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MAASAI-Labs

Prediction Market Odds

by MAASAI-Labs

Search prediction markets

search_markets
Read-only

Search open Polymarket and Kalshi markets by topic to retrieve implied YES probability, bid/ask, 24h change, volume, close date, ID, and link.

Instructions

Search open markets on Polymarket and Kalshi by topic (e.g. 'Fed rate', 'Bitcoin 150k', 'World Cup'). Returns implied YES probability, bid/ask, 24h change, volume, close date, ID and link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
venueNodefault both

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true), so the description's real contribution is the payload it returns: implied YES probability, bid/ask, 24h change, volume, close date, ID and link. That materially helps an agent judge whether results suffice. It still omits ordering, pagination, and what happens on an empty or unknown-topic query.

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?

Two sentences, front-loaded with the action and scope, followed by the result shape. Every clause carries information; nothing is redundant with the title.

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?

With no output schema, the description correctly enumerates return fields, and it covers venues and scope. For a 3-param tool it is nearly self-sufficient, missing only the limit/pagination and result-ordering behavior an agent might need.

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 coverage is only 33% (just the venue enum's 'default both'), so the description must compensate. It partially does: the topic examples clarify the query parameter and the venue names imply the 'both' default, but limit (1-25) and the venue enum values themselves get no explanation, leaving real gaps.

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+resource ('Search open markets'), scopes it to two named venues, and gives concrete query examples ('Fed rate', 'Bitcoin 150k'). The 'by topic' framing implicitly separates it from trending_markets and get_market_odds, but no sibling is named explicitly.

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 query examples hint at the kind of input to supply, but there is no statement of when to use this versus trending_markets, get_market_odds, compare_markets, or market_briefing, and no exclusions or prerequisites. The agent must infer routing from sibling names alone.

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