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polymarket-category-performance

Analyze Polymarket trading activity across categories: volume, liquidity, market count, and top market per category. Filter by a single category for focused insights.

Instructions

Polymarket category activity breakdown: volume, liquidity, market count, and top market per category (crypto, politics, sports, ai, macro, equities). Shows where trading activity is concentrated. Optionally filter to one category. $0.004/call — 20% below closest x402 competitor. Source: Polymarket public API (no key required).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoFilter to a single category. Omit to return all categories ranked by volume.
min_liquidityNoOnly include markets with at least this much liquidity (USD). Default: 1000.
Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It discloses the source ('Polymarket public API'), pricing ($0.004/call), and that no key is required. However, it does not describe potential side effects, rate limits, data freshness, or if the operation is read-only (though it is implied). The pricing info is a unique addition but not covering standard behavioral traits.

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 concise sentences, front-loaded with the core purpose, followed by value proposition and pricing/source. Every sentence adds value with no redundancy.

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?

Despite lacking an output schema, the description lists the exact metrics returned (volume, liquidity, market count, top market) and the categories, giving a clear picture of the output. It also covers optional filtering and default behavior (when no category is provided, returns all ranked by volume). This is nearly complete for a simple tool.

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 100%: both parameters have descriptions. The description adds no new meaning beyond what the schema provides (e.g., 'Optionally filter to one category' mirrors the schema). Thus, baseline 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 explicitly states it provides a 'category activity breakdown' with specific metrics (volume, liquidity, market count, top market) and lists the six categories (crypto, politics, sports, ai, macro, equities). This clearly distinguishes it from sibling Polymarket tools like polymarket-accuracy-score or polymarket-sentiment-shift.

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 for understanding 'where trading activity is concentrated' and mentions optional filtering, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. No sibling tool names are referenced.

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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