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Coinversaa

Coinversaa Pulse

Official

pulse_backstop_events

Identify the largest forced liquidations on Hyperliquid, ranked by realized loss. Returns wallet, coin, side, entry VWAP, peak size, and more for post-mortem analysis.

Instructions

Get the most catastrophic individual liquidations across Hyperliquid — large forced closes ranked by loss. Returns wallet, coin, side, entry VWAP, peak size, realized PnL, penalty fee, liquidation method, and liquidator address. Use for 'who got wrecked hardest?' and post-mortem analysis. Default returns $10k+ losses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
useToonFormatNoReturn data in compact toon format (default: true). Set to false for standard JSON.
methodNoOptional liquidation method filter (e.g. 'market', 'backstop').
maxRealizedPnlNoOnly return losses at least this large (negative). Default -10000 = $10k+ losses.
limitNoNumber of events to return.
offsetNoPagination offset.
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 the tool returns specific fields (wallet, coin, side, entry VWAP, etc.) and defaults to $10k+ losses. It does not mention rate limits or other behavioral traits, but the description is transparent about the data scope. No contradictions.

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 three well-structured sentences: first states purpose and scope, second lists return fields, third gives use case and default. No redundant information; every sentence is informative. It is appropriately concise.

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?

For a tool with 5 parameters and no output schema, the description adequately explains what the tool does and the key filter (default loss threshold). It could mention pagination behavior, but that is covered by the schema parameters (offset/limit). Overall, it provides sufficient context for an agent to use the tool 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 100%, so baseline is 3. The description adds value by explaining the default of maxRealizedPnl ("Default returns $10k+ losses") and gives context for the default filter. This clarifies the parameter's meaning beyond the schema description, justifying a score above baseline.

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 the most catastrophic individual liquidations across Hyperliquid — large forced closes ranked by loss.' It specifies the resource (liquidations), action (get), and ranking (by loss). It implicitly distinguishes from siblings like pulse_top_liquidators and live_recent_liquidations by focusing on catastrophic losses.

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 provides explicit use cases: 'Use for "who got wrecked hardest?" and post-mortem analysis.' It does not explicitly state when not to use or compare to alternatives, but the purpose is clear enough to guide selection among sibling tools. A slight improvement would be contrasting with related tools.

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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