[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6X926F2GMKPTGSNYAC0AYNN":3,"skill-same:01M6X926F2GMKPTGSNYAC0AYNN":88},{"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":49,"commitSha":50,"skillDirectory":51,"forksCount":52,"repositoryHtmlUrl":53,"repositoryHomepageUrl":6,"ownerHtmlUrl":54,"ownerBlogUrl":55,"ownerDescription":56,"updatedAt":57,"install":58,"resources":71},"01M6X926F2GMKPTGSNYAC0AYNN","rhino-strategy",null,"RHINO — Momentum pyramider. Top 10 assets by OI + volume. Enters small (30% of max) on high-conviction convergence, then adds to winners at +10% ROE (40% more) and +20% ROE (final 30%). Thesis re-validated before every add — 4h trend intact, SM aligned, volume present. DSL High Water Mode trails the full position. The only skill in the zoo that builds into winners instead of entering full size and hoping.","enuno\u002Fcrewless-capital","enuno","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6727752?v=4","01M6J09HF6Y74150F7PEMC446X","Elvis Nuno","01M6X86WGZG9RH09ACTSTJ2383",1,"MIT","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Frhino\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"strategy","rhino strategy","dsl","assets","convergence","at","high","mode","top","size","more","re","trails","position","present","trend","thesis","volume","max","only","2026-11-10 10:12:30",false,"---\nname: rhino-strategy\ndescription: >-\n  RHINO — Momentum pyramider. Top 10 assets by OI + volume. Enters small (30% of max)\n  on high-conviction convergence, then adds to winners at +10% ROE (40% more) and\n  +20% ROE (final 30%). Thesis re-validated before every add — 4h trend intact, SM aligned,\n  volume present. DSL High Water Mode trails the full position. The only skill in the zoo\n  that builds into winners instead of entering full size and hoping.\nlicense: MIT\nmetadata:\n  author: jason-goldberg\n  version: \"1.0\"\n  platform: senpi\n  exchange: hyperliquid\n---\n\n# RHINO — Momentum Pyramider\n\nEnter small. Add to winners. Build into conviction.\n\nThe only skill in the Senpi zoo that adds to winning positions. Every other skill enters full size once and lets DSL manage the exit. RHINO enters at 30% of max position, then pyramids in as the trade proves correct — adding at +10% ROE and +20% ROE if the thesis still holds.\n\n## Why Pyramiding\n\nStandard approach: risk 100% of position size at entry, when the thesis is unproven.\n\nRHINO approach: risk 30% at entry, 70% only after the trade confirms.\n\nIf Stage 1 fails → you lose on 30% of max size (not 100%).\nIf it reaches Stage 3 → your full position is built across the move with a better average entry than all-in would give.\n\nThe math: on a $300 max position, RHINO risks $90 at entry. If it fails, you lose $90 × stop = ~$18. An all-in entry would lose $300 × stop = ~$60. Same signal, 3x less risk on the initial bet.\n\n## MANDATORY: DSL High Water Mode\n\n**RHINO MUST use DSL High Water Mode. This is not optional.**\n\nSpec: https:\u002F\u002Fgithub.com\u002FSenpi-ai\u002Fsenpi-skills\u002Fblob\u002Fmain\u002Fdsl-dynamic-stop-loss\u002Fdsl-high-water-spec%201.0.md\n\nWhen creating DSL state files, you MUST include:\n\n```json\n{\n  \"lockMode\": \"pct_of_high_water\",\n  \"phase2TriggerRoe\": 8,\n  \"tiers\": [\n    {\"triggerPct\": 8,  \"lockHwPct\": 25, \"consecutiveBreachesRequired\": 3},\n    {\"triggerPct\": 15, \"lockHwPct\": 45, \"consecutiveBreachesRequired\": 2},\n    {\"triggerPct\": 25, \"lockHwPct\": 60, \"consecutiveBreachesRequired\": 2},\n    {\"triggerPct\": 40, \"lockHwPct\": 75, \"consecutiveBreachesRequired\": 1},\n    {\"triggerPct\": 60, \"lockHwPct\": 85, \"consecutiveBreachesRequired\": 1}\n  ]\n}\n```\n\n**FALLBACK:** Use `tiersLegacyFallback` from config until engine supports `pct_of_high_water`.\n\n**DSL applies to the full position, not per-add.** Each pyramid add increases position size but the DSL state tracks one high-water mark for the entire position. After adding, the DSL floor recalculates based on the new total margin.