book_levels
ChatGPTAnswers: what does the depth ladder look like, with the detail L2 throws away? The top price levels per side, best-first, each with total size, order count, DISTINCT WALLET count and the age of the oldest order on it — so a level held by one wallet's single order is distinguishable from the same size spread across twenty. Example: 'is SOL's 3rd bid level real depth or one wallet?' — book_levels('SOL', depth=5) and read bids[2].wallets. Snapshot-derived: refreshed every 60 s, latest-only (no history), and as_of_height is the L1 block the answer is true at — check age_s before citing it. market_orderbook remains the aggregated L2 view; this is the L4 one. Coin is case-sensitive in the node's own spelling (BTC, xyz:GOLD, #28200) and is passed through unchanged — 'btc' will 404. Pro tier.
book_stop_map
ChatGPTAnswers: where are the stops, and how much size fires if price gets there? Buckets every untriggered stop / take-profit order by distance from mid in 0.25 % steps, out to within_pct, reporting per bucket the count, size, reduce-only share, stop vs take-profit split and side split — plus totals below and above mid, the nearest trigger each side, and how many sit beyond the window. Example: 'what is stacked under BTC within 2 %?' — book_stop_map('BTC', within_pct=2) and read totals_below plus the negative buckets. Note totals_below / totals_above / nearest_* always cover EVERY trigger on the coin, while buckets is the within_pct window. Snapshot-derived: refreshed every 60 s, latest-only (no history), and as_of_height is the L1 block the answer is true at — check age_s before citing it. market_orderbook remains the aggregated L2 view; this is the L4 one. Coin is case-sensitive in the node's own spelling (BTC, xyz:GOLD, #28200) and is passed through unchanged — 'btc' will 404. Pro tier.
book_summary
ChatGPTAnswers: how deep and how lopsided is this book right now? Returns touch prices, spread in bps, and per side the size / order count / distinct wallet count within 0.5, 1, 2, 5 and 10 % of mid (nested bands, not rings), plus near- and far-band imbalance, the number of orders resting at the touch, their median age, and the share of them that are post-only. Example: 'is HYPE's bid side thinner than its ask side inside 1 %?' — book_summary('HYPE') and compare bid.bands vs ask.bands. Snapshot-derived: refreshed every 60 s, latest-only (no history), and as_of_height is the L1 block the answer is true at — check age_s before citing it. market_orderbook remains the aggregated L2 view; this is the L4 one. Coin is case-sensitive in the node's own spelling (BTC, xyz:GOLD, #28200) and is passed through unchanged — 'btc' will 404. Pro tier.
book_whales
ChatGPTAnswers: who is sitting on this book, and where? Returns the largest resting orders (wallet, side, price, size, original size, distance from mid, tif, order type, how long it has rested) and the biggest wallets per side by total resting size. Example: 'is one wallet holding up the ETH bid?' — book_whales('ETH', limit=10) and check whether bid_wallets[0].size dominates. Wallet addresses join to the trader tools (pulse_trader_profile, pulse_trader_performance). Snapshot-derived: refreshed every 60 s, latest-only (no history), and as_of_height is the L1 block the answer is true at — check age_s before citing it. market_orderbook remains the aggregated L2 view; this is the L4 one. Coin is case-sensitive in the node's own spelling (BTC, xyz:GOLD, #28200) and is passed through unchanged — 'btc' will 404. Pro tier.
builder_cohorts
ChatGPTCohort composition of a builder's attributed users over the period (day/week/month): split by all-time exchange-wide profitability tier (pnlTiers) and size tier (sizeTiers), largest cohort first, each with users, share of totalUsers, builder fees paid, attributed volume, realized PnL, and fills. Tiers are LIFETIME labels emitted as legacy slugs (money_printer..giga_rekt / leviathan..shrimp) — not the 30d-rolling tiers the pulse cohort tools use — and wallets missing from the rollup appear under 'untracked' so per-tier user counts always sum to totalUsers. Attribution slightly undercounts versus ledger revenue (trigger-order fills — see the response's dataNotes). Use for 'is builder X's user base smart money or exit liquidity?' or 'do whales or shrimp pay most of its fees?'. Requires Pro tier. Availability: computed per builder on request and can exceed its 30-second budget on large builders; if it times out, retry once a minute later.
builder_fills
ChatGPTIndividual fills attributed to a builder (0x-hex address) within a lookback window (since, e.g. '6h' or '7d', clamped to 90d), optionally filtered to one exact coin (BTC, xyz:GOLD, @123 spot, #10010 HIP-4 outcome) or one wallet. Each fill: time, wallet, coin, marketType (perp|spot|hip4), side (BUY|SELL), price, size, USD volume, realized PnL, builderFeeUsd, tid, and the order id it attributes to (null if untracked). Trigger-order (stop/TP) fills are not yet attributed, so this feed slightly undercounts versus ledger revenue — see the response's dataNotes. Use for 'show me the flow going through frontend X right now' or auditing one wallet's activity via a builder. Requires Pro tier.
builder_journey
ChatGPTHow fast and how unevenly a builder monetizes the wallets it acquires (takes only the 0x-hex builder address — no other parameters): users and minFills, avgRevenueUsd and medianRevenueUsd of lifetime attributed builder fees per qualifying wallet, concentration (avg/median — 1 = evenly spread, higher = whale-skewed, 0 when the median is 0), daysToPeak, daysToHalfRevenue and daysToThreeQuartersRevenue as {avgDays, medianDays} measured from each wallet's first attributed fill to its single highest-revenue day and to 50% and 75% of its lifetime fees, and peakDayDistribution bucketing those wallets into under7d, from7To30d and over30d. NOT the lifetime user base builder_lifecycle covers: the universe is the TRAILING-YEAR acquisition cohort — wallets whose first builder-fee order via this builder fell within the last 365 days, with at least minFills (fixed at 3) lifetime attributed fills — computed per wallet then aggregated, so young cohorts' truncated series bias the day counts low; see the response's dataNotes. Use for 'how fast and how unevenly does builder X monetize a new user?'. Requires Pro tier.
builder_leaderboard
ChatGPTBuilders (HIP-3 dexes, frontends, bots) ranked by exact revenue from Hyperliquid's on-chain cumulative builder-fee ledger over the requested period. Each row carries join-attributed fill volume, distinct users, and fill counts — plus the same metrics for the immediately preceding window for deltas — the builder's most common requested fee rate over the last 7d of orders (feeTenthsBp, tenths of a basis point), and builderName from a curated registry (omitted when unknown). Attributed metrics slightly undercount versus ledger revenue because trigger-order fills (stop/TP) are not yet attributed — see the response's dataNotes; the 'verified' stamp gives the ledger block this data was reconciled against. Use for 'which builders earn the most?' or 'is builder X growing?'. Ledger history begins at the fee ledger's first on-chain entry: dataNotes states that date whenever a window predates it, and data_coverage (builder_ledger) reports it. Requires Starter tier or higher.
