parlayapi_find_arbitrage

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

With no annotations provided, the description carries the transparency burden. It clarifies that the tool scans every event, returns arbitrage bets whose combined probability is below 100%, and even discloses a real caveat: exchange-anchored asks can have no volume. It does not explicitly state 'read-only/no bets placed', but the verbs 'scans' and 'returns' strongly imply a non-mutating action.

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 well structured: a one-sentence purpose, a concise explanation of the discovery logic and supported market type, then a focused Args block. Every part adds operational information needed to pick and call the tool correctly.

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 that an output schema exists, the description does not need to explain return format. It adequately covers the tool's purpose, supported markets, key behavioral caveats, and all parameter semantics. It could be improved by mentioning when to choose a sibling tool like find_ev or find_middles instead.

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 input schema has 0% description coverage, so the description must compensate fully. The Args section does exactly that: it explains each parameter's meaning (e.g., min_profit as a percentage, markets as comma separated market_keys), gives examples, states optionality, and covers behavior like exclude_exchanges dropping no-volume exchange-anchored arbs.

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 verb and resource: 'Find... arbitrage opportunities across bookmakers', then reinforces it with the technical criterion of combined implied probability under 100%. This clearly distinguishes it from siblings like parlayapi_find_ev and parlayapi_find_middles.

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 gives clear context for when this tool is appropriate, especially for soccer and other 3-way markets, and notes the optional scan scope via markets. It does not explicitly name sibling tools or say 'use for arbitrage, not for EV/middles', but the use case is strongly implied.

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