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Recent liquidations

liquidations
Read-onlyIdempotent

Liquidation trades for a pair with the long and short breakdown, live tape merged with the recorded series so a restart never erases history. A long is force-closed by selling, so sell-side events are long liquidations. long_liquidations and short_liquidations are event COUNTS; long_usd and short_usd carry the dollar split. Pass hours to ask for a period (hours: 24 for today); without it you get the most recent rows and window_minutes tells you how far back they reach. truncated:true means more events matched than were returned, so window_minutes covers the returned rows only and total_in_window has the real count. Descriptive market data only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinNoAlias for pair.
pairNoe.g. ETH/USD. A bare symbol like ETH also works.
hoursNoLook back this many hours, up to 720. Omit for the most recent events.
limitNoMax rows returned. Capped at 25 keyless and 1000 on a developer plan; asking for more returns the cap, and the payload says so in `capped`. count and the *_usd totals always cover the whole window regardless.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoOne line saying what the numbers cover, or why there are none. Read it before reporting any zero as a market reading.
pairNoThe pair these events belong to.
countNoHow many events fired in the whole window, not how many rows came back.
cappedNoPresent only when an argument was cut down to a ceiling. Absent means nothing was clamped, so a smaller number than you asked for is the data and not a limit.
sourcesNoHow the events split between the streamed exchanges and Hyperliquid, and whether the Hyperliquid part is a sample.
long_usdNoDollars of longs force-closed across the window.
availableNoFalse when this lane could not answer: a producer is dark, the pair sits outside this plan, or the argument named something we do not carry. Absent or true means the numbers are a real reading, not a guess.
short_usdNoDollars of shorts force-closed across the window.
truncatedNoTrue when more rows matched than were returned, so what you have is a page and not the whole set.
access_noteNoWhat this connection could not return and what lifts it. Always pass this on to the user: it is the only place that information appears.
liquidationsNoThe events themselves, newest first: price, size in base and quote, side (long_liquidated or short_liquidated), exchange and time. A sample of the window when truncated is true.
window_hoursNoThe period the totals cover, in hours.
rows_returnedNoHow many event rows are actually in this reply.
window_minutesNoThe same period in minutes.
requested_hoursNoThe period asked for, so a page can be told apart from a period.
total_in_windowNoHow many events the window holds in total.
history_includedNoTrue when the recorded series was merged in, so a restart has not erased earlier events.
total_volume_usdNoDollars forced out across the whole window.
long_liquidationsNoCOUNT of longs force-closed. For dollars read long_usd.
rows_span_minutesNoHow far back the returned rows themselves reach.
short_liquidationsNoCOUNT of shorts force-closed. For dollars read short_usd.

TDQS

A4.1/5.0
Behavior5/5

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

The description richly discloses behavioral traits beyond annotations: live tape merged with recorded series, long liquidations defined as sell-side events, count vs. USD field semantics, window_minutes behavior, truncated:true semantics, and total_in_window. This is strong added context that complements the readOnlyHint and idempotentHint annotations.

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 dense but every sentence adds value, covering merge behavior, liquidation mechanics, field semantics, and truncation edge cases. It is front-loaded with the core purpose and flows logically into parameter behavior, though it is somewhat long for a list-style tool.

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?

The description covers all relevant edge cases: omitted hours, truncated results, limit caps, and interpretation of count vs. USD fields. Combined with the output schema being present, an agent has everything needed to invoke and interpret 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% for parameters, so the baseline is 3. The description adds meaningful extra semantics, such as hours:24 meaning today, omitting hours returning the most recent rows with window_minutes, limit caps returning a capped flag, and totals always covering the whole window. This goes well beyond the schema's property descriptions.

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 clearly states what the tool returns: liquidation trades for a pair with a long/short breakdown, identifying the resource and scope. It is specific about field semantics but does not explicitly differentiate from sibling tools like market_liquidations or defi_liquidations, so it lacks explicit sibling routing.

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 gives useful parameter-level usage guidance, such as passing hours for a period and the default behavior when hours is omitted. However, it does not state when to prefer this tool over alternative liquidation tools or provide exclusion criteria, leaving selection 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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TDQS

A3.6/5.0
Disambiguation3/5

Many tools share the same broad purpose domains, such as market_digest vs market_overview vs market_snapshot and whale_context vs whale_profile vs whale_flow, making selection genuinely ambiguous for an agent. The long descriptions help separate them, but the sheer number of overlapping 'one-call' market and whale views still invites misselection, and whale_tape is a direct duplicate alias.

Naming Consistency4/5

Names are consistently snake_case and mostly follow a clear domain-prefix pattern: market_*, whale_*, hl_*, defi_*. Minor deviations like liquidations vs market_liquidations, liq_zones, my_access, and the deprecated whale_tape keep it from a perfect score, but the overall convention is predictable and readable.

Tool Count2/5

With 30 tools, the server exceeds the reasonable upper bound and feels heavy even for a broad data domain. Many tools could be consolidated—for instance, several one-call market summary tools and multiple whale-flow variants—without losing capability.

Completeness4/5

The tool set covers an impressively wide range of whale and market data: news, liquidations, funding, DEX activity, Hyperliquid wallets, market scans, history, and plan access. There are minor gaps such as no general price/OHLC history or per-wallet trade history beyond swaps and fills, but agents can work around these using the existing surface.

Resources