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

Annotations already cover the read-only and open-world profile, and an output schema exists, so the description's added value is the market-dependence of the count and the worked examples (NJ 131 vs NY 36). That tells the agent results vary meaningfully by state and that the call is cheap. What's missing is any note on whether the count is real-time or cached.

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?

Two sentences, front-loaded with the purpose, then the usage rationale and parameter note. Nothing is redundant and every clause carries information.

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 one-optional-parameter read tool with annotations and an output schema, the description supplies everything needed: what it returns, why to call it, and how the single parameter affects output. No gaps remain.

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%, so baseline is 3, but the description adds semantics the schema lacks: that the optional state materially changes the result and that the count is market-specific, illustrated with two concrete values. It reinforces rather than repeats the schema's 'default nj' note.

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 ('Get the number of events in play in a FanDuel Sportsbook market') and pins down the exact figure ('shown beside the homepage Live link'). The word 'count' plus the integer examples makes clear this returns a scalar, distinguishing it implicitly from list-returning siblings like fanduel_sportsbook_live or fanduel_sportsbook_live_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?

Gives concrete use cases: 'watch betting activity cheaply or decide whether to list live events,' which tells the agent this is a lightweight pre-check. It stops short of naming the sibling tools (e.g. the full live-events endpoint) it should precede, so the alternative is implied rather than explicit.

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