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Prediction Markets Quant

by com.predictionmarketspicks
OverviewDiscussionsAdmin

NBA Game Line Board (Kalshi vs the books)

nba_game_board
Read-only

Use for "Knicks moneyline on Kalshi vs the books" and "cheapest place for the Celtics spread tonight". Kalshi NBA moneyline, spread and total beside DraftKings, FanDuel, BetRivers, Fanatics, ESPN, Novig and ProphetX at the same line: the cheapest venue per side, Kalshi fee included. Market prices only, no model.

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": "nba_game_board"
  }
}

Input Schema

NameRequiredDescriptionDefault
gameNoTwo teams, e.g. "BOS @ DET".
teamNoTeam code or name (NYK, Knicks).
limitNoMax games (default 5; 2 when the call has no arguments).
marketNoOptional market. One of: moneyline · spread · total.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / limit / description
      Previous value: -"Max games (default 5)."New value: +"Max games (default 5; 2 when the call has no arguments)."
  2. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / limit / description
      Previous value: -"Max games (default 5). Values above 20 are clamped to 20."New value: +"Max games (default 5)."
  3. Changed2 schema fields changed
    • removedInput schema / properties / limit / anyOf
      Removed value: -[
-  {
-    "anyOf": [
-      {
-        "type": "number"
-      },
-      {
-        "type": "string"
-      }
-    ]
-  },
-  {
-    "type": "null"
-  }
-]
    • addedInput schema / properties / limit / type
      Added value: +[
+  "number",
+  "string",
+  "null"
+]
  4. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish read-only, open-world, and non-destructive behavior. The description adds meaningful context beyond that: the specific books compared, same-line comparison, cheapest venue per side, Kalshi fee inclusion, and that only market prices are returned rather than model-derived values.

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 and front-loaded with the use case and example queries. Every sentence contributes to clarifying the tool's scope, data sources, and pricing behavior without redundant wording.

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?

Given four optional parameters and no output schema, the description provides enough detail about what the board returns: Kalshi lines beside book lines, cheapest venue per side, fees included, and market prices only. Minor gaps like ordering or pagination are not critical for this read-only comparison tool.

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 description coverage is 100%, so the input schema already documents game, team, limit, and market. The description does not add parameter-level syntax or behavior beyond the schema, making the baseline 3 appropriate.

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 resource and scope: NBA moneyline, spread and total markets compared against named sportsbooks, with Kalshi fees included. It clearly distinguishes itself from sibling tools like nba_prop_board and calculate_ev by emphasizing game-line market prices only and no model.

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?

The opening 'Use for' phrasing and the two concrete example queries give clear when-to-use guidance. It does not explicitly name when not to use the tool or point to a specific alternative, but 'Market prices only, no model' implicitly separates it from calculate_ev and similar siblings.

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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