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Simulate Equity Vault Deposit

simulate_equity_deposit
Read-only

Preview depositing USDG into a stock + yield equity vault — deterministic, read-only, no wallet. You end up 1x long the stock (held as your own Morpho collateral), with stockLtvPct of its value borrowed as USDG and flash-looped into the vault's yield strategy. Returns the stock received, the borrow, the stock liquidation price and headroom, the yield leg's size/leverage/APY, the net APY at that LTV, fees and price impact per leg.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesDeposit amount in human units of the vault's deposit token (USDG), e.g. '10000'.
chainIdNoChain to target. Supported: 1, 4663. Default: 1.
slippageNoSwap slippage ratio. Default 0.01 (the app's setting for vaults), capped at 0.01.
strategyIdYesThe vault's id from list_strategies (starts with 'equity-').
stockLtvPctNoStock-leg LTV percent to borrow at (e.g. '50'). Default: the vault's targetLtvPct. Capped at 88% of the stock market's liquidation LTV (55 on a 62.5% market) — a higher value is refused, not clamped.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description adds 'deterministic, read-only, no wallet' and explains the resulting position mechanics, including the 1x long and flash-looped yield leg. It also enumerates the returned metrics, giving a full picture of what the tool computes. No contradiction with annotations.

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 well-structured sentences: the first states the action and constraints, and the second enumerates the computed results. Every sentence earns its place with no filler or redundancy.

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 read-only simulation with no output schema, the description compensates by explicitly listing the outputs: stock received, borrow, liquidation price/headroom, yield leg size/leverage/APY, net APY, fees, and price impact. Combined with the fully documented input schema, the tool is complete for an agent to invoke and interpret.

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 100%, so the baseline is 3; the schema already documents all five parameters. The description adds minor context by referencing stockLtvPct in the mechanics, but does not materially add meaning beyond the schema.

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 opens with a specific verb and resource: 'Preview depositing USDG into a stock + yield equity vault'. It also immediately distinguishes the tool from transaction builders by saying 'deterministic, read-only, no wallet'.

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 clearly frames this as a preview/simulation tool and notes that no wallet is required, which tells the agent when to use it before a build_equity_deposit_tx call. It does not explicitly name alternatives or state exclusions, but the usage context is unambiguous.

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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