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agent-next

polymarket-paper-trader

by agent-next

cancel_all_orders

Cancel all open limit orders in a single request to clear pending positions and reset your paper-trading portfolio instantly.

Instructions

Cancel all pending limit orders at once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

B3/5.0
Behavior2/5

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

With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It states the action but does not mention whether this is irreversible, how it handles non-limit orders, whether it confirms the cancellation count, or any side effects. A mutation tool of this nature should specify these details, especially since the output schema is not described.

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 a single, focused sentence with no unnecessary words. The action is front-loaded, making the tool's purpose immediately clear. However, it is concise to the point of omitting essential context, but that is penalized in other dimensions. For this dimension alone, it is efficiently structured.

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?

The tool is a mutation with no annotations, no parameter explanation, and no return-value description (despite having an output schema). It does not clarify whether it cancels all orders globally or within a specific account, nor does it mention irreversibility or order-type exclusions. The description is too sparse to fully guide an agent in invoking it correctly, especially given the many sibling tools that deal with orders.

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

Parameters1/5

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

The schema has a single parameter 'account' with a default value, and schema description coverage is 0%. The description does not mention the parameter at all, leaving its purpose ambiguous. An agent cannot infer whether 'account' selects a specific trading account, a portfolio, or something else. The description fails to compensate for the lack of schema documentation.

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 states a specific action (cancel), resource (all pending limit orders), and scope (at once). It clearly distinguishes from the sibling cancel_order, which cancels a single order, by explicitly indicating batch cancellation. This is unambiguous and specific enough for an agent to understand the tool's role.

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 a clear use case: cancel all pending limit orders in one go. However, it does not explicitly name alternative tools (e.g., cancel_order for individual orders) or provide guidance on when not to use it. An agent must infer the distinction from the sibling name alone, which is a mild gap.

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