builder_lifecycle
ChatGPTWhere every wallet that ever traded via this builder stands today (takes only the 0x-hex builder address — no other parameters): totalUsers split into five MUTUALLY EXCLUSIVE statuses that sum back to it, each {users, share} — active (attributed fill via THIS builder within 7d), cooling (within 30d but not 7d), switched (no fill here in 30d but at least one via a DIFFERENT builder in that window, detectable only with all-builder attribution), dormant (no fill via any builder in 30d, last fill here within 90d) and movedOn (no fill anywhere in 30d and none here in 90d) — plus trueRetention ((active+cooling)/totalUsers), churn ((dormant+movedOn)/totalUsers) and competitiveLoss (switched/totalUsers), which sum to 1, and competitiveLossFeesUsd, the builder fees those switched wallets paid to OTHER builders in the last 30d. LIFETIME universe on the ORDERS plane — every wallet that ever placed a builder-fee order via this builder, including ones whose orders never filled (they land in movedOn, or in switched if they filled via a DIFFERENT builder in the last 30d) — with only the status test reading recent attributed fills, so this is one snapshot of the whole historical user base rather than builder_retention's per-cohort monthly grid; see the response's dataNotes. Use for 'how many of builder X's users are still active, and how many did a rival take?'. Requires Pro tier. Availability: typically 1-15 seconds; can exceed its 30-second budget on the largest builders, in which case retry once a minute later.
builder_orders
ChatGPTWhat this builder's users INTEND at placement time, before anything fills (0x-hex builder address plus a day/week/month period): totalIntents — non-trigger order intents plus still-PENDING stop/TP placements, the actions denominator — an actions[] mix of {actionType, orders, share}, largest first except the 'trigger' pseudo-type which is appended last, over 'order' (plain placements), 'batchModify' (modify intents on an existing order) and 'trigger' (pending stop/TP placements), a tifs[] time-in-force mix of {tif, orders, share} over non-trigger intents ('unknown' covers market orders and older rows), reduceOnlyShare, a trigger breakdown (total, takeProfit, stopLoss, triggerMarket, triggerLimit, positionTpsl, standaloneTpsl, resolved, pending) and fillConversion {orders, filledOrders, share} — the share of non-trigger intents whose own oid took at least one attributed fill. Measured on the PLACEMENT plane, not the fill plane behind builder_fills and builder_traders, so orders that never filled still count; trigger placement history begins 2026-03-24, and a resolved placement is excluded from totalIntents and the 'trigger' action because it already surfaces as a plain 'order' row, while the trigger breakdown covers both statuses — see the response's dataNotes. Use for 'do builder X's users place stops and take-profits, and how much of their order flow actually fills?'. Requires Pro tier.
builder_overlap
ChatGPTThe top 10 OTHER builders this builder's active users also traded through in the period (day/week/month), ranked by shared users — i.e. which other frontends/bots/dexes this builder's audience also uses. Returns activeUsers (the share denominator: distinct wallets with attributed fills via this builder) and per row: the other builder's 0x address, curated builderName (omitted when unknown), sharedUsers, share of this builder's active users, and feesUsd those shared users paid to the OTHER builder in the period. Based on attributed fills, which slightly undercount (trigger-order fills — see the response's dataNotes). Use for 'who is builder X's closest competitor?' or 'where else does its audience trade?'. Requires Pro tier.
builder_profile
ChatGPTSingle-builder overview for a 0x-hex builder address: exact revenue from Hyperliquid's on-chain builder-fee ledger over the period (day/week/month), first/last fee accrual timestamps, distinct fee tokens, most common requested fee rate over the last 7d of orders (feeTenthsBp, tenths of a basis point), a daily attributed series (fees/volume/users/fills) with the biggest day highlighted, top coins by attributed volume, and how many of the period's attributed wallets are all-time profitable. Attributed metrics slightly undercount versus ledger revenue (trigger-order stop/TP fills not yet attributed — see the response's dataNotes); builderName comes from a curated registry, omitted when unknown. Returns 404 for addresses with no revenue in the fee ledger. Use for 'how is builder X doing?' or 'what do people trade on frontend Y?'. Requires Starter tier or higher. Availability: typically 10-25 seconds on large builders; the coin split (topCoins) may come back null with an explanation in dataNotes when the live pass exceeds its budget. Ledger history begins at the fee ledger's first on-chain entry (see data_coverage, builder_ledger).
builder_retention
ChatGPTMonthly retention matrix for a builder's users (takes only the 0x-hex builder address — no other parameters): wallets are cohorted by the calendar month (YYYY-MM, UTC) of their first builder-fee order via this builder, and each cohort's activeWallets[k] counts wallets still active k months later, where 'active' = placed at least one builder-fee order that month (index 0 = the cohort month itself = newWallets). Covers the last 12 calendar months, oldest cohort first. Measured on the ORDERS plane — the order need not fill — so counts can exceed the attributed-fill user counts on builder_cohorts/builder_overlap; see the response's dataNotes for the attribution caveat. Use for 'does builder X retain users month over month, or churn them?'. Requires Pro tier.
builder_traders
ChatGPTWallets that traded via a builder (0x-hex address) in the window, sortable by builder fees paid, volume, or realized PnL. Each row: wallet, realized PnL on its attributed fills, builderFeesUsd, volumeUsd, fills, latest equity (0 if untracked), and the wallet's ALL-TIME exchange-wide cohort tiers (pnlTier/sizeTier, emitted as legacy slugs like smart_money/whale; null if untracked) — lifetime labels, unlike the 30d-rolling tiers the pulse cohort tools classify by, so memberships can differ. Attributed fills slightly undercount versus ledger revenue (trigger-order stop/TP fills not yet attributed — see the response's dataNotes). Use for 'who are builder X's biggest fee payers?' or 'are smart-money wallets using this frontend?'. Requires Pro tier. Availability: this endpoint computes per builder on request and can exceed its 30-second budget on large builders; if it times out, retry once a minute later.
