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caiovicentino

Polymarket MCP Server

analyze_market_opportunity

Analyze a prediction market by ID to get a trading recommendation, risk assessment, and confidence score for informed decisions.

Instructions

AI-powered market analysis with trading recommendation, risk assessment, and confidence score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
market_idYesMarket ID to analyze

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions 'AI-powered' implying computational cost or latency, but does not disclose whether it's synchronous, if it has side effects, requires special permissions, or how it handles invalid market_ids. The trading recommendation and risk assessment imply analytical output, but no further detail is given.

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 a single, concise sentence with no filler. It front-loads the key deliverables (trading recommendation, risk assessment, confidence score), which is efficient. However, it could be slightly more structured to include usage context without being verbose.

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?

This is an analysis tool that is more complex than a simple data getter, yet there is no output schema and no annotations. The description omits return format, error handling, and any prerequisites or side effects, leaving the agent with insufficient information to use it correctly in a real workflow.

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 covers 100% of the parameter (market_id with a description), so the baseline is 3. The description does not add any additional meaning about market_id beyond what the schema provides; it merely repeats that it's the market to analyze.

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 states a specific purpose: AI-powered market analysis with trading recommendation, risk assessment, and confidence score. This clearly differentiates it from the many get_* retrieval tools among siblings, though it doesn't explicitly name a sibling to contrast with.

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?

There is no guidance on when to use this tool versus the numerous get_* and subscribe_* siblings. It doesn't state whether it's a standalone analysis tool or a complement to data retrieval, nor does it mention any prerequisites or context where it's appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.