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emerging-movers by senpi-ai/senpi-skills
npx skills add https://github.com/senpi-ai/senpi-skills --skill emerging-movers追踪所有 Hyperliquid 资产上的聪明钱市场集中度,并在资产成为拥挤的前三名交易标的之前,标记出排名加速上升的资产。当一项资产登上聪明钱排行榜榜首时,轻松赚钱的机会已经消失。本工具旨在捕捉这一上升轨迹。
每次扫描仅需一次 API 调用。LLM 代币消耗近乎为零。每 60 秒运行一次。
Senpi 的 leaderboard_get_markets 返回所有资产在过去 4 小时滚动窗口内,按聪明钱总利润百分比进行的排名。这不是交易者数量,而是资金实际流向的体现。
#1 ETH SHORT 31.4% 286 traders
#2 BTC SHORT 25.1% 436 traders
#3 HYPE SHORT 24.2% 330 traders
...
#36 ASTER SHORT 0.2% 18 traders ← 60秒后: #13, 0.82%, 65 traders
该脚本会随时间推移追踪此排行榜,并检测加速情况。
| 信号 | 条件 | 优先级 |
|---|---|---|
| IMMEDIATE_MOVER | 在一次扫描中,排名从 #25+ 跃升 10+ 位 | 最高 — 立即行动 |
| NEW_ENTRY_DEEP |
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| 从无到有,直接进入前 20 名 |
| 非常高 |
| CONTRIB_EXPLOSION | 在一次扫描中,贡献度增长 3 倍以上 | 非常高 |
| DEEP_CLIMBER | 排名从 #25+ 跃升 5+ 位 | 高 |
| 信号 | 条件 |
|---|---|
| NEW_ENTRY | 首次出现在前 50 名 |
| RANK_UP | 在一次扫描中排名上升 2+ 位 |
| CLIMBING | 在多次扫描中排名上升 3+ 位 |
| ACCEL | 贡献百分比逐次扫描增加 |
| STREAK | 每次检查都在持续攀升 |
| VELOCITY | 贡献度持续正增长 |
这些过滤器可以防止仅因排名跃升而看似良好,但在执行上失败的虚假 IMMEDIATE 信号:
| 过滤器 | 规则 | 原理 |
|---|---|---|
| 排名不稳定 | 历史记录中出现 >5 次排名反转 → erratic: true,降级 | 排名来回跳动是噪音 |
| 速度门槛 | contribVelocity < 0.03 → lowVelocity: true,从 IMMEDIATE 中排除 | 走势缺乏动力 |
| 交易者数量下限 | <10 名交易者 → 跳过 IMMEDIATE | 存在单一鲸鱼风险 |
| 最大杠杆检查 | 最大杠杆 < 10 倍 → 跳过 | 有限的仓位规模不值得操作 |
有关实现细节和真实示例,请参阅 references/quality-filters.md。
┌────────────────────────────────────┐
│ Cron: 每 60 秒执行一次 │
├────────────────────────────────────┤
│ scripts/emerging-movers.py │
│ • 从 JSON 加载扫描历史记录 │
│ • 获取排行榜(1 次 API 调用) │
│ • 解析前 50 个市场 │
│ • 与之前的扫描结果进行比较 │
│ • 检测信号 + v3.1 过滤器 │
│ • 保存更新后的历史记录 │
│ • 输出包含警报的 JSON │
├────────────────────────────────────┤
│ Agent 读取输出: │
│ • IMMEDIATE 警报 → 立即评估 │
│ • Deep climbers → 排队等待审查 │
│ • 无警报 → 静默 │
└────────────────────────────────────┘
| 文件 | 用途 |
|---|---|
scripts/emerging-movers.py | 扫描脚本 |
emerging-movers-history.json | 自动管理的扫描历史记录(最近 60 次扫描) |
max-leverage.json | 可选:资产最大杠杆参考 |
完整的 JSON 模式请参阅 references/output-schema.md。
关键顶级字段:alerts[], topMovers[], immediateMovers[], deepClimbers[], scanCount, timestamp。
每个警报的字段:asset, direction, rank, prevRank, contribution, traderCount, reasons[], contribVelocity, isImmediate, isDeepClimber, erratic, lowVelocity。
*/1 * * * * python3 scripts/emerging-movers.py
isImmediate: true + erratic: false + lowVelocity: false → 立即评估,通过 Scanner 寻找入场机会isDeepClimber: true → 排队等待下一次扫描器运行erratic: true 或 lowVelocity: true → 记录日志但不采取行动每周安装量
125
代码仓库
GitHub 星标数
53
首次出现
2026年2月27日
安全审计
安装于
openclaw122
opencode115
gemini-cli115
github-copilot115
codex115
kimi-cli115
Tracks Smart Money market concentration across all Hyperliquid assets and flags assets accelerating up the ranks before they become crowded top-3 plays. By the time an asset hits the top of the SM leaderboard, the easy money is gone. This catches the trajectory.