data_coverage
ChatGPTReport the data window (start/end or latest row) and freshness stamp of each dataset behind this server, with the API route each figure came from — check window and freshness before relying on a historical range or citing a date. Datasets: trades (indexed trade history, /pulse/stats), builder_ledger (fee ledger + attribution coverage), census (chain-state stamp), hip4 (latest outcome fill), liquidations (risk-route availability/freshness), lifecycles (latest close; rolling 90-day window), cohort_history, book (L4 order-book rollups: coins covered, latest L1 height/time and age; snapshot-derived, refreshed every 60 s, no history). Where the API exposes no window start the dataset is listed with windowStart null and a note; no date is guessed. Sources are queried sequentially (the API's per-key burst allowance is small) and a failing source is reported in that dataset's notes rather than failing the call. Also returns server { version, hiddenTools, toolCount }. Free tier (some sources need a higher tier and then report the tier gate in notes).
hip4_cross_product_overlap
ChatGPTMeasure overlap between HIP-4 outcome traders and perp traders over a recent window. Returns outcome trader count, perp trader count, overlap count, and overlap percentage. Requires a Pro-or-higher key.
hip4_daily_volume
ChatGPTGet daily HIP-4 volume trajectory: fills, unique trades, unique wallets, contracts, and notional USDH by day. Use for outcome-market activity trends. HIP-4 fills are indexed from mainnet launch (2026-05-02; the API clamps every look-back to it) — see data_coverage for freshness.
hip4_most_active
ChatGPTReturn the most active HIP-4 outcomes over a recent window, ranked by fill count. Includes outcome/question metadata when available.
hip4_outcome
ChatGPTGet details for one HIP-4 outcome contract by outcome ID. Returns metadata when available plus side tokens, fills, unique wallets, notional USDH, and trading timestamps.
hip4_outcome_recent_trades
ChatGPTGet recent real fills for one HIP-4 outcome. Excludes settlement, pair-redeem, and auction-phase fills. Returns trade time, wallet, side, price, size, PnL, and fee.
hip4_outcome_summary
ChatGPTGet the full HIP-4 summary for one outcome across both sides: fills, unique wallets, contracts, side notional, total notional, realized PnL, and trading window. Requires a Starter-or-higher key.
hip4_outcomes
ChatGPTList active HIP-4 outcome contracts that traded recently. Returns outcome IDs, question metadata when available, side tokens, fills, unique wallets, notional USDH, and first/last traded timestamps. Use when users ask what prediction/outcome markets are active. Outcomes are sorted by notionalUsdh descending and capped at limit (default 25, max 200; the API route has no paging, so the cap is applied by the connector) — the response carries count (returned), totalCount, truncated and a note; raise limit or shorten hours to see more. HIP-4 fills are indexed from mainnet launch (2026-05-02; the API clamps every look-back to it) — see data_coverage for freshness.
hip4_perp_position_context
ChatGPTJoin one HIP-4 outcome's current net-positive holders to currently open perp positions on the same underlying asset. Returns per-side wallet counts, open-position overlap, long/short wallet counts, net underlying position, underlying notional, aligned vs hedge counts, prediction-native counts, and top wallets with signal labels. Use when users ask whether outcome traders are already exposed to the same asset, whether a side is directional or hedged, or which large outcome holders have no underlying perp exposure. Requires a Pro-or-higher key.
hip4_questions
ChatGPTList HIP-4 question metadata from Hyperliquid outcomeMeta, including question IDs, descriptions, fallback outcomes, named outcomes, settlement metadata, and parsed expiry/threshold fields when present. Questions are returned newest first (questionId descending) and capped at limit (default 25, max 200; the API route has no paging, so the cap is applied by the connector) from offset — the response carries count (returned), totalCount (after filtering), truncated, hasMore and nextOffset (null on the last page — stop there) and a note naming the next offset. Narrow with status (open = nothing settled yet, settled = at least one named outcome settled) or search (matches name, description and class). For one question's outcomes use hip4_outcomes; HIP-4 is indexed from mainnet launch (2026-05-02) — see data_coverage.
hip4_recent_settlements
ChatGPTList recent HIP-4 settlements. Returns outcome ID, settlement time, winning side when determinable, winner/loser fill counts, winner payouts, and loser losses.
hip4_top_traders
ChatGPTRank top HIP-4 outcome traders by recent outcome activity. Returns address, fills, distinct outcomes, contracts, notional USDH, and realized PnL. Requires a Starter-or-higher key.
hip4_trader_outcomes
ChatGPTGet one wallet's HIP-4 outcome history: outcome ID, side index, side token, fills, net shares, gross bought/sold USDH, realized PnL, and first/last traded. Requires a Starter-or-higher key. Rows are sorted by gross notional (grossBoughtUsdh + grossSoldUsdh) descending and capped at limit (default 50, max 200; the API route has no paging, so the cap is applied by the connector) — the response carries count (returned), totalCount, truncated and a note; raise limit or shorten days to see more. The API clamps days to 90 and to HIP-4 mainnet launch (2026-05-02) — see data_coverage.
list_asset
ChatGPTLookup one asset by canonical name or synonym. Returns every venue it trades on, collateral tokens, open interest per venue, and synonyms list. Accepts both canonical names (GOLD, BTC) and synonyms (PAXG, XAUT) — the server resolves them. Use when the user mentions a specific asset and you need its venue availability.
list_assets
ChatGPTDirectory of every canonical asset that trades on Hyperliquid or any builder dex, grouped by economic exposure (not by venue ticker). Each asset entry lists its synonyms (e.g. PAXG is a synonym of GOLD), which venues it trades on, aggregated open interest, and a cross-market flag (listed on 2+ venues). Prefer this over list_markets when the user asks 'what assets are available?', 'which venues is GOLD on?', or 'show me cross-market assets'. The full directory is ~415 assets and far too large to return whole, so the connector trims it two ways (the API route offers neither): rows come back in detail='summary' form by default — identity, venue symbols and cross-venue totals, without each venue's price/funding/OI, which is what list_markets and pulse_cross_market_asset are for — and are capped at limit (default 25, max 500) from offset. The route returns the directory ordered by aggregate open interest, DESCENDING, and the connector preserves that order, so the default page is the 25 largest assets by open interest — not an arbitrary 25. The response carries count (returned), totalCount (after filtering), truncated, hasMore and nextOffset (null on the last page — stop there) and a note naming the next offset. Narrow with search (matches canonical name, synonyms and venue symbols) or crossMarketOnly before raising limit; pass detail='full' only when you actually need per-venue market data. To look up one asset you already know, use list_asset — it is one row and needs no paging.
