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joshavenue

Hydromancer MCP

by joshavenue

Order book depth and slippage

hydromancer_market_depth
Read-only

Measure available USD liquidity within 0.1–2% of a market's price and estimate slippage for a specified order size across a chosen history window.

Instructions

How much can be bought or sold near the current price. Returns USD depth on each side within 0.1% to 2% of the price for a market, plus the expected slippage for a market order of a given size over time.

Input Schema

NameRequiredDescriptionDefault
coinYesMarket name, any case: "BTC", "eth", "HYPE", "kPEPE", or a HIP-3 market such as "xyz:TSLA".
sinceNoSlippage history window. Default "24h".
orderSizeUsdNoOrder size for the slippage estimate, in USD (default 100,000).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context beyond annotations: it specifies that depth is reported in USD within a 0.1% to 2% price band and that slippage is estimated over time for a given order size. It does not mention rate limits or auth, but for a read-only market-data tool this is a meaningful addition.

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?

The description is two tight sentences with no filler, and the core purpose is front-loaded before the return details. Every sentence contributes useful information about what is returned.

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

Completeness4/5

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

With no output schema, the description appropriately explains the return values: USD depth within a price band and expected slippage for a given order size over time. The simple three-parameter schema is well covered. It is slightly incomplete only because it lacks usage guidance and a fuller description of the return shape.

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 schema already documents coin, since, and orderSizeUsd in detail. The description loosely maps to those parameters by mentioning 'a market', 'given size', and 'over time', but it does not add syntax or default information beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource and return type: USD order book depth on each side and expected slippage for a market order. It clearly distinguishes the tool conceptually from sibling tools like market_snapshot or price_history by focusing on liquidity depth and slippage. It does not explicitly name a sibling, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the tool returns but gives no explicit guidance on when to use it versus alternatives such as market_snapshot or price_history. There are no exclusions, prerequisites, or named alternatives. Usage must be inferred from the purpose statement alone.

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