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prediction_markets

Read-onlyIdempotent

Query live prediction market odds & real-money implied probabilities (%) from Polymarket and Manifold Markets for any crypto, macro-economic, political, or technology event.

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of markets to return (1-15, default: 5)
queryYesEvent or topic to search (e.g., 'bitcoin', 'fed rate', 'AI', 'election')
x_api_keyNoOptional ak_live_... 30-day Prepaid API Pass key to unlock the full unmasked dataset
payment_signatureNoOptional x402 v2/v1 Base64 or JSON EIP-3009 USDC payment signature to unlock the full unmasked dataset directly via MCP

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / payment_signature
      Added value: +{
      +  "description": "Optional x402 v2/v1 Base64 or JSON EIP-3009 USDC payment signature to unlock the full unmasked dataset directly via MCP",
      +  "type": "string"
      +}
    • addedInput schema / properties / x_api_key
      Added value: +{
      +  "description": "Optional ak_live_... 30-day Prepaid API Pass key to unlock the full unmasked dataset",
      +  "type": "string"
      +}
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds useful context about the data returned (live odds, real-money implied probabilities), but omits behavioral traits like the masked-vs-unmasked dataset, rate limits, or latency, which live only in the parameter descriptions.

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?

A single dense sentence that front-loads the verb, the resource, and the sources with no filler. Every clause earns its place.

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?

There is no output schema, so the description must carry return-value meaning, and it does say what comes back (odds and implied probabilities in %). With full schema coverage on inputs, only the masking/unmasked-data nuance is left implicit.

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 all four parameters (limit, query, x_api_key, payment_signature) are already documented. The description adds no parameter-level meaning (no default behavior, no note on what unlock actually reveals), so the baseline 3 applies.

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?

States a specific verb ('Query') and resource ('live prediction market odds & real-money implied probabilities') with named data sources (Polymarket, Manifold Markets). However, it never distinguishes itself from the sibling kalshi_polymarket_arb, which also touches Polymarket, so the agent has no in-description cue about which to pick.

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

Usage Guidelines3/5

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

Usage is only implied: 'for any crypto, macro-economic, political, or technology event' sketches the topic scope, but there is no explicit when-to-use, when-not-to-use, or named alternative. The overlap with kalshi_polymarket_arb goes unaddressed.

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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