list_markets
ChatGPTCANONICAL market discovery tool. Returns trading symbols on Hyperliquid and its builder dexes with dex, mark price, 24h volume, funding rate, open interest, and 24h change. Use this whenever the user asks 'what markets are available?', mentions a commodity (gold, silver, oil), stock (TSLA, AAPL, NVDA), or builder-dex market. For asset-level grouping across venues, use list_assets instead. The full list is ~450 markets, so the connector trims it (the API route offers no paging): markets with no open interest and no 24h volume (hasActivity=false — delisted listings, including every market on the legacy flx/vntl/hyna/km/abcd/cash dexes) are hidden unless includeInactive=true, and rows are capped at limit (default 50, max 500) from offset. Rows keep the route's order (native perps first, then each builder dex, each in Hyperliquid listing order), so paging is stable. Narrow with dex or search (substring of the symbol, e.g. 'OIL' finds xyz:BRENTOIL) before raising limit. The response carries count (returned), totalCount (after filtering), inactiveHidden, truncated, hasMore and nextOffset (null on the last page — stop there) and a note naming the next offset. The io, mkts and para dexes are not served by this route yet (see the server instructions); asking for them returns an empty list with a note. globalStats: totalTrades24h is always 0 and totalUsers is capped at 1000 by the API — use pulse_global_stats / pulse_active_traders for those figures.
live_cohort_bias
ChatGPTSee what each trader cohort is doing on a specific coin RIGHT NOW. Returns the net long/short bias for every tier (Apex, Sharps, Middleweights, etc.) on the given coin. Answers questions like 'are the Sharps traders long or short ETH?'
live_cohort_bias_history
ChatGPTGet historical cohort bias data for a specific coin. Use this when a user asks 'were smart-money cohorts accumulating or exiting?' or 'which tier flipped first?'. Returns hourly net-bias snapshots — one row per tier per hour, so the 7-day default for all 8 tiers of a category is ~1,300 rows. Returns { rows, count, totalCount, truncated, hasMore, nextOffset, note? } with rows newest first (then tier), capped at limit (default 100, max 2000) from offset; nextOffset (and the note) name the next page, and are null / 'End of results' on the last one. Pass tier for a single series, or shorten hours, before raising limit.
live_coin_risk_history
ChatGPTGet the historical risk lane for a coin. Best for questions like 'how did this setup become fragile?' or 'did smart money rotate before the move?'. Returns hourly OI, long/short history, cohort rotation, candle data, and liquidation counts over time; by default the minute-level markDislocations section is omitted (it alone is ~700 rows per 12h). Pass include=[..., 'markDislocations'] to add the complete minute-level series, or use live_mark_dislocations when you want explicit resolution and row-limit controls. The response lists sections and omittedSections. Freshness and availability are in the response's freshness/availability stamps; see data_coverage for the risk-data window.
live_coin_risk_snapshot
ChatGPTGet the current risk snapshot for a single coin. Use this when a user asks 'is BTC crowded?', 'who is holding the risk?', or 'how liquidation-prone is this market right now?'. Always returns the coin's concentration scalars — concentrationTop5, nearLiquidationNotional, nearLiquidationPositions, avgLiquidationDistancePct — plus availability/freshness stamps. Everything else is a section you opt into with include: market, longShort and topPositions are the default posture set; sizeBreakdown, liquidationHeatmap (40 buckets), liquidationSummary7d and recentLiquidations are opt-in. The response lists sections and omittedSections. topPositions is capped at limit (default 10, the API serves 20) with totalCount/truncated/hasMore/nextOffset; page with offset until nextOffset is null. For the heatmap alone use live_liquidation_heatmap; for liquidation events use live_recent_liquidations; for time series use live_coin_risk_history.
live_liquidation_heatmap
ChatGPTGet a liquidation heatmap for any coin. Shows where liquidation clusters are across price levels — essential for identifying support/resistance and potential squeeze zones.
live_liquidation_summary
ChatGPTGet an aggregated liquidation summary over a time window. This is the best liquidation tool for summaries, rankings, and trend analysis. Returns event count, penalty fees, closed PnL, per-coin rollups, and a liquidation timeline.
live_long_short_ratio
ChatGPTGet long/short ratio data. With a coin, returns that pair's ratio plus its top 5 long and short positions. Without a coin, returns the exchange-wide totals plus a per-coin breakdown (bySymbol) — ~430 coins, so the connector caps it (the API route has no paging): bySymbol keeps the route's order, largest total notional (long + short) first, capped at limit (default 25, max 500) from offset, with count (returned), totalCount, truncated, hasMore and nextOffset (null on the last page — stop there) and a note naming the next offset. The global breakdown carries no per-coin top positions (the route never fills them), so those fields are dropped from bySymbol rows; call again with coin for them. With hours, returns the history series instead (oldest first, newest limit rows kept, offset pages further back).
live_mark_dislocations
ChatGPTGet historical mark/oracle dislocation data for a coin. Use this to answer questions like 'did basis stress or oracle drift show up before liquidations?'. Returns timestamped mark price, oracle price, and basis percentage over the requested window — default 168 hours (7 days), max 720 hours (30 days). The source series is one row per minute; the connector buckets it by resolution (default 5m: the max-|basisPct| minute in each 5-minute bucket; 1h likewise; 1m = raw) and returns at most limit rows (default 500, newest kept), with totalCount, truncated and a note when rows were dropped. For 7 days at full detail use resolution=1h, or page by shortening hours. See data_coverage for the risk-data freshness stamp.
live_official_oi
ChatGPTOfficial per-dex open interest for a coin, sourced from Hyperliquid's Info API (not derived from live_positions). Returns hourly snapshots with open interest, mark price, and 24h notional volume. Use when an agent needs venue-reported ground truth, per-dex breakdown, or wants to cross-check computed OI against official numbers. Default 7 days, max 30 days.
live_oi_history
ChatGPTGet historical open interest data for any coin on Hyperliquid, or global OI across all coins. Best for identifying accumulation/distribution phases, market conviction shifts, and whether a move was backed by positioning. Default 7 days, max 30 days.
live_recent_liquidations
ChatGPTGet real liquidation events from the syncer. Best for questions like 'where did forced unwind activity actually hit?' or 'show me BTC liquidations over the last 30 days'. Returns wallet, coin, penalty fee, and closed PnL.
