[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6X9437CQ55N5AYHCPF71JWG":3,"skill-same:01M6X9437CQ55N5AYHCPF71JWG":87},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":53,"repositoryHtmlUrl":54,"repositoryHomepageUrl":6,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6X9437CQ55N5AYHCPF71JWG","whale-index",null,"Auto-mirror top Discovery traders on Hyperliquid. Scans top 50 traders, scores on PnL rank (35%), win rate (25%), consistency (20%), hold time (10%), drawdown (10%). Creates 2-5 mirror strategies with overlap checks. Daily rebalance with 2-day watch period before swaps. Use when setting up trader mirroring, copy trading, or portfolio auto-rebalancing based on Discovery leaderboard performance.","enuno\u002Fcrewless-capital","enuno","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6727752?v=4","01M6J09HF6Y74150F7PEMC446X","Elvis Nuno","01M6X86WGZG9RH09ACTSTJ2383",1,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"index","whale index","whale","strategies","when","pnl","for","mirror","top","consistency","with","performance","time","daily","up","auto","use","discovery","monitoring","auth","2026-11-10 10:12:30",false,"---\nname: whale-index\ndescription: >-\n  Auto-mirror top Discovery traders on Hyperliquid. Scans top 50 traders,\n  scores on PnL rank (35%), win rate (25%), consistency (20%), hold time (10%),\n  drawdown (10%). Creates 2-5 mirror strategies with overlap checks.\n  Daily rebalance with 2-day watch period before swaps.\n  Use when setting up trader mirroring, copy trading, or portfolio\n  auto-rebalancing based on Discovery leaderboard performance.\nlicense: Apache-2.0\ncompatibility: >-\n  Requires mcporter (configured with Senpi auth) and cron for daily monitoring.\nmetadata:\n  author: jason-goldberg\n  version: \"1.0\"\n  platform: senpi\n  exchange: hyperliquid\n---\n\n# Whale Index — Auto-Mirror Top Discovery Traders\n\nScan the Discovery leaderboard, score traders, create mirror strategies, and rebalance daily. Set your risk level and budget — the agent handles selection, allocation, monitoring, and swaps.\n\n## Skill Attribution\n\nWhen creating a strategy, include `skill_name` and `skill_version` in the call. See `references\u002Fskill-attribution.md` for details.\n\n---\n\n## 5-Step Flow\n\n### Step 1: Onboard the User\n\nCollect: budget, risk tolerance (conservative\u002Fmoderate\u002Faggressive).\n\n| Budget | Slots |\n|--------|-------|\n| $500-$2k | 2 |\n| $2k-$5k | 3 |\n| $5k-$10k | 4 |\n| $10k+ | 5 |\n\nRisk mapping:\n\n| Risk | Allowed Labels | Max Leverage |\n|------|---------------|-------------|\n| Conservative | ELITE only | 10x |\n| Moderate | ELITE, RELIABLE | 15x |\n| Aggressive | ELITE, RELIABLE, BALANCED | 25x |\n\n### Step 2: Discover Traders\n\n**2a. Pull candidates:** `discovery_top_traders(limit=50, timeframe=\"30d\")`\n\n**2b. Hard filters:**\n- Consistency label matches risk level\n- Risk label matches risk level\n- Min 30d track record\n- Not already in user's portfolio\n\n**2c. Score remaining candidates:**\n\n```\nscore = 0.35 × pnl_rank + 0.25 × win_rate + 0.20 × consistency + 0.10 × hold_time + 0.10 × drawdown\n```\n\nAll components normalized 0-100.\n\n**2d. Overlap check:** Compare active positions across selected traders. Flag >50% position overlap.\n\n**2e. Allocation weighting:**\nScore-weighted allocation with 35% cap per slot. Re-normalize after capping.\n\n### Step 3: Present & Confirm\n\nShow the user: trader address, rank, labels, win rate, allocation amount. Wait for approval before executing.\n\n### Step 4: Execute\n\nFor each slot:\n1. Create mirror strategy via `strategy_create_mirror`\n2. Set strategy-level stop loss (-10% conservative, -15% moderate, -25% aggressive)\n3. Confirm mirroring is active\n\n### Step 5: Daily Monitoring (Cron)\n\nSee [references\u002Fdaily-monitoring.md](references\u002Fdaily-monitoring.md) for the complete daily check procedure, swap criteria, and rebalance logic.