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

Beyond the readOnlyHint annotation, the description adds that it is 'explicitly not trading advice,' explains the empty-array behavior when no market qualifies, and reveals that the de-vigged sportsbook consensus is carried as one venue—context that affects interpretation. No contradictions 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 moderately long but well-structured, front-loading the core function and then delivering usage guidance in clear uppercase markers. Every sentence contributes value, though it could be tightened slightly.

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 conceptual complexity of cross-venue disagreement, the description provides a complete picture: what the data represents, why it exists, when to use it, and an important edge case (empty array). With an output schema present and one well-documented parameter, 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?

The schema description for the sole parameter (limit) is fully self-explanatory, covering defaults and demo limits. The tool description adds no additional semantics for the parameter, so the baseline of 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 the tool lists markets where venues disagree, ranked by cross-market spread, with a restriction to markets priced by at least two venues. It distinguishes itself from siblings by framing this as the cross-venue arbitrage-and-mispricing view and contrasting with list_movers and get_market_history.

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 explicitly states when to use the tool ('USE WHEN asked where the market is inconsistent, which venue is mispricing something, or for the widest gaps right now') and when to use something else with named alternatives (list_movers, get_market_history, get_market_probabilities). This gives clear decision criteria.

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