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top_traders

Polymarket leaderboard re-ranked by skill, not size: top traders by edge over the odds paid, return and consistency, for day, week, month or all time, optionally per category (sports, politics, crypto, economy). Exposes big-volume losers the profit leaderboard hides.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of traders, 1 to 25
periodNo
categoryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses useful traits: the ranking methodology, the available time scopes and categories, and the deliberate framing that it surfaces big-volume losers the profit leaderboard hides. It does not mention auth requirements, rate limits, pagination, or result shape, which are meaningful gaps for a data-retrieval tool.

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?

Two tight sentences with the ranking premise front-loaded, followed by scope and the differentiator. No filler sentences; the value proposition is stated efficiently.

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?

For a read-only retrieval tool with no output schema, the description explains what is returned conceptually (traders ranked by edge, return, consistency across scopes). It leaves the per-trader result shape unspecified, but the ranking semantics are complete enough to call the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33% (only 'limit' is described), so the description must compensate, and it does partially: it explains that period spans day/week/month/all-time and enumerates the category values (sports, politics, crypto, economy). It misses the 'other' category and the 1-25 limit range handling, but overall adds substantial meaning over the raw schema.

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 names a specific resource (Polymarket trader leaderboard) and states the exact ranking basis (edge over odds paid, return, consistency) versus raw size, which tells an agent what it gets. It does not, however, differentiate itself from similar-sounding siblings such as skilled_whales or smart_money, leaving that distinction to be inferred.

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?

It implies when to reach for it by listing period and category scoping ('day, week, month or all time', 'per category'), giving the agent context. But it never states when not to use it or names an alternative sibling for related queries, so usage is only implied rather than guided.

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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