datagolf_outrights

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds significant value by disclosing the auth requirement ('needs your own key in DATAGOLF_KEY') and the response structure (event_name, last_updated, books_offering, odds). No contradiction with annotations.

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 is compact and well-structured: one sentence for purpose, a return block, and one for authentication. Every element earns its place, with no redundancy or fluff.

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 no output schema, the description includes a detailed return structure, the current-event scope, the number of sportsbooks, and the auth requirement. This is complete for a read-only odds tool with annotations already covering safety.

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?

Schema coverage is 100%; all four parameters have descriptions, enums, and defaults in the input schema. The description's mention of 'win / top-N / make-cut' aligns with the market enum but does not add meaningful details beyond the schema, so the baseline 3 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?

The description clearly states that the tool returns 'Outright (win / top-N / make-cut) odds for the current event across ~13 sportsbooks, plus Data Golf's model line.' This identifies the resource (outright odds), scope (current event), and differentiates it from historical or matchup tools.

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 provides clear context: it is for 'the current event' and focuses on outright odds, implicitly distinguishing it from historical or in-play tools. However, it does not explicitly name alternative tools 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.