live_risk_overview
ChatGPTGet the exchange-wide market risk snapshot. Best for questions like 'what looks fragile right now?' or 'which coins are most crowded?'. Always returns the exchange totals — open interest, unique wallets, long/short counts, net bias, average leverage, unrealized PnL, top-10 crowding concentration and near-liquidation notional — plus availability/freshness stamps. The bulky parts are sections you opt into with include: topCrowdedCoins (default), longShort (per-coin long/short breakdown, ~25 rows), liquidationSummary7d (7-day totals plus byCoin and a daily timeline) and history (one open-interest row per market, ~325). The response lists sections and omittedSections. topCrowdedCoins, longShort.bySymbol, liquidationSummary7d.byCoin and history.oi are each capped at limit (default 10) with totalCount/truncated/hasMore/nextOffset on each list; page with offset (nextOffset null means that list is finished) or raise limit. For a coin-level view use live_coin_risk_snapshot; for time series use live_coin_risk_history.
market_historical_oi
ChatGPTGet historical hourly open interest snapshots (notional USD). Supports per-coin filtering or global exchange aggregation. Max range is 30 days.
market_orderbook
ChatGPTGet the order book (bid/ask depth) for any trading pair on Hyperliquid. Shows price levels and sizes on both sides. Essential for understanding liquidity, spread, and potential support/resistance.
market_positions
ChatGPTGet all open positions for any wallet address on Hyperliquid. Shows current entries, sizes, unrealized PnL, and leverage for each position.
market_price
ChatGPTGet current mark price for any trading pair on Hyperliquid. Use standard symbols (BTC, ETH, SOL) or builder dex format (xyz:SILVER, xyz:BRENTOIL, xyz:TSLA).
market_recent_candles
ChatGPTGet recent 1-minute candle history for a market. Best for short intraday structure checks, recent momentum, and micro-pullback analysis. This MCP tool is intentionally capped to the most recent 12 hours so agents do not fetch huge minute-bar dumps in one call.
pulse_active_traders
ChatGPTDistinct wallets that filled at least one perp trade in the last 24h, exchange-wide, plus total match count. The 'daily active traders' headline number. Cached up to 120s.
pulse_anti_survivors
ChatGPTFind wallets that blew up and never recovered — cumulative realized PnL hit a deep trough and is still underwater. Returns wallet, trough depth, and current cumulative PnL. Use for 'who got rekt and stayed rekt?'.
pulse_backstop_events
ChatGPTGet 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.
pulse_biggest_trades
ChatGPTGet the biggest winning or losing trades across all of Hyperliquid. Use type='wins' for the largest profitable trades, or type='losses' for the largest losses. Useful for market sentiment and narrative analysis.
pulse_capital_titans
ChatGPTFind the most fee-efficient traders: highest realized PnL per dollar of fees paid. Returns wallet, total PnL, total fees, PnL-per-fee-dollar ratio, and lifecycle count. Use for 'who extracts the most edge per dollar spent on fees?'. minPnl/minFees gates filter out noise.
pulse_cohort_bias_history
ChatGPTGet historical hourly bias snapshots for trader cohorts. Returns net long/short notional and account counts per tier — 32 tier rows per hour (16 PnL + 16 size tiers), so filter with tierType and/or tier for a readable series. Use this to see how different groups (whales, smart money) have shifted their positioning over time. Supports per-coin or global aggregate; the API default window is 7d, max 30d. Returns { rows, totalCount, truncated, note? } with rows newest first, capped at limit (default 100); when truncated, narrow with tierType/tier or a shorter since, or raise limit (max 2000). Cohort history is served for up to the last 30 days; see data_coverage.
pulse_cohort_history
ChatGPTGet historical performance data for a specific trader cohort over time. Shows how a tier's aggregate PnL, trade count, and activity have changed day-by-day. Use to spot trends like 'the sharps (Sharps) tier has been increasingly bearish over the last month.'
pulse_cohort_performance_daily
ChatGPTGet historical daily performance statistics for trader cohorts. Returns PnL, volume, trade counts, and active trader counts per tier — 32 tier rows per day, so filter with tierType and/or tier for a readable series. Use this to track the consistency and profitability of different groups over time. API default window 30d, max 30d. Returns { rows, totalCount, truncated, note? } sorted by date (newest first) then tierType and tier, capped at limit (default 100); when truncated, narrow with tierType/tier or a shorter since, or raise limit (max 2000). Cohort history is served for up to the last 30 days; see data_coverage.
pulse_cohort_positions
ChatGPTSee what a specific trader cohort is holding RIGHT NOW. For example, get all live positions held by 'apex' (Apex) tier traders or 'heavyweights' (Heavyweights) size wallets. This is real-time whale intelligence.
pulse_cohort_recent_alpha_concentration
ChatGPTHow concentrated profit is WITHIN a recent-tier cohort: percentile bands of the cohort's wallets and each band's share of the cohort's total PnL. Returns band, wallet count, band PnL, % of tier PnL, and tier total wallets. Use for 'within the hot apex (Apex) cohort, do a few wallets carry everything?'.
pulse_cohort_recent_lifecycle_stats
ChatGPTPer-wallet lifecycle stats for a cohort defined by its LAST-30-DAY tier: lifecycles, wins, losses, liquidations, total PnL, fees, avg hold, biggest win/loss, plus the wallet's recent pnl/size tier labels. Use for position-level analysis of who is currently printing.
pulse_cohort_recent_positions
ChatGPTLive positions held by a cohort defined by its LAST-30-DAY tier (pnl_tier_recent / size_tier_recent), not lifetime tier. Surfaces what currently-printing wallets are positioned for right now — catches regime changes the all-time pulse_cohort_positions misses.
pulse_cohort_recent_top_positions
ChatGPTTop closed position lifecycles by a cohort defined by its LAST-30-DAY tier: the biggest/most notable open->close cycles from currently-printing wallets, with entry/exit VWAP, hold duration, realized PnL, fees, and liquidation flag.
pulse_cohort_recent_trades
ChatGPTRecent trades by a cohort defined by its LAST-30-DAY tier (pnl_tier_recent / size_tier_recent). Shows what currently-printing wallets have been trading in the window — real-time alpha weighted to who is hot NOW, not all-time.
pulse_cohort_summary
ChatGPTGet behavioral cohort analysis across every tracked wallet on Hyperliquid. Returns PnL tiers (Apex/apex, Sharps/sharps, Grinders/grinders, Scrapers/scrapers, The Crowd/crowd, Bleeders/bleeders, Trapped/trapped, Blown Out/blown_out) and size tiers (Heavyweights/heavyweights, Cruiserweights/cruiserweights, Middleweights/middleweights, etc). Response payloads still use legacy slugs (money_printer, leviathan, ...). Each tier shows wallet count, avg PnL, avg win rate, and total volume. For the current tracked-wallet total, call pulse_global_stats first.
pulse_cohort_trades
ChatGPTSee every trade a specific cohort has made recently. For example: 'show me all trades the apex (Apex) tier made in the last hour.'
