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DF Market Intelligence

DF Market Intelligence

by nasosal92
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

predictions_top

Fetch live prediction markets ranked by trading volume across Polymarket and Kalshi, including implied probabilities, 24h change, volume and close time.

Instructions

Top prediction markets — Highest-volume live prediction markets across Polymarket and Kalshi with implied probabilities, 24h change, volume and close time. Refreshed every 15 minutes. Costs $0.005 USDC per call (x402 on Base), paid automatically from your configured wallet.

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": "predictions_top"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo1-100, default 25
sourceNoOptional: polymarket or kalshi

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does well on key traits: it discloses freshness ('Refreshed every 15 minutes') and billing ('Costs $0.005 USDC per call ... paid automatically from your configured wallet'). It does not cover rate limits or error behavior, but the cost and staleness disclosures are substantial for a read-only data tool.

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?

The description is two tightly written sentences. The core scope is front-loaded, and the remaining sentences add essential context about refresh cadence and cost without any filler.

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?

No output schema exists, but the description lists the returned fields (implied probabilities, 24h change, volume, close time), which is important. Combined with the freshness and payment notes, it is nearly complete for this tool, though it could say more about result ordering or coverage gaps.

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%, and both parameters (limit and source) are fully documented in the schema, including the source enum. The description adds no parameter-specific syntax or constraints beyond what the schema already provides, so the baseline of 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?

The description uses a specific verb and resource ('Top prediction markets') and immediately scopes it to 'Highest-volume live prediction markets across Polymarket and Kalshi.' This distinguishes it clearly from sibling tools like predictions_search and predictions_movers, which imply keyword search and movement-based ranking respectively.

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 implied by the scope ('top ... highest-volume live'), so an agent can infer this is for browsing leading markets. However, the description never explicitly says when to use this versus predictions_search or predictions_movers, nor does it state any exclusions or prerequisites beyond the payment note.

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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