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Rekko-AI

Rekko MCP

by Rekko-AI
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Python
Remote

get_arbitrage

Identify cross-platform arbitrage opportunities between Kalshi and Polymarket prediction markets. Set minimum spread thresholds to filter profitable trades.

Instructions

Get cross-platform arbitrage opportunities between Kalshi and Polymarket (cached).

Args: min_spread: Minimum spread threshold (0.0-1.0). Default 0.02 (2%).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
min_spreadNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/rekko_mcp/server.py:321-328 (handler)
    The `get_arbitrage` tool is defined here using the @mcp.tool() decorator. It proxies the request to the /v1/arbitrage endpoint.
    @mcp.tool()
async def get_arbitrage(min_spread: float = 0.02) -> str:
    """Get cross-platform arbitrage opportunities between Kalshi and Polymarket (cached).

    Args:
        min_spread: Minimum spread threshold (0.0-1.0). Default 0.02 (2%).
    """
    return await _request("GET", "/v1/arbitrage", params={"min_spread": min_spread})

Tool Definition Quality

A3.7/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses the caching behavior (data staleness), which is critical for arbitrage tools. However, it omits other behavioral details like cache duration, rate limits, or what constitutes an 'opportunity' in the output.

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?

Efficient two-part structure: single sentence for purpose, Args block for parameter details. No redundant text; every element earns its place.

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

Completeness4/5

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

Adequate for a single-parameter retrieval tool that has an output schema. The description covers the essential domain context (Kalshi/Polymarket), data freshness (cached), and parameter documentation. Missing minor details like cache TTL or error conditions.

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

Parameters4/5

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

With 0% schema description coverage, the description fully compensates by documenting the min_spread parameter with semantics (threshold), valid range (0.0-1.0), and default value (0.02/2%). Minor gap: doesn't explain what 'spread' measures (price difference between platforms?).

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

Purpose4/5

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

States specific action (Get) and resource (cross-platform arbitrage opportunities) with clear scope (Kalshi and Polymarket). The '(cached)' notation implicitly distinguishes it from sibling 'get_arbitrage_live', though it could explicitly name the alternative.

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?

Provides implied usage guidance through the '(cached)' label, suggesting when to use this versus a live data source. However, it lacks explicit when-to-use/when-not-to-use rules or explicit mention of the 'get_arbitrage_live' alternative.

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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