pulse_coin_alpha_map
ChatGPTPer-coin profit pools split into winners vs losers vs net. Returns coin, lifecycles, unique wallets, winners pool, losers pool, net PnL, winning/losing lifecycle counts, and total fees. Use for 'which coins are net wealth creators vs destroyers?'.
pulse_coin_kings
ChatGPTFind the top earner(s) per coin within the window. perCoinRank=1 returns only the #1 earner ('king') of each coin; higher values return the top-N per coin. Returns coin, wallet, coin PnL, fees, lifecycle count, and rank. Use for 'who owns BTC?' / 'who is the best trader of each market?'.
pulse_compare
ChatGPTSide-by-side comparison of 2-5 wallets via their lifecycle summaries — win rate, total/avg PnL, hold duration, biggest win/loss, fees, liquidations. Use for head-to-head trader comparison ('who is the better trader, A or B?').
pulse_cross_market_asset
ChatGPTCross-market aggregation for one asset: per-venue long/short positions, notional, net bias, unique wallets, leverage, plus a cross-venue total. Also returns biasRange (max-min netBias across venues) to detect disagreement. Accepts canonical names or synonyms (e.g. PAXG resolves to GOLD). Use when the user asks 'is gold crowded?', 'do different dexes disagree on BTC direction?', 'total OI on ETH across all venues?'.
pulse_entity_leaderboard
ChatGPTTop entities (owners, NOT wallets) ranked by combined gross open entry notional across all their sub-accounts. This is the deduplicated view a wallet leaderboard cannot give: a fund running 35 sub-accounts appears as ONE entity with its true combined book. System/protocol accounts are excluded. Each row: entity master address, wallet count, open position count, gross entry notional. Requires Pro tier.
pulse_entity_profile
ChatGPTResolve ANY wallet to its owner entity: the master account, every named sub-account (and weaker 'linked' wallets), each member's open book, the COMBINED open positions across all of them, and a 'verified vs chain at block N' stamp. Answers 'who owns this wallet?' and 'what is this trader's real total book across all their accounts?' — sub-accounts trade independently on Hyperliquid, so per-wallet views undercount every multi-account trader. Note: vaults appear as named sub-accounts of their creator. Requires Pro tier.
pulse_exchange_oi
ChatGPTCurrent open interest for the whole exchange by dex, with long/short notional split. Gross both-sides convention (matches HyperTracker/hl.eco headlines; halve for one-sided OI). Use for 'what's the OI on Hyperliquid / on xyz?', market-size questions, and long-vs-short balance checks. Cached up to 120s.
pulse_exchange_positions
ChatGPTExchange-wide position vitals by dex: open positions and wallets holding them, plus the 24h flow — positions closed, liquidations, and TOTAL REALIZED PNL across the whole exchange (gross profits/losses split). Answers 'how many positions are open on Hyperliquid?' and 'did traders collectively make or lose money today?' Cached up to 120s.
pulse_exchange_volume
ChatGPT24h trading volume for the WHOLE exchange, split by dex: native Hyperliquid ('hl') plus every builder dex (xyz, io, para, ...), with per-dex match counts and distinct traders. Use for 'how much volume does Hyperliquid do?' — and note builder dexes are a large share of it (~30% on 2026-09-23; read byDex for today's split rather than assuming). Aggregates cached up to 120s.
pulse_global_stats
ChatGPTGet global Hyperliquid trading statistics: total traders, trades, volume, PnL, and data coverage period. Use this to understand the overall scale of the market. dataStartDate/dataEndDate are the indexed trade window (from 2025-03-22); data_coverage reports the window and freshness of every dataset.
pulse_hidden_gems
ChatGPTDiscover underrated high-performing traders who fly under the radar. Filters by minimum win rate, PnL, and trade count. These are skilled traders that most platforms don't surface.
pulse_hour_profitability
ChatGPTGlobal PnL heatmap by UTC hour of position close. Returns, for each of the 24 hours, lifecycle count, total PnL, avg PnL, wins, and losses. Use for 'what time of day is most profitable to close?' / session-bias analysis.
pulse_leaderboard
ChatGPTGet ranked trader leaderboard. Sort by PnL, win rate, volume, score, or risk-adjusted returns. Filter by time period (day/week/month/allTime) and minimum trade count. Use this to find the best traders on Hyperliquid. Trade history is indexed from 2025-03-22 (pulse_global_stats.dataStartDate; see data_coverage for the current window).
pulse_lethal_coins
ChatGPTFind the most dangerous markets: coins with the highest per-lifecycle liquidation rate. Returns coin, total lifecycles, liquidations, liquidation %, and total penalty. Use for 'which coins blow people up most often?'.
pulse_lifecycle
ChatGPTLook up one position lifecycle by its numeric ID, including the trade fills that composed it (timestamp, side, size, price, PnL, fee, tx hash) joined from the trades table within the open->close window. Use after pulse_trader_lifecycles to drill into exactly how a single position was built and unwound. Fills are paged by the connector: fillsLimit (default 100, max 1000) and fillsOffset; the response carries fillCount (total fills in the lifecycle), fillsOffset, truncated, hasMore and nextOffset (the next fillsOffset; null on the last page — stop there) and a note naming it. Lifecycles are a rolling 90-day window (closed within the last 90 days, plus open ones); see data_coverage.
pulse_lifecycles_recent
ChatGPTGlobal feed of the most recently CLOSED position lifecycles across ALL wallets — 'what just closed exchange-wide right now'. Reads the corrected position_lifecycles_full table. Each row: id, address, coin, side, entryVwap, exitVwap, peakSize, notional, realizedPnl, fees, builderFee, wasLiquidated, openedAt/closedAt (+ raw ms) and durationMs. MAE/MFE (maePx/mfePx) are returned only when non-zero, and they scale with position size: on an UNFILTERED call — which is newest-first and therefore dominated by dust-sized closes — no row carries them (sampled 0 of 200 at median notional ~$270). Pass minNotional to reach positions that have them: ~42% of rows at minNotional=10000, ~89% at minNotional=100000. Plan on filtering rather than on the fields being there. Cross-wallet successor to pulse_recent_closed_positions. Filter by coin, minNotional, hold-duration range, and time window. Ordered by close time descending and bounded by since (default 1h) and limit — this is a recency feed, NOT a 90-day window, and wide windows can time out; for a wallet's full 90-day history use pulse_trader_lifecycles. See data_coverage for the lifecycle freshness stamp.
