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agent-next

polymarket-paper-trader

by agent-next

place_limit_order

Place a limit order on a Polymarket paper-trading account, keeping it open until filled, cancelled, or set to expire at a specific time.

Instructions

Place a limit order that stays open until filled or cancelled/expired.

side: "buy" or "sell" limit_price: target price between 0 and 1 order_type: "gtc" (stays open until cancelled) or "gtd" (expires at timestamp) expires_at: ISO timestamp for GTD orders (required if order_type="gtd")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideYes
amountYes
accountNodefault
outcomeYes
expires_atNo
order_typeNogtc
slug_or_idYes
limit_priceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully discloses order lifecycle behavior, order_type semantics, and the conditional requirement for expires_at. However, it omits other behaviors such as what the response is, whether the order consumes account funds immediately, or how it interacts with cancellation tools.

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, front-loaded with the core purpose, and uses a clean parameter list with no filler. Each line adds useful information, and the conditional relationship between order_type and expires_at is expressed concisely.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter tool with no annotations and zero schema-level parameter descriptions, the description is incomplete. It explains some parameters but omits key required fields like slug_or_id and outcome, and does not describe return values or post-order behavior, leaving an agent without enough context to reliably invoke the tool.

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 0%, so the description must compensate. It does add meaning for side, limit_price, order_type, and expires_at, including the price range and the conditional requirement. However, it leaves several required parameters (slug_or_id, outcome, amount) and account unexplained, so coverage is only partial.

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 states a specific action ('Place a limit order') and its key behavior ('stays open until filled or cancelled/expired'), making the tool's purpose clear. However, it does not explicitly distinguish itself from sibling tools like buy or sell, though the 'limit order' terminology largely implies the difference.

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 description implies when to use this tool: when a resting limit order is desired rather than an immediate market order. It does not provide explicit guidance about when not to use it or how it compares with the buy/sell siblings, leaving much of that decision to the agent's inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.