema already documents leg_win_prob with 100% coverage. The description adds a concrete example value ('0.58') and clarifies that is_plus_ev represents the slip-level breakeven, which is not obvious from the schema alone. This adds meaningful semantic value beyond the schema.

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 clearly states the tool returns PrizePicks Power Play and Flex Play payout schedules for 2-6 legs plus per-leg breakeven probabilities. It uses specific verbs like 'Returns' and 'Pass' and mentions unique resources (Power Play, Flex Play) that distinguish it from sibling tools focused on odds, events, or scores.

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 'Useful for' section provides concrete example queries, giving clear context on when to use this tool. It does not explicitly mention exclusions or alternative tools, but among the siblings there are no other payout-specific tools, so the guidance is sufficient.

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