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Prediction Markets Quant

by com.predictionmarketspicks
OverviewDiscussionsAdmin

Explain This Game — why we price an NFL game there

explain_game
Read-only

Why our model prices one NFL game where it does: Kalshi price and market line, our win probability and its anchor, the model's lean in points, each team's offense/defense/special-teams rating, the QB gate, and the published position or why none. Use for "why do you price vs there", "explain the game line".

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": "explain_game"
  }
}

Input Schema

NameRequiredDescriptionDefault
gameNoThe matchup — two teams in any form ("Bills vs Chiefs", "BUF@KC", "Buffalo at Kansas City"), or one team for its game that week.
weekNoOptional NFL week (e.g. 6). Defaults to the current week.

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. Changed2 schema fields changed
    • removedInput schema / properties / week / anyOf
      Removed value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "string"
-  }
-]
    • addedInput schema / properties / week / type
      Added value: +[
+  "number",
+  "string"
+]
  3. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), and the description adds the substantive detail an agent can't get from them: the full breakdown of what the answer contains, including the QB gate and the 'published position or why none' outcome. No mention of latency, cost, or data freshness, which keeps it below a 5.

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?

The purpose is front-loaded in the first clause before the content list, and the usage quotes at the end are compact. The middle enumeration is long but each item is a distinct output field, so little is wasted.

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 correctly compensates by listing the returned components, and both parameters are documented in the schema. Only minor gaps remain around response shape/ordering and whether a missing game is an error or an empty answer.

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% and both param descriptions already explain accepted matchup formats and the optional week default, so the description adds nothing beyond the schema. Baseline 3 is 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?

Specific verb + resource: explains why the model prices a single NFL game where it does, and enumerates the exact components returned (market line, win probability and anchor, points lean, team ratings, QB gate, position). This clearly separates it from explain_ladder, explain_player, explain_prop, and nfl_win_probability.

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?

Explicit trigger phrases ('why do you price <team> vs <team> there', 'explain the <team> game line') tell the agent exactly when to reach for it. It stops short of naming which sibling to use instead (e.g. nfl_win_probability for raw numbers), so no true exclusion is stated.

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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