\n\n## The Three Stages\n\n### Stage 1 — SCOUT (30% of max position)\n\n**When:** Score 10+ convergence on a top-10 asset.\n\n| Signal | Requirement |\n|---|---|\n| 4h trend structure | BULLISH or BEARISH (not neutral) |\n| 1h trend | Must agree with 4h |\n| 1h momentum | ≥ 0.3% in direction |\n| SM alignment | Hard block if opposing |\n| Min score | 10 |\n\n**Size:** 30% of max margin. At $1,000 account with 30% max margin = $300 max position, scout enters with $90.\n\n**Purpose:** Skin in the game. Prove the thesis with minimal risk.\n\n### Stage 2 — CONFIRM (add 40% at +10% ROE)\n\n**When:** Position is at +10% ROE AND thesis re-validated:\n- 4h trend still intact (same direction)\n- SM still aligned (not flipped)\n- Volume still present (ratio ≥ 0.5x average)\n\n**Size:** 40% of max margin. Adds $120 to the $90 scout. Position is now $210 (70% of max).\n\n**Purpose:** The trade is working. Double down while the signal is confirmed.\n\n### Stage 3 — CONVICTION (add final 30% at +20% ROE)\n\n**When:** Position is at +20% ROE AND thesis re-validated (same checks as Stage 2).\n\n**Size:** Final 30% of max margin. Adds $90. Position is now $300 (100% of max).\n\n**Purpose:** The trade is running. Full conviction deployed. DSL High Water trails the full $300 from here.\n\n### What If a Stage Doesn't Trigger?\n\nStage 2 and 3 are optional. If the trade reaches +10% ROE but the 4h trend has broken, the add doesn't happen — the scout position rides with DSL protection. If it never reaches +10%, the scout either hits its stop or trails out on DSL. No forced adds.\n\n## Scan Priority\n\nEvery 3-minute scan, RHINO checks in this order:\n\n1. **Add to existing winners** — do any positions qualify for Stage 2 or 3? If yes, add and return.\n2. **Entry cap check** — any slots available?\n3. **Scout new positions** — scan top 10 for new Stage 1 entries.\n\nAdds take priority over new entries. A winning position that needs Stage 2 is more valuable than a new scout.\n\n## Risk Management\n\n| Rule | Value | Notes |\n|---|---|---|\n| Max positions | 3 | Each pyramids independently |\n| Floor base | 2.5% notional | Wider — scout entries need room |\n| Phase 2 trigger | +8% ROE | Before Stage 2 add happens |\n| Stagnation TP | 15% ROE, 90 min | Patient — pyramided positions need time |\n| Max single loss | 8% of account | At Stage 1, actual risk is 30% of this |\n| Max consecutive losses | 2 → 90 min cooldown | |\n| Drawdown halt | 20% | |\n\n## Cron Architecture\n\n| Cron | Interval | Session | Purpose |\n|---|---|---|---|\n| Scanner | 3 min | isolated | Pyramid evaluation + new scouts |\n| DSL v5 | 3 min | isolated | High Water Mode trailing |\n\n## Notification Policy\n\n**ONLY alert:**\n- Stage 1 SCOUT opened (asset, direction, margin, score)\n- Stage 2 CONFIRM added (asset, +ROE at add, new total margin)\n- Stage 3 CONVICTION added (asset, +ROE at add, full position)\n- Position CLOSED (DSL or structural, total P&L across all stages)\n- Risk triggered, critical error\n\n**NEVER alert:** Scanner found nothing, DSL routine, pyramid evaluation found no adds, any reasoning.\nAll crons isolated. `NO_REPLY` for idle cycles.\n\n## Bootstrap Gate\n\nCheck `config\u002Fbootstrap-complete.json` every session. If missing:\n1. Verify Senpi MCP\n2. Create scanner cron (3 min, isolated) and DSL cron (3 min, isolated)\n3. Write `config\u002Fbootstrap-complete.json`\n4. Send: \"? RHINO is online. Scouting top 10 by OI + volume. Enter small, add to winners. Silence = no conviction.\"\n\n## Expected Behavior\n\n| Metric | Expected |\n|---|---|\n| Scouts\u002Fday | 2-4 (score 10+ on top 10 assets) |\n| Adds\u002Fday | 1-2 (only scouts that reach +10% ROE with intact thesis) |\n| Full pyramids (Stage 3)\u002Fday | 0-1 (rare — the trade must run to +20% with thesis intact) |\n| Win rate on scouts | ~50-55% |\n| Win rate on full pyramids | ~70-80% (pre-selected by being up +20% with confirmed thesis) |\n| Avg winner (scout only) | 10-20% ROE on 30% position |\n| Avg winner (full pyramid) | 30-80%+ ROE on 100% position |\n| Avg loser | -15 to -20% ROE on 30% position (scout stops) |\n| Profit factor | Target 1.5-2.5 |\n\nThe edge: losers are small (30% position × stop). Winners are big (100% position × High Water trail). Asymmetric by design.