\n\n**Swap criteria (ALL must be true):**\n1. Degraded: dropped below rank 50 OR consistency fell OR inactive 48h+ OR drawdown 2× historical\n2. Sustained: WATCH status for 2+ consecutive days (tracked via `watchCount`)\n3. Better alternative: replacement scores ≥15% higher\n4. User's strategy-level SL not hit\n\n**Key principle:** The 2-day watch period prevents churn from temporary dips.\n\n## Teardown\n\nTo exit: close all mirror strategies, return funds to main wallet.\n\n## API Dependencies\n\n- `discovery_top_traders` — trader leaderboard\n- `strategy_create_mirror` — create mirror strategy\n- `strategy_get_clearinghouse_state` — check positions\n- `strategy_close_strategy` — teardown\n\n## Fee Estimates\n\nMirror strategies incur the same trading fees as the mirrored trader's activity. Budget ~0.5-1% daily in fees for active traders.\n","# Whale Index — Auto-Mirror Top Discovery Traders\n\nScan the Discovery leaderboard, score traders, create mirror strategies, and rebalance daily. Set your risk level and budget — the agent handles selection, allocation, monitoring, and swaps.\n\n## Skill Attribution\n\nWhen creating a strategy, include `skill_name` and `skill_version` in the call. See `references\u002Fskill-attribution.md` for details.\n\n---\n\n## 5-Step Flow\n\n### Step 1: Onboard the User\n\nCollect: budget, risk tolerance (conservative\u002Fmoderate\u002Faggressive).\n\n| Budget | Slots |\n|--------|-------|\n| $500-$2k | 2 |\n| $2k-$5k | 3 |\n| $5k-$10k | 4 |\n| $10k+ | 5 |\n\nRisk mapping:\n\n| Risk | Allowed Labels | Max Leverage |\n|------|---------------|-------------|\n| Conservative | ELITE only | 10x |\n| Moderate | ELITE, RELIABLE | 15x |\n| Aggressive | ELITE, RELIABLE, BALANCED | 25x |\n\n### Step 2: Discover Traders\n\n**2a. Pull candidates:** `discovery_top_traders(limit=50, timeframe=\"30d\")`\n\n**2b. Hard filters:**\n- Consistency label matches risk level\n- Risk label matches risk level\n- Min 30d track record\n- Not already in user's portfolio\n\n**2c. Score remaining candidates:**\n\n```\nscore = 0.35 × pnl_rank + 0.25 × win_rate + 0.20 × consistency + 0.10 × hold_time + 0.10 × drawdown\n```\n\nAll components normalized 0-100.\n\n**2d. Overlap check:** Compare active positions across selected traders. Flag >50% position overlap.\n\n**2e. Allocation weighting:**\nScore-weighted allocation with 35% cap per slot. Re-normalize after capping.\n\n### Step 3: Present & Confirm\n\nShow the user: trader address, rank, labels, win rate, allocation amount. Wait for approval before executing.\n\n### Step 4: Execute\n\nFor each slot:\n1. Create mirror strategy via `strategy_create_mirror`\n2. Set strategy-level stop loss (-10% conservative, -15% moderate, -25% aggressive)\n3. Confirm mirroring is active\n\n### Step 5: Daily Monitoring (Cron)\n\nSee [references\u002Fdaily-monitoring.md](references\u002Fdaily-monitoring.md) for the complete daily check procedure, swap criteria, and rebalance logic.\n\n**Swap criteria (ALL must be true):**\n1. Degraded: dropped below rank 50 OR consistency fell OR inactive 48h+ OR drawdown 2× historical\n2. Sustained: WATCH status for 2+ consecutive days (tracked via `watchCount`)\n3. Better alternative: replacement scores ≥15% higher\n4. User's strategy-level SL not hit\n\n**Key principle:** The 2-day watch period prevents churn from temporary dips.\n\n## Teardown\n\nTo exit: close all mirror strategies, return funds to main wallet.\n\n## API Dependencies\n\n- `discovery_top_traders` — trader leaderboard\n- `strategy_create_mirror` — create mirror strategy\n- `strategy_get_clearinghouse_state` — check positions\n- `strategy_close_strategy` — teardown\n\n## Fee Estimates\n\nMirror strategies incur the same trading fees as the mirrored trader's activity. Budget ~0.5-1% daily in fees for active traders.