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get_my_open_orders

Read-only

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already establish read-only, non-destructive behavior, so the description need not repeat that. The description adds valuable context by noting that the tool covers TP/SL trigger orders and returns oids specifically for cancellation, which is useful behavioral detail beyond the annotation fields.

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?

Two short sentences with no filler. The trigger condition is front-loaded, and the second sentence adds a concrete, useful detail about the return value. Every part of the description contributes to correct tool selection and invocation.

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

Completeness5/5

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 with annotations covering safety and an empty schema, the description is complete. It states the purpose, the trigger, the scope (including TP/SL orders), and the key return information needed for the likely follow-up action (cancellation).

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

Parameters4/5

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

The tool has zero parameters and 100% schema coverage, so there is nothing for the description to clarify about inputs. The description still clarifies the implicit scope ('my' open orders) and the inclusion of trigger orders, which compensates for the absence of parameters.

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 uses a specific verb ('get') and resource ('my open/resting orders on Hyperliquid'), and explicitly includes TP/SL trigger orders, which distinguishes it from historical order records or trade history. It clearly identifies what the tool returns (each order's oid) and the intended use case.

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 opens with 'Use this when the user asks for their open/resting orders,' providing a clear, explicit trigger for invocation. It does not explicitly name alternatives or exclusion criteria, but the phrasing and inclusion of trigger orders give enough context to route to this tool over siblings like get_my_order_records.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool maps to a distinct resource/action: market data, account state, resting orders, audit records, fills, order placement, and risk management. The only close pair, preview_order and place_order, is clearly delineated as validation vs execution.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (get_, place_, cancel_, close_, set_). The object names are uniform and predictable, making the set easy to navigate.

Tool Count5/5

13 tools is well-scoped for a trading server: market data, account/order queries, execution, and position risk each have coverage without redundancy or bloat.

Completeness4/5

The surface covers the core trading lifecycle: market data, account, preview/place/cancel, close position, TP/SL, and historical records. Minor gaps exist (e.g., no modify-order operation and no standalone position detail endpoint), but agents can work around them via cancel/replace and get_my_account.

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