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0xsl1m

cerebrus-pulse-mcp

cerebrus_liquidations

Map liquidation clusters across 5 leverage tiers for any Hyperliquid perpetual. Get cascade risk level, estimated USD at each zone, and proximity alerts to avoid cascade liquidations.

Instructions

Get estimated liquidation heatmap for a Hyperliquid perpetual. Maps where liquidation clusters sit across 5 leverage tiers (3x-50x) for both longs and shorts. Returns cascade risk level (LOW/MODERATE/HIGH/EXTREME), estimated USD at each zone, proximity to current price, long/short ratio from funding skew, and nearest cluster alert. No other MCP provider offers this signal. Cost: $0.03 USDC via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinYesCoin ticker (e.g., BTC, ETH, SOL). Case-insensitive.

Implementation Reference

  • Handler for cerebrus_liquidations — validates coin argument and calls GET /liquidations/{coin}
    elif name == "cerebrus_liquidations":
        coin = _validate_coin(arguments["coin"])
        result = _api_get(f"/liquidations/{coin}")
  • Tool definition (schema) for cerebrus_liquidations — describes input schema requiring a 'coin' string parameter
    Tool(
        name="cerebrus_liquidations",
        description=(
            "Get estimated liquidation heatmap for a Hyperliquid perpetual. "
            "Maps where liquidation clusters sit across 5 leverage tiers (3x-50x) "
            "for both longs and shorts. Returns cascade risk level "
            "(LOW/MODERATE/HIGH/EXTREME), estimated USD at each zone, proximity "
            "to current price, long/short ratio from funding skew, and nearest "
            "cluster alert. No other MCP provider offers this signal. "
            "Cost: $0.03 USDC via x402."
        ),
        inputSchema={
            "type": "object",
            "properties": {
                "coin": {
                    "type": "string",
                    "description": "Coin ticker (e.g., BTC, ETH, SOL). Case-insensitive.",
                },
            },
            "required": ["coin"],
        },
    ),
  • Registration via @server.list_tools() decorator — the Tool object for cerebrus_liquidations is included in the returned list
    @server.list_tools()
    async def list_tools() -> list[Tool]:
  • Registration via @server.call_tool() decorator — dispatches to the handler branch for cerebrus_liquidations
    @server.call_tool()
    async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
  • CLI helper mapping for liquidations tool — maps the CLI name to API path /liquidations/{coin}
    "liquidations":  ("/liquidations/{coin}", [("coin", True, str, None)]),
Behavior4/5

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

No annotations exist, so the description bears full burden. It discloses cost ($0.03 USDC) and enumerates output details (cascade risk level, USD zones, proximity, ratio, alert). This goes beyond a basic purpose statement, but does not cover rate limits, data freshness, or auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph that efficiently conveys purpose, outputs, uniqueness, and cost. It is front-loaded with the primary function. Could be slightly more structured (e.g., bullet points), but no unnecessary words.

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?

With no output schema, the description effectively enumerates output components (cascade risk, USD, proximity, ratio, alert). It also provides pricing and uniqueness. This is sufficient for an agent to understand what to expect from the tool.

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?

Schema coverage is 100% with a single parameter. The description adds context by providing examples (BTC, ETH, SOL) and specifying 'Hyperliquid perpetual,' clarifying the domain. This adds meaning beyond the schema description's 'Case-insensitive' hint.

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 clearly states 'Get estimated liquidation heatmap for a Hyperliquid perpetual.' It specifies the action (get), resource (liquidation heatmap), and platform (Hyperliquid). It distinguishes itself by noting 'No other MCP provider offers this signal,' which helps differentiate from siblings.

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?

The description implies use when liquidation data is needed, but does not explicitly state when to use or avoid, nor does it mention alternatives among sibling tools. The cost disclosure provides some guidance but lacks when-not-to-use context.

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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