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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety behavior is covered. The description adds meaningful context beyond annotations: 2-credit cost and market-information handling restrictions. It does not discuss auth or error behavior, but it adds useful operational constraints.

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 front-loaded with the use case and scope, then gives the sibling alternative, cost, and usage constraints. Every sentence carries useful information with no filler or repetition.

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?

With an output schema and annotations already present, the description covers the remaining critical context: scope, returned market data, alternative tool routing, cost, and market-information constraints. Nothing essential for correct invocation 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?

Schema description coverage is 100%, so the schema already documents all three parameters. The description repeats the days default/range but adds no extra meaning for team or league beyond what the schema provides, making the baseline 3 appropriate.

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 states a specific use case ('upcoming fixtures') with a precise time scope (next 1-30 days, default 7) and names the returned market data (median three-way line, moneylines, goal total, handicap, implied probabilities). It also explicitly distinguishes the tool from get_odds, which is for every book's line, so an agent can select it without opening schemas.

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?

It gives explicit when-to-use guidance for upcoming fixtures and a clear alternative: 'For every book's line use get_odds.' It adds cost and usage constraints ('never work out a stake...'), so both selection and invocation boundaries are covered.

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