\n\n## Files\n\n| File | Purpose |\n|---|---|\n| `scripts\u002Frhino-scanner.py` | Thesis builder + pyramid evaluator + scout finder |\n| `scripts\u002Frhino_config.py` | Shared config, MCP helpers |\n| `config\u002Frhino-config.json` | All variables with pyramid stages + DSL High Water |\n\n## License\n\nMIT — Built by Senpi (https:\u002F\u002Fsenpi.ai).\nSource: https:\u002F\u002Fgithub.com\u002FSenpi-ai\u002Fsenpi-skills\n","# RHINO — Momentum Pyramider\n\nEnter small. Add to winners. Build into conviction.\n\nThe only skill in the Senpi zoo that adds to winning positions. Every other skill enters full size once and lets DSL manage the exit. RHINO enters at 30% of max position, then pyramids in as the trade proves correct — adding at +10% ROE and +20% ROE if the thesis still holds.\n\n## Why Pyramiding\n\nStandard approach: risk 100% of position size at entry, when the thesis is unproven.\n\nRHINO approach: risk 30% at entry, 70% only after the trade confirms.\n\nIf Stage 1 fails → you lose on 30% of max size (not 100%).\nIf it reaches Stage 3 → your full position is built across the move with a better average entry than all-in would give.\n\nThe math: on a $300 max position, RHINO risks $90 at entry. If it fails, you lose $90 × stop = ~$18. An all-in entry would lose $300 × stop = ~$60. Same signal, 3x less risk on the initial bet.\n\n## MANDATORY: DSL High Water Mode\n\n**RHINO MUST use DSL High Water Mode. This is not optional.**\n\nSpec: https:\u002F\u002Fgithub.com\u002FSenpi-ai\u002Fsenpi-skills\u002Fblob\u002Fmain\u002Fdsl-dynamic-stop-loss\u002Fdsl-high-water-spec%201.0.md\n\nWhen creating DSL state files, you MUST include:\n\n```json\n{\n  \"lockMode\": \"pct_of_high_water\",\n  \"phase2TriggerRoe\": 8,\n  \"tiers\": [\n    {\"triggerPct\": 8,  \"lockHwPct\": 25, \"consecutiveBreachesRequired\": 3},\n    {\"triggerPct\": 15, \"lockHwPct\": 45, \"consecutiveBreachesRequired\": 2},\n    {\"triggerPct\": 25, \"lockHwPct\": 60, \"consecutiveBreachesRequired\": 2},\n    {\"triggerPct\": 40, \"lockHwPct\": 75, \"consecutiveBreachesRequired\": 1},\n    {\"triggerPct\": 60, \"lockHwPct\": 85, \"consecutiveBreachesRequired\": 1}\n  ]\n}\n```\n\n**FALLBACK:** Use `tiersLegacyFallback` from config until engine supports `pct_of_high_water`.\n\n**DSL applies to the full position, not per-add.** Each pyramid add increases position size but the DSL state tracks one high-water mark for the entire position. After adding, the DSL floor recalculates based on the new total margin.\n\n## The Three Stages\n\n### Stage 1 — SCOUT (30% of max position)\n\n**When:** Score 10+ convergence on a top-10 asset.\n\n| Signal | Requirement |\n|---|---|\n| 4h trend structure | BULLISH or BEARISH (not neutral) |\n| 1h trend | Must agree with 4h |\n| 1h momentum | ≥ 0.3% in direction |\n| SM alignment | Hard block if opposing |\n| Min score | 10 |\n\n**Size:** 30% of max margin. At $1,000 account with 30% max margin = $300 max position, scout enters with $90.\n\n**Purpose:** Skin in the game. Prove the thesis with minimal risk.\n\n### Stage 2 — CONFIRM (add 40% at +10% ROE)\n\n**When:** Position is at +10% ROE AND thesis re-validated:\n- 4h trend still intact (same direction)\n- SM still aligned (not flipped)\n- Volume still present (ratio ≥ 0.5x average)\n\n**Size:** 40% of max margin. Adds $120 to the $90 scout. Position is now $210 (70% of max).\n\n**Purpose:** The trade is working. Double down while the signal is confirmed.\n\n### Stage 3 — CONVICTION (add final 30% at +20% ROE)\n\n**When:** Position is at +20% ROE AND thesis re-validated (same checks as Stage 2).\n\n**Size:** Final 30% of max margin. Adds $90. Position is now $300 (100% of max).\n\n**Purpose:** The trade is running. Full conviction deployed. DSL High Water trails the full $300 from here.