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unixlamadev-spec

lpxpoly-mcp

by unixlamadev-spec
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JavaScript
Remote

analyze_market

Analyze Polymarket prediction markets to assess probabilities, provide reasoning, and recommend positions for informed trading decisions.

Instructions

Get AI analysis of a specific Polymarket prediction market. Returns probability assessment, reasoning, and recommended position.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesMarket question or search term (e.g. 'Fed rate cut March 2025', 'Trump approval rating')

Implementation Reference

  • src/index.ts:186-208 (handler)
    The handler for the 'analyze_market' tool, which takes a query, calls the LPXPoly API with type 'market', and formats the response.
    case "analyze_market": {
  const { query } = args as any;

  const result = await callLPXPoly("/api/analyze", {
    type: "market",
    query,
  });

  return {
    content: [
      {
        type: "text",
        text: [
          `📊 Market Analysis: ${query}`,
          ``,
          result.analysis || result.response || JSON.stringify(result, null, 2),
          ``,
          `âš¡ Powered by LPXPoly | lpxpoly.com`,
        ].join("\n"),
      },
    ],
  };
}
  • src/index.ts:53-67 (schema)
    Definition of the 'analyze_market' tool schema.
    {
  name: "analyze_market",
  description:
    "Get AI analysis of a specific Polymarket prediction market. Returns probability assessment, reasoning, and recommended position.",
  inputSchema: {
    type: "object",
    properties: {
      query: {
        type: "string",
        description: "Market question or search term (e.g. 'Fed rate cut March 2025', 'Trump approval rating')",
      },
    },
    required: ["query"],
  },
},

Tool Definition Quality

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool returns analysis and recommendations but fails to describe critical traits like whether it's a read-only operation, if it requires authentication, rate limits, error handling, or how it interacts with the market data. This leaves significant gaps in understanding the tool's behavior.

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 description is concise and front-loaded, consisting of a single sentence that directly states the tool's function and return values. There is no wasted text, but it could be slightly improved by structuring usage guidance separately for better clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for a tool that performs AI analysis on markets. It does not explain the format or structure of the returned analysis, potential limitations, or how the 'recommended position' should be interpreted, leaving the agent with insufficient context for effective use.

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?

The input schema has 100% description coverage, with the 'query' parameter well-documented as a market question or search term. The description adds no additional meaning beyond this, such as formatting examples or constraints not in the schema. With high schema coverage, the baseline score of 3 is appropriate.

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?

The description clearly states the tool's purpose with a specific verb ('Get AI analysis') and resource ('specific Polymarket prediction market'), and mentions the return content ('probability assessment, reasoning, and recommended position'). However, it does not explicitly distinguish this tool from its siblings (e.g., 'get_top_markets'), which prevents a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_top_markets' or 'get_edge_opportunities'. It lacks context about prerequisites, such as whether the market must exist or if authentication is needed, and offers no explicit when-not-to-use scenarios.

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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