pulse_market_concentration
ChatGPTPower-law shape of trader profits: percentile bands (top 0.1%, 1%, 10%, ...) and each band's share of total profits. Returns band label, wallet count, band PnL, % of total profits, and rank range. Use for 'how concentrated is alpha — do the top 1% take everything?'.
pulse_max_pain_events
ChatGPTFind the biggest survived drawdowns: closed perp positions that went deeply underwater (high MAE) yet still closed in profit. These are 'diamond hands' winners that nearly blew up first. Returns { events, count, hasMore, nextOffset, placeholderRowsSkipped, rowsScanned, note?, dataNotes? }: each event has the position, entry/MAE/exit prices, realized PnL, and max drawdown %, deepest drawdown first. Filtered to material positions (minPnl) with bounded drawdowns. Rows whose MAE price is a placeholder of exactly 1 on a market priced far from 1 (an upstream data defect that fakes a ~99.9% drawdown) are skipped and counted in placeholderRowsSkipped; paging (limit/offset) runs over the remaining events, and nextOffset is null on the last page.
pulse_most_traded_coins
ChatGPTGet the most actively traded coins on Hyperliquid, ranked by cumulative trade count (descending). Each row: coin, traders (unique wallets), totalTrades and totalPnl. Note this route returns no volume figure — for traded volume use list_markets (24h volume per symbol) or pulse_exchange_volume. Use to understand what the market is focused on right now.
pulse_my_plan
ChatGPTShow the current API key's plan: tier, rate limits (per-minute/daily/monthly), and every tier's limits. Use when the user asks what plan they are on or after a tier/rate-limit rejection. Live remaining-quota counts also arrive on every API response as X-RateLimit-* headers.
pulse_newcomer_whales
ChatGPTFind new big players: wallets whose first-ever lifecycle is recent but who have already moved large notional. Returns wallet, first-seen date, gross notional, total PnL, and lifecycle count. Use for 'who just showed up and is already trading big?'. Lower minNotional if no rows return at default.
pulse_one_month_wonders
ChatGPTFind flash-in-the-pan traders: big winners in a single month who then gave it back. Returns wallet, best-month PnL, total PnL, giveback amount, active months, and profitable months. Use for 'who had one great month then faded?'.
pulse_perfect_exits
ChatGPTFind positions that exited near the top: closed perp positions whose exit captured a high fraction of the maximum favorable excursion (MFE). These are well-timed exits. Returns the position, entry/exit/MFE prices, realized PnL, and MFE capture % (capped at 100). Filtered to material positions (minPnl) with a real favorable move.
pulse_persistent_winners
ChatGPTFind consistently profitable wallets: traders that were profitable in N+ distinct calendar months of the 90-day window. Returns wallet, profitable-month count, total PnL, and best-month PnL. Use for 'who is consistently good, not just lucky once?'.
pulse_pnl_leaders
ChatGPTToday's biggest realized winners AND losers: wallets ranked by summed realized PnL on positions CLOSED in the last 24h, with position counts and liquidation flags. Realized-on-the-day — different from the portfolio leaderboards (which rank account value over longer windows). Use for 'who made/lost the most money today?'. Requires Starter tier or higher.
pulse_recent_closed_positions
ChatGPTGet recently closed positions across all traders. See what positions were just closed in the last N minutes/hours — with entry/exit prices and hold duration. Filterable by coin, minimum notional size, and hold duration range. Use to find: sub-second HFT trades (maxDuration=1000), positions that just got stopped out, large positions that just closed (minNotional=100000), quick scalps vs long holds.
pulse_recent_trades
ChatGPTGet the biggest trades on Hyperliquid in the last N minutes/hours. Returns trades sorted by absolute PnL — the largest movers. Use this to see what's happening right now on the exchange.
pulse_style_distribution
ChatGPTHFT vs swing vs holder PnL split, bucketed by lifecycle hold duration. Returns, per style bucket, lifecycle count, unique wallets, total PnL, avg PnL, and total fees. Use for 'do scalpers or swing traders make more money on Hyperliquid?'.
pulse_survivors
ChatGPTFind comeback traders: wallets whose cumulative realized PnL hit a deep trough and then climbed back to positive. Returns wallet, trough depth, current cumulative PnL, and recovery amount. Use for 'who blew up but recovered?'. Realized-PnL drawdown only.
pulse_token_leaderboard
ChatGPTGet the top traders for a specific coin. Answers questions like 'who are the best BTC traders?' or 'who profits most from SOL?'. Returns ranked traders with PnL, trade count, win rate, and volume for that specific coin.
pulse_top_liquidators
ChatGPTFind the wallets that execute the most liquidations (take over other traders' forced closes). Returns liquidator wallet, liquidations executed, distinct victims, distinct coins and total penalty collected. victimClosedPnl (and its older alias totalLiquidationPnl, same value) is the closed PnL of the positions that were liquidated — the VICTIMS' losses, which is why it is negative — NOT the liquidator's profit, which the data does not attribute. Use for 'who is the biggest backstop/liquidation player?'; do not report either PnL field as what a liquidator earned.
pulse_trader_closed_position_stats
ChatGPTGet aggregate statistics about a trader's closed positions: average hold duration, win rate by position (not by fill), total positions closed, and PnL summary. Use this to understand how long a trader typically holds and their position-level performance. Answers: 'What is this trader's average hold time?', 'Win rate by position (not by fill)?', 'Is this trader a scalper or swing trader?', 'Average PnL per position?'
pulse_trader_closed_positions
ChatGPTGet closed position history for any wallet. Shows every position that was opened and closed — with entry/exit prices, hold duration, PnL, and leverage. Use this to analyze a trader's position lifecycle and timing patterns. Answers: 'Show me all historical positions for this trader', 'What was the PnL and duration of each position?', 'When did this whale close their massive ETH long?'
pulse_trader_daily_stats
ChatGPTGet day-by-day performance breakdown for any trader. Each row is one active day: date, pnl, trades, winningTrades, volume and cumulativePnl (the running total over the trader's whole history, so it stays correct on any page). Use for deep due diligence and identifying consistency patterns. A long-lived wallet has hundreds of active days, so the connector pages them (the API route returns every day at once with no paging): rows come back NEWEST FIRST in days, capped at limit (default 90, max 1000) from offset, with count (returned), totalCount (after filtering), truncated, hasMore and nextOffset (null on the last page — stop there) and a note naming the next offset. Narrow to a period with startDate/endDate (YYYY-MM-DD, inclusive) instead of paging when you know the window. Note: this returns an object ({ address, days, … }), not a bare array.
