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Vectorial Data Terminal: Hyperliquid, Polymarket & yield for AI agents

get_prediction_positions

Read-only

Your open prediction positions (Polymarket's numbers): shares, average and current price, cost, value, P&L, and whether a resolved winner is waiting to be collected (collectable).

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": "get_prediction_positions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare this a read-only, open-world call, so the bar is lower; the description still adds real value by disclosing the data source (Polymarket's numbers) and the exact returned fields, including that a resolved winner may appear as 'collectable'. It does not state whether the list is bounded/paginated or whether prices are live, but nothing here contradicts the annotations.

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?

A single front-loaded sentence with a dense field list; the resource is stated before the detail, and no sentence is wasted. The parenthetical 'Polymarket's numbers' is slightly informal but does identify the data source.

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, the description carries the return-value burden, and it does so by enumerating every field the agent can expect. The only gaps are operational details (ordering, limits, which wallet/account the positions belong to), which are minor for a parameterless read.

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 tool takes zero parameters, so the baseline applies and no parameter meaning is required. The description correctly adds no irrelevant argument discussion and instead spends its space on what comes back.

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 (open prediction positions) and enumerates exactly what each entry contains: shares, average/current price, cost, value, P&L and a collectable flag. It is clearly a read-getter for prediction-market holdings, distinct from the generic get_positions or get_predictions_account. It stops short of naming those siblings, so differentiation is inferred rather than stated.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no prerequisites, and no mention of the obvious alternatives (get_predictions_account for balances, get_positions for spot, collect_prediction_winnings as the follow-up action). The words 'open' and 'collectable' imply scope and a next step, but the agent must infer both.

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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