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Lumerin-protocol

@hashpower/mcp

Official

Simulate order

simulate_order

Determine if a limit order at a specified price and quantity would fill on-chain, and view the expected average fill price. Works for both buy and sell orders without placing a real order.

Instructions

On-chain simulateOrder view: would this price/qty fill, at what average? Positive qty = buy, negative = sell. Does not place an order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
priceYesLimit price in token native units, integer string
venueYes
quantityYesSigned quantity integer string
expirationAtNoRequired for futures

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that this is an on-chain read-only view, that it does not place or modify an order, and clarifies the buy/sell sign convention — all core behavioral traits. It omits peripheral details like authorization or response behavior, but the non-mutation guarantee is front-loaded and clear.

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 sentences, roughly 30 words, with the purpose question front-loaded before the sign convention and non-mutation warning. Every sentence earns its place; there is no filler or restatement of the title.

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

Completeness3/5

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

For a tool with no output schema, no annotations, and 11 siblings, the description covers the core intent but leaves several invocation details to inference: no hint of what the returned fill/average data will look like, no mention of the venue/expirationAt interaction, and no explicit distinction from check_can_place_order. Adequate and workable, but there is clear room to improve.

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 coverage is 75%, and the schema itself already documents price, quantity, and expirationAt with useful descriptions. The description adds the concrete sign convention (positive qty = buy, negative = sell), which goes slightly beyond the schema's generic 'signed quantity', but it does not compensate for or clarify the remaining parameters beyond what the schema states.

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?

States a specific verb+resource (simulate an order) and immediately answers the two key decision questions: would it fill, and at what average price. It also explicitly says 'Does not place an order,' which separates it from sibling order-building tools like build_order_tx, so an agent can tell it apart without opening schemas.

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?

Usage context is only implied: the simulate-vs-execute distinction is hinted by 'Does not place an order,' but no sibling is named and no when/when-not guidance is given. Given siblings include check_can_place_order and build_order_tx, explicit routing would meaningfully help, so the definition meets only the 'implied usage' bar.

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