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Predict.fun Leaderboard

predictfun_leaderboard
Read-onlyIdempotent

Every Predict.fun wallet ranked by realized P&L (default), volume or fills over a window, or by today's unrealized P&L; each row carries realized and unrealized P&L, open value, open and resolved positions (outcome tokens), volume and fills for every window. Rebuilt hourly. Returns {rows, window, sort, label_basis, as_of_ts}; page with offset (max 1000).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "predictfun_leaderboard"
  }
}

Input Schema

NameRequiredDescriptionDefault
sortNoDefault `realized`. `unrealized` takes window `all` only.
limitNoRows (default 20, max 50).
offsetNoRows to skip, 0 to 1000.
windowNoDefault `all`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint/idempotentHint annotations, the description discloses data freshness ('Rebuilt hourly'), pagination ceiling (max 1000), and the full field set each row carries, plus the exact response shape. Those are the kinds of operational facts annotations cannot convey and that directly affect how an agent plans calls and interprets results.

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 ranking scope and defaults are front-loaded, followed by row contents, freshness, and return shape in a compact two-sentence body. It is dense with semicolon-heavy clauses but nearly every phrase carries information; only the repeated offset ceiling is redundant.

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, describing the return object is valuable and here it is explicit; freshness and pagination are also covered. Remaining gaps are minor, such as what `label_basis` means and whether wallets with no activity are included.

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 baseline is 3. The description mostly restates schema facts (default realized, offset max 1000) and only adds a little cross-parameter meaning via the sort/window interaction already covered by the schema's own enum note.

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 names the specific resource (every Predict.fun wallet) and the exact ranking bases (realized P&L default, volume, fills over a window, or today's unrealized P&L). Combined with the platform name, an agent can distinguish it from hl_leaderboard and polymarket_leaderboard without opening a schema.

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?

There is no explicit when-to-use/when-not guidance or routing to a sibling tool; usage is only implied by stating the default sort and the 'unrealized takes window `all` only' constraint. Those hints are useful but don't tell an agent what situation should select this tool over the other two leaderboards.

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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