ParlayAPI

parlayapi_find_arbitrage

Find cross-book arbitrage candidates from current quoted prices.

Scans every event for quoted prices whose combined implied probability
is under 100%. Results are candidates, not guaranteed executable profit:
prices can move or be unavailable, and limits, latency, commissions,
voids, settlement rules, or stake constraints can change the outcome.
Soccer and other 3-way (home/draw/away) markets are supported, including
candidates anchored on the draw.

Args:
    sport_key: e.g. "baseball_mlb", "soccer_epl".
    min_profit: Minimum profit % to include (e.g. 1.5 for 1.5%). Default 0.
    exclude_exchanges: Drop arbs anchored on an exchange (novig/prophetx),
        whose asks can be no-volume. Default False.
    markets: Comma-separated market_keys to limit the scan (optional),
        e.g. "h2h,spreads,totals".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`markets`	No
`sport_key`	Yes
`min_profit`	No
`exclude_exchanges`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 5, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations provided, the description carries full behavioral burden and does so excellently: it discloses that results are candidates not guaranteed profit, enumerates risk factors (price movement, unavailability, limits, latency, commissions, voids, settlement rules, stake constraints), and notes 3-way market support including draw-anchored candidates. This is rich, critical context an agent needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with a clear opening statement, risk disclosure paragraph, and Args block. Slightly verbose in the risk enumeration, but every clause earns its place given the financial stakes. Front-loaded with purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Complete for a 4-param tool with no annotations and an output schema. The description covers purpose, mechanism, risk factors, market support, and all parameter semantics. An agent has everything needed to invoke correctly and interpret results appropriately.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate and it does thoroughly for all 4 parameters: sport_key with examples, min_profit with format explanation and default, exclude_exchanges with rationale about no-volume asks, and markets with format examples. This adds substantial meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Find') and resource ('cross-book arbitrage candidates from current quoted prices'), and the second paragraph explains the scanning mechanism (combined implied probability under 100%). An agent can distinguish this from siblings like find_ev or find_middles 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.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage implicitly (scanning for arbitrage opportunities), but doesn't explicitly state when to use this versus alternatives like find_ev or best_line. No exclusion criteria or alternative routing is provided, leaving the agent to infer when arbitrage hunting is appropriate.

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

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