\n\n### What If a Stage Doesn't Trigger?\n\nStage 2 and 3 are optional. If the trade reaches +10% ROE but the 4h trend has broken, the add doesn't happen — the scout position rides with DSL protection. If it never reaches +10%, the scout either hits its stop or trails out on DSL. No forced adds.\n\n## Scan Priority\n\nEvery 3-minute scan, RHINO checks in this order:\n\n1. **Add to existing winners** — do any positions qualify for Stage 2 or 3? If yes, add and return.\n2. **Entry cap check** — any slots available?\n3. **Scout new positions** — scan top 10 for new Stage 1 entries.\n\nAdds take priority over new entries. A winning position that needs Stage 2 is more valuable than a new scout.\n\n## Risk Management\n\n| Rule | Value | Notes |\n|---|---|---|\n| Max positions | 3 | Each pyramids independently |\n| Floor base | 2.5% notional | Wider — scout entries need room |\n| Phase 2 trigger | +8% ROE | Before Stage 2 add happens |\n| Stagnation TP | 15% ROE, 90 min | Patient — pyramided positions need time |\n| Max single loss | 8% of account | At Stage 1, actual risk is 30% of this |\n| Max consecutive losses | 2 → 90 min cooldown | |\n| Drawdown halt | 20% | |\n\n## Cron Architecture\n\n| Cron | Interval | Session | Purpose |\n|---|---|---|---|\n| Scanner | 3 min | isolated | Pyramid evaluation + new scouts |\n| DSL v5 | 3 min | isolated | High Water Mode trailing |\n\n## Notification Policy\n\n**ONLY alert:**\n- Stage 1 SCOUT opened (asset, direction, margin, score)\n- Stage 2 CONFIRM added (asset, +ROE at add, new total margin)\n- Stage 3 CONVICTION added (asset, +ROE at add, full position)\n- Position CLOSED (DSL or structural, total P&L across all stages)\n- Risk triggered, critical error\n\n**NEVER alert:** Scanner found nothing, DSL routine, pyramid evaluation found no adds, any reasoning.\nAll crons isolated. `NO_REPLY` for idle cycles.\n\n## Bootstrap Gate\n\nCheck `config\u002Fbootstrap-complete.json` every session. If missing:\n1. Verify Senpi MCP\n2. Create scanner cron (3 min, isolated) and DSL cron (3 min, isolated)\n3. Write `config\u002Fbootstrap-complete.json`\n4. Send: \"? RHINO is online. Scouting top 10 by OI + volume. Enter small, add to winners. Silence = no conviction.\"\n\n## Expected Behavior\n\n| Metric | Expected |\n|---|---|\n| Scouts\u002Fday | 2-4 (score 10+ on top 10 assets) |\n| Adds\u002Fday | 1-2 (only scouts that reach +10% ROE with intact thesis) |\n| Full pyramids (Stage 3)\u002Fday | 0-1 (rare — the trade must run to +20% with thesis intact) |\n| Win rate on scouts | ~50-55% |\n| Win rate on full pyramids | ~70-80% (pre-selected by being up +20% with confirmed thesis) |\n| Avg winner (scout only) | 10-20% ROE on 30% position |\n| Avg winner (full pyramid) | 30-80%+ ROE on 100% position |\n| Avg loser | -15 to -20% ROE on 30% position (scout stops) |\n| Profit factor | Target 1.5-2.5 |\n\nThe edge: losers are small (30% position × stop). Winners are big (100% position × High Water trail). Asymmetric by design.\n\n## Files\n\n| File | Purpose |\n|---|---|\n| `scripts\u002Frhino-scanner.py` | Thesis builder + pyramid evaluator + scout finder |\n| `scripts\u002Frhino_config.py` | Shared config, MCP helpers |\n| `config\u002Frhino-config.json` | All variables with pyramid stages + DSL High Water |\n\n## License\n\nMIT — Built by Senpi (https:\u002F\u002Fsenpi.ai).\nSource: https:\u002F\u002Fgithub.com\u002FSenpi-ai\u002Fsenpi-skills\n",{"name":5,"license":15,"metadata":44,"description":7},{"author":45,"version":46,"exchange":47,"platform":48},"jason-goldberg","1.0","hyperliquid","senpi","main","bfe4e4653cba696a8dc20f70c6006651b997fdef","migrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Frhino",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":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add enuno\u002Fcrewless-capital --skill rhino-strategy",{"tool":64,"command":65},"bunx","bunx skills add enuno\u002Fcrewless-capital --skill rhino-strategy",{"tool":67,"command":68},"pnpm","pnpm dlx skills add