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place_shadow_trade

Record paper trades on prediction markets to track hypothetical positions without executing real transactions.

Instructions

Place a paper (shadow) trade on a prediction market for tracking purposes.

Args: ticker: Market ticker symbol (e.g. "KXBTC-100K"). side: Trade direction: "yes" or "no". size_usd: Trade size in USD.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYes
sideYes
size_usdYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Implementation of the place_shadow_trade tool using a POST request to the API.
    @mcp.tool()
    async def place_shadow_trade(ticker: str, side: str, size_usd: float) -> str:
        """Place a paper (shadow) trade on a prediction market for tracking purposes.
    
        Args:
            ticker: Market ticker symbol (e.g. "KXBTC-100K").
            side: Trade direction: "yes" or "no".
            size_usd: Trade size in USD.
        """
        return await _request(
            "POST",
            "/v1/trades/shadow",
            json={"ticker": ticker, "side": side, "size_usd": size_usd},
        )
Behavior3/5

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

With no annotations provided, the description carries the full burden. It successfully conveys that this is a simulated ('paper') trade rather than a real market execution, which is critical behavioral context. However, it omits other key traits like whether the operation creates persistent state, idempotency, or side effects.

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?

The description is efficiently structured with a single purpose sentence followed by a standard Args docstring block. There is no redundant or filler text; every line provides essential information about the tool's function or its parameters.

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?

Given the simple 3-parameter schema and existence of an output schema (which handles return value documentation), the description adequately covers inputs and basic purpose. However, it lacks safety/mutation context (e.g., destructive hints, idempotency) that would normally appear in annotations or a more detailed description.

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

Parameters5/5

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

The schema has 0% description coverage, requiring the description to compensate fully. The Args section excellently documents all three parameters: it provides a concrete example for 'ticker', enumerates valid values ('yes'/'no') for 'side' which the schema omits, and clarifies the currency unit for 'size_usd'.

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 clearly states the action (Place), resource (paper/shadow trade), and context (prediction market, tracking purposes). However, it does not explicitly differentiate from the sibling tool `report_trade`, which could lead to confusion about when to use simulation versus reporting actual trades.

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 phrase 'for tracking purposes' provides implied guidance on when to use the tool (simulated tracking scenarios). However, it lacks explicit when-not guidance or mentions of alternatives like `report_trade` for real trades.

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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