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get_arbitrage_spreads

Return live Kalshi vs Polymarket US cross-venue box / mispricing teasers.

Call when you need fee-buffered arb candidates (rule: P_Kalshi_YES + P_Poly_NO < 0.97).
Do not call for single-venue forecasts, sports picks, or SEC filing alpha — use the
other tools for those. Read-only / idempotent; no orders are placed. `limit` is 1–10.
Response JSON includes candidates[] plus an `unlock` block pointing at the paid
x402 depth endpoint when full sizing is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Despite no annotations, the description discloses critical behaviors: 'Read-only / idempotent; no orders are placed' establishes safety, and 'Response JSON includes candidates[] plus an unlock block' explains output shape and the existence of a paid endpoint. This fully covers behavioral expectations.

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?

The description is compact, front-loading the purpose, with each sentence earning its place. The usage rule is presented in parentheses, and exclusions are concise. No fluff or redundancy.

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?

Given the tool's complexity (cross-venue arb, fee buffer, output schema), the description is complete: it covers purpose, usage rules, exclusions, limit range, read-only safety, response structure including the paid unlock endpoint, and when full sizing is needed. Nothing essential is missing.

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 compensates by stating '`limit` is 1–10', giving a range constraint. However, it does not explicitly state that limit controls the number of candidates returned, though this is inferable from context. It adds value beyond the bare schema but is not fully explicit.

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 states a specific verb ('Return') and resource ('live Kalshi vs Polymarket US cross-venue box / mispricing teasers'), clearly identifying the tool's purpose. It also distinguishes itself from siblings by explicitly excluding single-venue forecasts, sports picks, and SEC filing alpha, which map to other tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

Provides explicit when-to-use instructions ('Call when you need fee-buffered arb candidates') with a concrete numeric rule (P_Kalshi_YES + P_Poly_NO < 0.97), and explicit when-not-to-use with alternative tools ('use the other tools for those'). This leaves no ambiguity about selection.

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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