\n",{"name":5,"license":15,"metadata":44,"description":7,"compatibility":49},{"author":45,"version":46,"exchange":47,"platform":48},"jason-goldberg","1.0","hyperliquid","senpi","Requires mcporter (configured with Senpi auth) and cron for daily monitoring.","main","bfe4e4653cba696a8dc20f70c6006651b997fdef","migrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index",0,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital","https:\u002F\u002Fgithub.com\u002Fenuno","https:\u002F\u002Fenuno.github.io\u002FDynamicCareerCanvas","Digital Nomad, Blockchain Evangel, and Digital Solutions Architect. \r\nCreator of TerraHash Stack.\r\nCEO of Ryno Crypto Mining Services.","2026-07-02 10:49:15",{"source":8,"skillName":5,"commands":60,"prompt":70,"zipAvailable":71},[61,64,67],{"tool":62,"command":63},"npx","npx skills add enuno\u002Fcrewless-capital --skill whale-index",{"tool":65,"command":66},"bunx","bunx skills add enuno\u002Fcrewless-capital --skill whale-index",{"tool":68,"command":69},"pnpm","pnpm dlx skills add enuno\u002Fcrewless-capital --skill whale-index","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index\u002FSKILL.md",true,[73,79,83],{"path":74,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":77,"sourceHtmlUrl":78},"readme.md","REFERENCE","参考文档",3010,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index\u002Freadme.md",{"path":80,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":81,"sourceHtmlUrl":82},"references\u002Fdaily-monitoring.md",3292,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index\u002Freferences\u002Fdaily-monitoring.md",{"path":84,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002Fskill-attribution.md",415,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index\u002Freferences\u002Fskill-attribution.md",[88,117,143,167,190,212],{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":99,"publishedAt":39},"01M6X94YFR1XNANZ321FS661NG","supermemory","Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static\u002Fdynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsupermemory\u002FSKILL.md",[94],{"categoryNo":95,"categoryName":96,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[90,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,25,115,116,23],"ai agents","memory","rag","semantic search","infrastructure","search","applications","api","knowledge","context","Art","personalization","across","learned","retention","persistent memory","static",{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":124,"publishedAt":39},"01M6X94S3K97CSK7VFF5H85ED2","wolverine-strategy","WOLVERINE v2.0 — HYPE alpha hunter. Entry-only scanner, DSL-exit-only architecture. v1.1 lost -22.7% because the scanner's thesis exit chopped 25\u002F27 trades before DSL could manage them. v2.0 removes thesis exit entirely. Scanner decides entries (score 8+, 4H\u002F1H aligned, SM consensus). DSL manages all exits (wide Phase 1 for HYPE volatility, trailing tiers starting at +15% ROE). Leverage lowered to 7x. Max 4 entries\u002Fday. 3-hour cooldown between entries. DSL exit managed by plugin runtime via runtime.yaml.","MIT","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwolverine\u002FSKILL.md",[],[125,126,127,128,129,130,131,132,133,134,135,47,136,137,138,139,25,140,141,142],"strategy","wolverine strategy","architecture","alpha","Volatility","consensus","only","trading","scanner","manage","max","runtime","leverage","hunter","at","managed","dsl","phase",{"skillNo":144,"name":145,"nameZh":6,"description":146,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":147,"categories":148,"keywords":152,"publishedAt":39},"01M6X94HN3CHBM37GM2C84KT26","wolf-strategy","WOLF v6.3 — Fully autonomous multi-strategy trading for Hyperliquid perps via Senpi MCP. Manages multiple strategies simultaneously, each with independent wallets, budgets, slots, and DSL configs. 