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polymarket_rewards_markets

List Polymarket rewards markets by date, category, and sort order to find reward-bearing prediction markets. Filters by question, category, and reward metrics return clean JSON rows for analysis.

Instructions

List Polymarket rewards markets. Returns normalized public rewards-market rows used by Polymarket's /rewards page. The order_by enum accepts market, earnings, max_spread, min_size, rate_per_day, price, earning_percentage, and spread; the position enum accepts asc and desc; the tag_slug enum accepts all, politics, sports, crypto, pop-culture, middle-east, business, and science.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoOptional market question search text
dateNoReward program date in YYYY-MM-DD format; defaults to today in UTC
limitNoMaximum rows, defaults to 100 and supports up to 100
cursorNoOptional rewards cursor from a prior response; defaults to MA==
order_byNoRewards market sort
positionNoSort direction
tag_slugNoRewards category

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.17.5
    • addedInput schema / properties / order_by / enum
      Added value: +[
+  "market",
+  "earnings",
+  "max_spread",
+  "min_size",
+  "rate_per_day",
+  "price",
+  "earning_percentage",
+  "spread"
+]
    • addedInput schema / properties / position / enum
      Added value: +[
+  "asc",
+  "desc"
+]
    • addedInput schema / properties / tag_slug / enum
      Added value: +[
+  "all",
+  "politics",
+  "sports",
+  "crypto",
+  "pop-culture",
+  "middle-east",
+  "business",
+  "science"
+]
  2. Addedv1.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that rows are 'normalized public rewards-market rows' and that the date defaults to today in UTC, which adds behavioral context. However, it doesn't mention pagination behavior, rate limits, or what fields the returned rows contain beyond the sortable columns.

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 focused paragraph that front-loads the core purpose and then lists enum values. It's efficient and every sentence adds information, though the enum enumeration is somewhat long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list tool with 7 optional parameters and no output schema, the description covers the core purpose and enum options but doesn't explain the return row structure, pagination cursor semantics, or how limit interacts with cursor. An agent could call it correctly but might not know what to expect in the response.

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 the schema already documents all 7 parameters. The description adds value by enumerating the exact enum values for order_by, position, and tag_slug, which reinforces but doesn't significantly extend the schema. Baseline 3 is appropriate.

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 verb ('List') and resource ('Polymarket rewards markets'), and clarifies it returns normalized public rewards-market rows used by Polymarket's /rewards page. It doesn't explicitly differentiate from sibling tools like polymarket_markets or polymarket_rewards_market, but the resource and normalization detail make the purpose clear.

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?

The description implies usage by describing what the tool returns and the available enums, but it doesn't state when to use this tool versus alternatives like polymarket_markets or polymarket_rewards_market. No explicit exclusions or alternative routing are provided.

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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