One API call per scan. Near-zero LLM tokens. Runs every 60 seconds.
Senpi's leaderboard_get_markets returns all assets ranked by percentage of total Smart Money profit in the last 4-hour rolling window. This isn't trader count — it's where the money is actually flowing.
#1 ETH SHORT 31.4% 286 traders
#2 BTC SHORT 25.1% 436 traders
#3 HYPE SHORT 24.2% 330 traders
...
#36 ASTER SHORT 0.2% 18 traders ← 60s later: #13, 0.82%, 65 traders
The script tracks this leaderboard over time and detects acceleration.
| Signal | Condition | Priority |
|---|---|---|
| IMMEDIATE_MOVER | 10+ rank jump from #25+ in ONE scan | Highest — act now |
| NEW_ENTRY_DEEP | Appears in top 20 from nowhere | Very high |
| CONTRIB_EXPLOSION | 3x+ contribution increase in one scan | Very high |
| DEEP_CLIMBER | 5+ rank jump from #25+ | High |
| Signal | Condition |
|---|---|
| NEW_ENTRY | First appearance in top 50 |
| RANK_UP | Jumped 2+ positions in one scan |
| CLIMBING | 3+ positions up over several scans |
| ACCEL | Contribution % increasing scan-over-scan |
| STREAK | Consistently climbing every check |
| VELOCITY | Sustained positive contribution growth |
These prevent false IMMEDIATE signals that looked great on rank jump alone but failed on execution:
| Filter | Rule | Rationale |
|---|---|---|
| Erratic rank | >5 rank reversals in history → erratic: true, downgraded | Bouncing ranks are noise |
| Velocity gate | contribVelocity < 0.03 → lowVelocity: true, excluded from IMMEDIATE | No momentum behind the move |
| Trader count floor | <10 traders → SKIP IMMEDIATE | Single whale risk |
| Max leverage check | max leverage < 10x → SKIP | Not worth the limited position sizing |
See references/quality-filters.md for implementation details and real-world examples.
┌────────────────────────────────────┐
│ Cron: every 60 seconds │
├────────────────────────────────────┤
│ scripts/emerging-movers.py │
│ • Loads scan history from JSON │
│ • Fetches leaderboard (1 API call) │
│ • Parses top 50 markets │
│ • Compares with previous scans │
│ • Detects signals + v3.1 filters │
│ • Saves updated history │
│ • Outputs JSON with alerts │
├────────────────────────────────────┤
│ Agent reads output: │
│ • IMMEDIATE alerts → evaluate now │
│ • Deep climbers → queue for review │
│ • No alerts → silent │
└────────────────────────────────────┘
| File | Purpose |
|---|---|
scripts/emerging-movers.py | Scanner script |
emerging-movers-history.json | Auto-managed scan history (last 60 scans) |
max-leverage.json | Optional: asset max leverage reference |
See references/output-schema.md for the complete JSON schema.
Key top-level fields: alerts[], topMovers[], immediateMovers[], deepClimbers[], scanCount, timestamp.
Per-alert fields: asset, direction, rank, prevRank, contribution, traderCount, reasons[], contribVelocity, isImmediate, isDeepClimber, erratic, lowVelocity.
*/1 * * * * python3 scripts/emerging-movers.py
isImmediate: true + erratic: false + lowVelocity: false → Evaluate immediately for entry via ScannerisDeepClimber: true → Queue for next scanner runerratic: true or lowVelocity: true → Log but do not actWeekly Installs
125
Repository
GitHub Stars
53
First Seen
Feb 27, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykWarn
Installed on
openclaw122
opencode115
gemini-cli115
github-copilot115
codex115
kimi-cli115
前端代码审计工具 - 自动化检测可访问性、性能、响应式设计、主题化与反模式
53,100 周安装