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vulcan-sport

Polymarket Autonomous Trader

by vulcan-sport

place_order

Place limit orders on Polymarket prediction markets, with manual approval or automatic execution within risk limits.

Instructions

Place a limit order on a market.

In confirm mode (default): returns a pending decision for your approval. In autonomous mode: executes immediately if within risk limits.

Args: condition_id: Market condition ID side: "YES" to buy YES shares, "NO" to buy NO shares price: Limit price (0.01 – 0.99) size_usdc: Position size in USDC order_type: "GTC" (Good Till Cancel) or "FOK" (Fill or Kill)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideYes
priceYes
size_usdcYes
order_typeNoGTC
condition_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that confirm mode returns a pending decision for approval and that autonomous mode executes immediately if within risk limits. It does not detail failure outcomes or order lifecycle beyond these key points.

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 compact and well-structured: two sentences on behavior followed by a clean argument list. Every sentence adds value, and the main purpose is front-loaded.

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?

Given the 5 parameters and an output schema, the description provides sufficient coverage of place order behavior, modes, and parameter semantics. It is slightly incomplete in not referencing how to obtain a condition_id (e.g., via search_markets), but overall it enables correct tool invocation.

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 zero description coverage, so the tool description fully compensates by explaining each parameter: condition_id, side (YES/NO), price (0.01–0.99), size_usdc, and order_type (GTC/FOK). This adds significant meaning beyond the bare schema field names.

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 starts with a clear, specific action: 'Place a limit order on a market.' This identifies the verb and resource precisely, and it is distinct from sibling tools like cancel_order or approve_trade.

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 explains the two execution modes (confirm and autonomous) and their differing behaviors, providing useful context on when the tool will place an order vs. request approval. However, it does not explicitly mention alternatives or exclusions, which would push it to a 5.

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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