Use this when the user asks for their open/resting orders on Hyperliquid (including TP/SL trigger orders). Returns each order's oid for cancellation.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only and non-destructive behavior, so the bar is lower. The description adds meaningful context by clarifying that TP/SL trigger orders are included and that the returned oid is intended for cancellation. This explains what the agent can do with the result beyond simply reading the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences deliver all essential information with no fluff. The usage trigger is front-loaded, and the value of the return field is stated efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only tool, the description is complete: it defines the scope, includes a subtle edge case (TP/SL triggers), and states the useful return value. No output schema exists, so mentioning the oid is sufficient for an agent to understand how to use the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the schema provides complete coverage vacuously. Per the baseline for zero-parameter tools, a score of 4 is appropriate; the description correctly implies that no inputs are required and the tool operates directly on the current user's orders.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'get' with a clear resource: the user's open/resting orders on Hyperliquid. It explicitly includes TP/SL trigger orders, which distinguishes it from order history or trade history tools. The stated purpose of returning each order's oid also signals a direct link to cancellation workflows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description opens with 'Use this when the user asks for their open/resting orders,' giving clear invocation context. It does not explicitly name sibling alternatives like get_my_order_records, but the phrase 'open/resting' versus historical records provides enough differentiation for an agent to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource or action, but get_markets and get_price overlap in the data they return (price, 24h change, volume, funding), differing mainly by all-markets vs single-coin scope. The descriptions are explicit enough that an agent should rarely misselect, though the boundary is slightly blurry.
All tool names follow a consistent verb_noun snake_case pattern: get_ for reads, plus clear action verbs like place_, preview_, cancel_, close_, and set_. There is no mixing of styles or vague generic verbs.
13 tools is well within the ideal range for a trading-focused server. Each tool covers a distinct part of the workflow without feeling bloated or redundant.
The tool surface covers the full trading lifecycle: market data, account/position/order/trade reads, order preview and placement, cancellation, position closing, and TP/SL management. No obvious dead-ends or missing core operations for the stated Hyperliquid perp trading purpose.