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polymarket-paper-trader

Search markets

search_markets
Read-onlyIdempotent

Search Polymarket markets by free-text query to find markets by keyword, returning slug, question, prices, and volume for each result.

Instructions

Search Polymarket markets by text and return slug, question, prices and volume.

Queries the live Polymarket API and changes nothing. Searches Polymarket only: use kalshi_markets to find Kalshi markets, list_markets to browse by volume, or get_markets_by_tag to browse a category.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum markets to return, clamped to 1-100. Default 10.
queryYesFree-text search, e.g. 'bitcoin' or 'fed rate cut'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.4.13
    • addedInput schema / properties / limit / description
      Added value: +"Maximum markets to return, clamped to 1-100. Default 10."
    • addedInput schema / properties / query / description
      Added value: +"Free-text search, e.g. 'bitcoin' or 'fed rate cut'."
  2. First observedv0.4.1

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered. The description's 'queries the live Polymarket API and changes nothing' largely restates readOnly/non-destructive, though 'live' hints at real-time data freshness. No pagination, rate-limit, or error behavior is disclosed, so this adds only marginal value over the annotations.

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?

Three short sentences, front-loaded with the action and return fields, followed by the routing guidance. Every sentence carries information; nothing is padding.

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?

An output schema exists, so return-value explanation is not strictly required, yet the description usefully names the key fields. Inputs, scope, and alternatives are all covered, leaving only freshness/pagination details unstated, which is acceptable for this complexity level.

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%: both query (free-text examples) and limit (clamped 1-100, default 10) are documented in the schema itself. The description adds only 'by text', which does not extend parameter meaning beyond the schema. Baseline 3 applies.

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?

States a specific verb (search), resource (Polymarket markets), and the input axis (free text), plus the fields returned. It also explicitly names what it is not (Kalshi, browse-by-volume, browse-by-tag), so an agent can select it without opening any schema.

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

Usage Guidelines5/5

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

Gives explicit routing: use kalshi_markets for Kalshi, list_markets to browse by volume, get_markets_by_tag to browse a category. All three alternatives and the conditions that select them are named.

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