pulse_trader_demo
ChatGPTGet a fast wallet briefing for demos and agent triage: lifecycle summary plus recent top wins and losses. Use when the user wants a quick read on a trader before deciding whether to run deeper lifecycle, drawdown, or token-level analysis.
pulse_trader_lifecycle_summary
ChatGPTGet a wallet's aggregate position-lifecycle stats: total/closed/open count, wins, losses, liquidations, win rate, total & avg PnL, biggest win/loss, avg/min/max hold duration, total fees, and unique coins traded. Same 90-day rolling window as pulse_trader_lifecycles. Use to size up a trader's position-level performance in one call.
pulse_trader_lifecycles
ChatGPTGet a wallet's position lifecycle history — every open->close cycle reconstructed from on-chain fills, with entry/exit VWAP, peak size, hold duration, realized PnL, fees, fill count, and liquidation status. Richer than closed-positions: each row is a full position lifecycle. 90-day rolling window (closed within the last 90 days, plus open ones; the table's first day is not exposed by the API — see data_coverage); spot (@-prefixed) excluded by default. Use for deep position-level due diligence and timing analysis.
pulse_trader_performance
ChatGPTGet performance comparison for a trader: 30-day vs all-time PnL, trade count, win rate, and trend direction (improving/declining/stable). Use this to evaluate if a trader is currently hot or cooling off.
pulse_trader_profile
ChatGPTGet full profile for any Hyperliquid trader by wallet address. Returns total PnL, trade count, win rate, volume, largest win/loss, first/last trade dates, PnL tier, size tier, and profit factor. Use this for due diligence on any wallet.
pulse_trader_token_stats
ChatGPTGet token-by-token P&L breakdown for any trader. Shows which coins they trade, their PnL per coin, win rate per coin, and volume per coin. Use to understand a trader's edge — e.g. 'this trader only makes money on ETH and loses on everything else.'
pulse_trader_trades
ChatGPTGet recent trades for a specific wallet address. See exactly what a trader has been doing in the last minutes/hours — every buy, sell, size, price, and PnL. Essential for copy-trading and due diligence. Trade history is indexed from 2025-03-22 (pulse_global_stats.dataStartDate; see data_coverage for the current window).
pulse_wallet_drawdown_curve
ChatGPTGet a wallet's per-position drawdown (MAE) and run-up (MFE) curve: for each closed perp lifecycle, the worst adverse price excursion and best favorable excursion vs entry, as percentages. Use to judge a trader's pain tolerance and exit timing — 'how far underwater did they go before it worked?'. Perp-only (spot has no MAE).
trader_builders
ChatGPTEvery builder (frontend, bot, HIP-3 dex) a wallet (0x-hex address) had attributed fills through within a lookback window (since, default '30d', clamped to 90d), ordered by builder fees paid descending. Each row: builder address, curated builderName (omitted when unknown), fills, builderFeesUsd, volumeUsd, and first/last attributed-fill timestamps within the window. Attribution slightly undercounts (trigger-order stop/TP fills not yet attributed — see the response's dataNotes). The inverse of builder_traders: wallet → builders instead of builder → wallets. Use for 'which apps does this trader use?' or 'how much has wallet X paid frontend Y in fees?'. Requires Starter tier or higher.
builder_cohorts
Claudebuilder_fills
Claudebuilder_journey
Claudebuilder_leaderboard
Claudebuilder_lifecycle
Claudebuilder_orders
Claudebuilder_overlap
Claudebuilder_profile
Claudebuilder_retention
Claudebuilder_traders
Claudehip4_cross_product_overlap
Claudehip4_daily_volume
Claudehip4_most_active
Claudehip4_outcome
Claudehip4_outcome_recent_trades
Claudehip4_outcome_summary
Claudehip4_outcomes
Claudehip4_perp_position_context
Claudehip4_questions
Claudehip4_recent_settlements
Claudehip4_top_traders
Claudehip4_trader_outcomes
Claudelist_asset
Claudelist_assets
Claudelist_markets
Claudelive_cohort_bias
Claudelive_cohort_bias_history
Claudelive_coin_risk_history
Claudelive_coin_risk_snapshot
Claudelive_liquidation_heatmap
Claudelive_liquidation_summary
Claudelive_long_short_ratio
Claudelive_mark_dislocations
Claudelive_official_oi
Claudelive_oi_history
Claudelive_recent_liquidations
Claudelive_risk_overview
Claudemarket_historical_oi
Claudemarket_orderbook
Claudemarket_positions
Claudemarket_price
Claudemarket_recent_candles
Claudepulse_active_traders
Claudepulse_anti_survivors
Claudepulse_backstop_events
Claudepulse_biggest_trades
Claudepulse_capital_titans
Claudepulse_cohort_bias_history
Claudepulse_cohort_history
Claudepulse_cohort_performance_daily
Claudepulse_cohort_positions
Claudepulse_cohort_recent_alpha_concentration
Claudepulse_cohort_recent_lifecycle_stats
Claudepulse_cohort_recent_positions
Claudepulse_cohort_recent_top_positions
Claudepulse_cohort_recent_trades
Claudepulse_cohort_summary
Claudepulse_cohort_trades
Claudepulse_coin_alpha_map
Claudepulse_coin_kings
Claudepulse_compare
Claudepulse_cross_market_asset
Claudepulse_entity_leaderboard
Claudepulse_entity_profile
Claudepulse_exchange_oi
Claudepulse_exchange_positions
Claudepulse_exchange_volume
Claudepulse_global_stats
Claudepulse_hidden_gems
Claudepulse_hour_profitability
Claudepulse_leaderboard
Claudepulse_lethal_coins
Claudepulse_lifecycle
Claudepulse_lifecycles_recent
Claudepulse_market_concentration
Claudepulse_max_pain_events
Claudepulse_most_traded_coins
Claudepulse_my_plan
Claudepulse_newcomer_whales
Claudepulse_one_month_wonders
Claudepulse_perfect_exits
Claudepulse_persistent_winners
Claudepulse_pnl_leaders
Claudepulse_recent_closed_positions
Claudepulse_recent_trades
Claudepulse_style_distribution
Claudepulse_survivors
Claudepulse_token_leaderboard
Claudepulse_top_liquidators
Claudepulse_trader_closed_position_stats
Claudepulse_trader_closed_positions
Claudepulse_trader_daily_stats
Claudepulse_trader_demo
Claudepulse_trader_lifecycle_summary
Claudepulse_trader_lifecycles
Claudepulse_trader_performance
Claudepulse_trader_profile
Claudepulse_trader_token_stats
Claudepulse_trader_trades
Claudepulse_wallet_drawdown_curve
Claudetrader_builders
Claude