5+N cron architecture: 5 shared wolf crons (Emerging Movers 3min, SM Flip 5min, Watchdog 5min, Risk Guardian 5min, Health Check 10min) plus one DSL v5.2 cron per strategy (native Hyperliquid SL sync via dsl-dynamic-stop-loss skill v5.3.1). Same asset can be traded in different strategies simultaneously. Enter early on first jumps, not at confirmed peaks. Dynamic risk-based leverage per strategy. Requires Senpi MCP connection, python3, mcporter CLI, OpenClaw cron system, and dsl-dynamic-stop-loss skill (provides dsl-cli.py + dsl-v5.py).","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwolf-strategy\u002FSKILL.md",[149],{"categoryNo":150,"categoryName":151,"taxonomyType":97,"taxonomyTypeDesc":98},"01JBSEEDCAT000000000000023","Skill与智能体开发",[125,153,154,155,127,156,157,158,159,160,161,22,162,137,163,164,139,165,166,25],"wolf strategy","MCP","openclaw","health","system","python3","check","health check","stop","shared","connection","wallets","stop-loss","hyperliquid perps",{"skillNo":168,"name":169,"nameZh":6,"description":170,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":171,"categories":172,"keywords":174,"publishedAt":39},"01M6X949FBGWWGY3YZ8N3WB3CP","wolf-howl","HOWL v2 — Hunt, Optimize, Win, Learn. Nightly self-improvement loop for the WOLF autonomous trading strategy. Runs once per day (via cron) to review all trades from the last 24 hours, compute win rates, analyze signal quality correlation, evaluate DSL tier performance, identify missed opportunities, and produce concrete improvement suggestions for the wolf-strategy skill. v2 adds fee drag ratio (FDR) analysis, holding period bucketing, LONG vs SHORT regime detection, rotation cost tracking, cumulative drift detection, and gross vs net profit factor separation. Use when setting up daily trade review automation, analyzing trading performance, or improving an autonomous trading strategy through data-driven feedback loops. Requires Senpi MCP connection, mcporter CLI, and OpenClaw cron system.","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwolf-howl\u002FSKILL.md",[173],{"categoryNo":150,"categoryName":151,"taxonomyType":97,"taxonomyTypeDesc":98},[175,154,176,30,177,178,179,180,181,182,33,183,184,185,186,187,188,141,189,23],"wolf howl","review","learn","analysis","loop","analyze","short","autonomous","optimize","drift","self","factor","loops","profit","fdr",{"skillNo":191,"name":192,"nameZh":6,"description":193,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":194,"categories":195,"keywords":196,"publishedAt":39},"01M6X93YTRGNPYNHZRTW9XNH1E","vixen-strategy","VIXEN v1.0 — Dual-mode emerging movers scanner. Built from FOX v1.6 live trading data (+34.5% ROI). Two entry modes: STALKER (steady accumulation, score 6+, catches the SM buildup BEFORE the explosion) and STRIKER (violent FIRST_JUMP, score 9+, with raw volume confirmation to filter blow-off tops). 2-hour per-asset cooldown after Phase 1 exits. DSL High Water Mode mandatory.","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fvixen\u002FSKILL.md",[],[125,197,198,199,200,201,133,202,203,204,29,205,206,207,208,209,210,211,141,142],"vixen strategy","roi","data","first","confirmation","volume","filter","asset","explosion","mode","high","v1","modes","emerging movers","entry",{"skillNo":213,"name":214,"nameZh":6,"description":215,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":121,"licenseFileUrl":6,"sourceHtmlUrl":216,"categories":217,"keywords":218,"publishedAt":39},"01M6X93TE6KBJ6Z7C9XWRD0FRV","viper-strategy","VIPER v2.1 — Range-bound liquidity sniper. Enters at support\u002Fresistance when Bollinger Bands are tight, ATR is low, RSI is at extremes within the range, and volume is declining. Works when nothing is trending — the chop predator. USD-weighted OI filtering (min $5M). DSL High Water Mode (mandatory). 5-minute scan interval. Second-best performer in the Senpi zoo at +6.2% ROI.","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fviper\u002FSKILL.md",[],[125,219,220,221,198,222,223,47,224,225,202,226,227,206,207,139,228,141,229,23],"viper strategy","viper","support","filtering","rsi","scan","usd","liquidity","trending","sniper","second"]