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jarvismaximum-hue

ProfitPlay MCP Server

market

Retrieve active prediction market data for cryptocurrency or stock price movements, including order book details and remaining time for specific game types like BTC-5min or ETH-5min.

Instructions

Get the current active market for a specific game type, including order book and time remaining.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gameTypeYesGame type, e.g. 'btc-5min', 'eth-5min', 'spy-10min'

Implementation Reference

  • The request handler for the 'market' tool, which fetches data from the API based on the provided gameType.
    case "market":
      return { content: [{ type: "text", text: JSON.stringify(await apiGet(`/api/games/${args?.gameType}/market`), null, 2) }] };
  • The schema registration for the 'market' tool, defining its input parameters.
      name: "market",
      description: "Get the current active market for a specific game type, including order book and time remaining.",
      inputSchema: {
        type: "object" as const,
        properties: {
          gameType: { type: "string", description: "Game type, e.g. 'btc-5min', 'eth-5min', 'spy-10min'" },
        },
        required: ["gameType"],
      },
    },
Behavior3/5

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

With no annotations, description carries full burden. 'Get' implies read-only safety, and mentioning 'order book and time remaining' compensates partially for missing output schema. However, lacks auth requirements, rate limits, or error handling (e.g., inactive markets).

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?

Single, efficient sentence front-loaded with the action verb. No redundant words; every clause provides necessary scoping (game type specificity) or return value hints (order book, time remaining).

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?

Appropriately compensates for missing output schema by naming key return components (order book, time remaining). Given low complexity (1 param) and high schema coverage, this is sufficient, though edge case behavior could be noted.

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 has 100% coverage with clear examples ('btc-5min', etc.). Description references 'specific game type' aligning with the parameter but adds no additional semantic context (format rules, validation) beyond the schema.

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?

Clear verb ('Get') and resource ('current active market') with specific scope ('order book and time remaining'). Implies distinction from sibling 'bet' (which places wagers) by focusing on data retrieval, though explicit sibling contrast is absent.

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

Usage Guidelines2/5

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

No explicit guidance on when to use versus alternatives like 'games' (which likely lists available types) or 'status'. Missing prerequisites or conditions (e.g., 'use before placing a bet').

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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