enuno\u002Fcrewless-capital --skill rhino-strategy","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Frhino\u002FSKILL.md",true,[72,78,84],{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"config\u002Frhino-config.json","REFERENCE","参考文档",2902,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Frhino\u002Fconfig\u002Frhino-config.json",{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"scripts\u002Frhino_config.py","SCRIPT","脚本",6626,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Frhino\u002Fscripts\u002Frhino_config.py",{"path":85,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":86,"sourceHtmlUrl":87},"scripts\u002Frhino-scanner.py",15813,"https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Frhino\u002Fscripts\u002Frhino-scanner.py",[89,121,141,166,191,212],{"skillNo":90,"name":91,"nameZh":6,"description":92,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":93,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":101,"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.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsupermemory\u002FSKILL.md",[96],{"categoryNo":97,"categoryName":98,"taxonomyType":99,"taxonomyTypeDesc":100},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[91,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120],"ai agents","memory","rag","semantic search","infrastructure","search","applications","api","knowledge","context","Art","personalization","across","learned","retention","for","persistent memory","static","when",{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":125,"categories":126,"keywords":127,"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.","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwolverine\u002FSKILL.md",[],[19,128,129,130,131,132,38,133,134,135,37,47,136,137,138,24,117,139,21,140],"wolverine strategy","architecture","alpha","Volatility","consensus","trading","scanner","manage","runtime","leverage","hunter","managed","phase",{"skillNo":142,"name":143,"nameZh":6,"description":144,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":145,"categories":146,"keywords":150,"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",[147],{"categoryNo":148,"categoryName":149,"taxonomyType":99,"taxonomyTypeDesc":100},"01JBSEEDCAT000000000000023","Skill与智能体开发",[19,151,152,153,129,154,155,156,157,158,159,160,161,137,162,163,24,164,165,117],"wolf strategy","MCP","openclaw","health","system","python3","check","health check","stop","strategies","shared","connection","wallets","stop-loss","hyperliquid perps",{"skillNo":167,"name":168,"nameZh":6,"description":169,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":170,"categories":171,"keywords":173,"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",[172],{"categoryNo":148,"categoryName":149,"taxonomyType":99,"taxonomyTypeDesc":100},[174,152,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,21,190,120],"wolf howl","review","performance","learn","analysis","loop","analyze","short","autonomous","up","optimize","drift","self","factor","loops","profit","fdr",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":93,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":197,"publishedAt":39},"01M6X9437CQ55N5AYHCPF71JWG","whale-index","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.","https:\u002F\u002Fgithub.com\u002Fenuno\u002Fcrewless-capital\u002Fblob\u002Fmain\u002Fmigrate-hyperliquid-firm\u002Fskills\u002Fsenpi-skills\u002Fwhale-index\u002FSKILL.md",[],[198,199,200,176,201,202,203,204,205,183,206,207,160,208,209,27,210,117,211,120],"index","whale","whale index","auth","monitoring","discovery","use","auto","daily","time","with","consistency","mirror","pnl",{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":216,"categories":217,"keywords":218,"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",[],[19,219,220,221,222,223,134,36,224,225,208,226,26,25,227,228,229,230,21,140],"vixen strategy","roi","data","first","confirmation","filter","asset","explosion","v1","modes","emerging movers","entry"]