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predgeAI

whale-data-mcp

by predgeAI

Wallet trade history + PnL curve

predge_wallet_history

Retrieve a wallet's Polymarket trade history with win-rate and modeled PnL curve. Select a 30d, 90d, or all-time window to evaluate trader performance.

Instructions

PAID (~$0.02). One wallet's trade history with a running win-rate and modeled-PnL curve. Params: address (0x…), window (30d|90d|all, default 30d).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo
addressYes
Behavior3/5

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

With no annotations provided, the description carries the burden. It discloses the cost (~$0.02) and the nature of the PnL as 'modeled', which is important caveat. However, it does not explain the potential latency, failure modes, or that this is a paid API call might need user consent. The 'PAID' alert is helpful but incomplete.

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 compact, one sentence with essential info front-loaded ('PAID' and purpose). It wastes no words. A small deduction for lack of line breaks, but overall very efficient.

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?

The tool is simple (2 parameters, no output schema), so the description covers the basics. However, it omits details about the output format (e.g., what the PnL curve looks like) and whether the win-rate is over the window. For a paid tool, an agent might need to know more about the return value to decide if it's worth calling.

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?

The schema has 0% description coverage, and the description compensates by explaining both parameters: address (0x...) and window (30d|90d|all, default 30d). This adds clarity to the enum and pattern, making it easier for the agent to fill in values. Without this, the schema alone might be unclear.

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 clearly states the tool returns a wallet's trade history with a win-rate and modeled-PnL curve. It distinguishes from siblings by specifying 'one wallet' and the PnL curve, differentiating from predge_wallet_profile (likely profile info) and predge_wallet_attest (attestation).

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

Usage Guidelines4/5

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

The description mentions the 'PAID' cost, which is a key usage consideration for an AI agent, and lists the parameter options. However, it does not explicitly state when to use this vs alternatives, though the 'PAID' callout and specific output imply it's for in-depth wallet analysis. It lacks explicit when-not-to-use guidance.

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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