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Sharp-API

sharpapi-mcp

Official
by Sharp-API

get_arbitrage

Find cross-book arbitrage opportunities where combined implied probability is under 100%, enabling locked-in margins by backing all outcomes.

Instructions

Find cross-book arbitrage opportunities: sets of prices whose combined implied probability is under 100%, so backing every outcome locks a margin. Requires a Hobby plan or above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sportNo
leagueNo
min_profitNoMinimum profit percent, e.g. 1.5

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the plan requirement and the core calculation, but does not mention side effects, read-only status, rate limits, or behavior when no arbitrage exists. This is partial but not comprehensive.

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

Conciseness5/5

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

Two sentences, no filler: the first defines the tool's core behavior and the second adds the plan requirement. Information is front-loaded with the verb and resource.

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

Completeness2/5

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

The tool has no output schema and no annotations, and the description omits parameter descriptions and return format. It gives enough concept but not enough operational detail for an agent to call it correctly with filters and interpret results.

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

Parameters1/5

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

Schema description coverage is only 25%, and the description adds no parameter-level meaning. 'limit', 'sport', and 'league' are left undocumented in both schema and description, so the description fails to compensate for the low coverage.

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?

The description uses a specific verb ('Find') and a clear resource ('cross-book arbitrage opportunities'), and defines the concept precisely with the combined implied probability under 100%, distinguishing it from sibling tools like get_ev and get_middles which target different edge concepts.

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?

Implicitly indicates use when arbitrage is sought, but does not contrast with sibling tools or state exclusions. The only explicit usage guidance is the plan requirement ('Requires a Hobby plan or above'), which is a constraint, not an alternative-selection rule.

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