Recipe 9 of 33
Rank every Hyperliquid coin by smart-money conviction and liquidation risk
Take smart-money bias per coin from the realized-PnL heatmap and the share of open interest near liquidation from the risk ranking, join them on symbol, and sort.
GET /v1/hl-cohorts/heatmap and GET /v1/hyperliquid/liquidations/risk answer it in two calls that cover every
coin. /heatmap?axis=pnl gives, per coin, the long and short notional of
each realized-PnL cohort; sum the 3x smart, 2x smart and smart cells for a smart-money bias.
/liquidations/risk?limit=500 gives, per coin, percent_risk,
the share of open notional in positions that have used more than half of the distance from entry to their
liquidation price. Join the two on symbol and rank.
Quick answer
Two calls, each covering every coin.
# every coin by realized-PnL cohort at the newest snapshot
curl -H "X-API-Key: $VIKE_API_KEY" \
"https://data.vike.io/v1/hl-cohorts/heatmap?axis=pnl"
# every coin's share of open notional near liquidation, the most at risk first
curl -H "X-API-Key: $VIKE_API_KEY" \
"https://data.vike.io/v1/hyperliquid/liquidations/risk?limit=500"Example response
Captured from the live API on 2026-10-24 at 17:12 UTC from the risk call with limit=5, trimmed to 3 rows.
percent_risk is a fraction from 0 to 1 despite its name: risk_value_usd / total_value_usd.
The top of the ranking is small builder-DEX markets, such as para:UNITREE with $2.1M of open
notional. On the heatmap side, BTC's three smart cohorts held $2.14B in this capture with a bias of
-0.10, so they leaned slightly short.
[
{
"symbol": "para:UNITREE",
"total_value_usd": 2113897.8153999997,
"risk_value_usd": 1071192.13365,
"percent_risk": 0.5067378970952316,
"positions_count": 114,
"at_risk_count": 9,
"cohort_axis": "size",
"cohort": null
},
{
"symbol": "io:NBIS",
"total_value_usd": 7650584.123199999,
"risk_value_usd": 3601011.4597,
"percent_risk": 0.4706845126740218,
"positions_count": 296,
"at_risk_count": 51,
"cohort_axis": "size",
"cohort": null
},
{
"symbol": "para:GLW",
"total_value_usd": 789788.5558,
"risk_value_usd": 370461.34382899996,
"percent_risk": 0.4690639552933871,
"positions_count": 40,
"at_risk_count": 12,
"cohort_axis": "size",
"cohort": null
}
]Variations
Keep markets big enough to matter. The route has no size filter, so cut by notional after the call.
# risk ranking for coins with at least $50M of open notional
curl -s -H "X-API-Key: $VIKE_API_KEY" \
"https://data.vike.io/v1/hyperliquid/liquidations/risk?limit=500" \
| jq '[.[] | select(.total_value_usd >= 50000000) | {symbol, percent_risk, total_value_usd}] | .[:10]'Smart-money bias per coin in one pass. Sum the three smart cells of each coin straight from the heatmap.
# smart-money long, short and bias per coin
curl -s -H "X-API-Key: $VIKE_API_KEY" \
"https://data.vike.io/v1/hl-cohorts/heatmap?axis=pnl" \
| jq '[.heatmap[] | {symbol, l: ([.segments[] | select(.cohort | test("smart")) | .total_long_value] | add), s: ([.segments[] | select(.cohort | test("smart")) | .total_short_value] | add)} | select(.l != null) | . + {bias: ((.l - .s) / (.l + .s))}] | sort_by(-.bias) | .[:10]'Risk inside the smart cohort only. axis and cohort restrict the risk ranking to one cohort's positions.
# how close the top 1% by realized PnL are to liquidation, per coin
curl -H "X-API-Key: $VIKE_API_KEY" \
"https://data.vike.io/v1/hyperliquid/liquidations/risk?axis=pnl&cohort=3x_smart&limit=500"The Smart Money Index for a short list. /symbols/{symbol}/indices adds smi and its hourly history, one coin per call.
# BTC Smart Money Index now and for the last week
curl -H "X-API-Key: $VIKE_API_KEY" \
"https://data.vike.io/v1/hl-cohorts/symbols/BTC/indices"Before you rely on it
You build the ranking; thin markets lead the risk list
No endpoint returns this ranking: you join two responses on symbol and pick the score. The risk
list is sorted by percent_risk alone, so micro-cap builder-DEX markets top it; filter on
total_value_usd first. A coin with no smart-cohort position has no smart bias, not a bias of 0.
/indices takes one call per coin, so use it for a short list, not for all 342.
Ask your agent
Connected to the Vike MCP server (https://vike.io/mcp) in Claude, ChatGPT or Cursor, ask it in plain words.
The hl_segments tool answers (view heatmap), with hl_liquidations for the risk ranking, at 1 credit a call each.
Rank Hyperliquid coins over $50M of open interest by smart-money bias and share near liquidation