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by parkyucheol-del
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Python
Remote

market.oracle_gap_bp

Check a Hyperliquid perpetual's oracle gap in basis points and elevated flag for a coin, returning only threshold-relevant numbers without full prices.

Instructions

Cheap-tier thin wrapper around market.oracle_gap: same call, same cache,
but trims the response to just the bp gap numbers and the elevated flag
(no absolute mid/mark/oracle prices). No new upstream call. Use this
instead of get_oracle_gap when all you need is the gap size for a
threshold check.

Args:
    coin: Hyperliquid perpetual ticker, e.g. "ETH" or "BTC".

Returns:
    On success: {"success": true, "coin", "mid_oracle_gap_bp",
        "mark_oracle_gap_bp", "elevated", "alert_threshold_bp", ...}
    On failure: {"success": false, "error": {"type", "message"}}

Input Schema

NameRequiredDescriptionDefault
coinYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that it is a thin cache-shared wrapper with 'no new upstream call' and that it trims the payload (no absolute mid/mark/oracle prices), and it documents both success and failure shapes. It stops short of stating rate limits or auth needs, but the read-only, cached nature is clear enough.

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?

Front-loads the key distinction (thin wrapper, same cache) before the routing advice, then gives compact Args/Returns blocks. Slightly more verbose than strictly necessary, but every section earns its place given the absent output schema.

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 single-parameter tool with no annotations and no output schema, the description supplies purpose, routing guidance, parameter format, and an explicit return shape including the error structure. An agent has everything needed to call it correctly.

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 0%, so the description must compensate, and it does: it defines 'coin' as a Hyperliquid perpetual ticker with examples ('ETH', 'BTC'). This adds real meaning beyond the bare string type in 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?

States a specific verb and resource (a thin wrapper returning the oracle gap in basis points) and explicitly contrasts itself with the sibling market.oracle_gap. An agent can distinguish this from get_oracle_gap solely from the description, since it names the trimmed payload.

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

Usage Guidelines5/5

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

Explicitly says 'Use this instead of get_oracle_gap when all you need is the gap size for a threshold check,' naming both the alternative and the selecting condition. Nothing is left to inference.

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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