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Prediction Markets Quant

by com.predictionmarketspicks
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Best Price After Fees — Kalshi vs Polymarket US vs Novig

best_price
Read-only

Use for "where is it cheapest to buy", "Kalshi or Polymarket US for the Bears game" and "cheapest venue for the Georgia Senate race". The same contract on Kalshi, Polymarket US and Novig as the cost to buy one contract including each venue's taker fee, with the cheapest named. Sports games (team, league or matchup), 2026 midterm races (state, slug or district) or the next FOMC meeting. Ranked by price only.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "best_price"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNoFree text: a team, matchup, race or "next Fed meeting".
raceNoA 2026 race: state, slug (georgia-senate) or district (AZ-01).
teamsNoOne or two teams, e.g. "Bears" or "NE @ CHI".
leagueNoNBA, NHL, NFL or MLB.
meetingNoAny value asks for the next FOMC meeting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
  2. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark it read-only and non-destructive, and the description adds the substantive behavioral facts: fees are included, results are "ranked by price only", and a cheapest venue is named. No mention of coverage gaps or what happens when a contract is missing on one venue, which is the main remaining blind spot.

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?

Front-loads three quoted intents before the definition, then scope and ranking rule. Some duplication between the example list and the supported-domain sentence (sports and races appear twice), but nothing is padded.

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?

With no output schema, the description does the necessary work by stating what comes back (per-venue cost for one contract, fees included, cheapest named, price-ranked). A caller can act on it; only edge-case behavior and result-shape detail are absent.

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

Parameters3/5

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

Schema coverage is 100%, so all five params are already documented with examples. The description adds only category-level mapping (sports -> team/league/matchup, races -> state/slug/district, "next Fed meeting"), not the free-form-vs-structured relationship or whether params combine — baseline 3 applies.

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 and resource: "the cost to buy one contract including each venue's taker fee, with the cheapest named" across Kalshi, Polymarket US and Novig. That fee-inclusive comparison framing clearly separates it from the sibling odds tools (race_odds, market_pulse, fed_rate_odds).

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

Usage Guidelines4/5

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

Quoted example queries ("where is it cheapest to buy", "cheapest venue for the Georgia Senate race") and an explicit supported-domain list (sports games, 2026 midterms, next FOMC meeting) give a clear entry condition. It never says when to prefer a sibling such as race_odds for raw odds instead, so no exclusion guidance.

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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