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Agent Skill · 待分类

vulture-strategy(秃鹫策略)

vulture-strategy 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

vulture-strategy 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 8,258。

总安装 312周安装 13GitHub Stars 75下载 104核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:vulture-strategy(秃鹫策略)
来源仓库:https://github.com/senpi-ai/senpi-skills
仓库路径:skills/vulture-strategy
安装命令:
npx skills add https://github.com/senpi-ai/senpi-skills --skill vulture-strategy
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/senpi-ai/senpi-skills --skill vulture-strategy

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于分析 GitHub 仓库协作状态与代码演进趋势。适合监控 Issue 处理进度、PR 合并频率与贡献者活跃度。通过 GitHub 安装,支持自动化报告生成。需配置适当 API 权限,防止触发速率限制或访问拒绝。vulture-strategy 属于待分类类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/vulture-strategy

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/senpi-ai/senpi-skills --skill vulture-strategy;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

vulture-strategy 怎么安装?

在终端执行 npx skills add https://github.com/senpi-ai/senpi-skills --skill vulture-strategy。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

vulture-strategy 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

vulture-strategy 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

vulture-strategy 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

vulture-strategy 用的人多吗?

公开数据是累计安装 312 次,近一周安装 13 次,下载 104 次,GitHub 75 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

vulture-strategy 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
vulture-strategy

秃鹫策略 · 本页

31275调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

🦅 VULTURE v2.4.0 — Long-Tail Momentum Rider

COMPLETE REWRITE from v1.0. v1.0 was a contrarian SM-exhaustion fader on 4 majors (BTC/ETH/SOL/HYPE) gated at MIN_4H_MOVE_PCT=3.0 — the combination was mathematically unreachable and produced 0 trades in 14+ days.

v2.0 was designed from the #1 Arena winner's playbook (3-week reigning Arena champion, 102 trades, 38.6% win rate, 6.15x profit factor, ~80% of profit from 6 trades out of 102, hold times 24h to 8 days). v2.4.0 keeps that thesis intact and adds two fleet patches.


⛔ Hard Rules (Fleet Patches)

RULE FP-002: User-conversation Claude sessions MUST NOT trade

Hard rule, not a heuristic. When responding to a user message (Telegram ping, status check, "tell me about your trades", etc.), the Claude Code session MUST NOT call any of:

  • create_position
  • close_position
  • edit_position
  • ratchet_stop_add / ratchet_stop_edit / ratchet_stop_delete
  • cancel_order
  • strategy_close / strategy_close_positions

These tools are reserved for the producer cron (vulture-scanner.py) and the DSL ratchet engine. The cron is the only entry path. The DSL is the only exit path. User-conversation sessions are read-only.

If a user asks "should I take this trade?" or "anything close to triggering?", respond by reading current state — DO NOT execute. The producer will fire on its next tick if a real signal is there.

RULE FP-001: Quiet hours for low-liquidity windows

Producer skips emission during 00:00-04:00 UTC by default. Apex setups (best signal score >= quietHours.apexBypassScore, default 12) bypass — high-conviction small-cap momentum can fire any hour; routine sub-apex entries wait until 04:00 UTC.

Configurable via quietHours.startUtc, quietHours.endUtc, quietHours.apexBypassScore in vulture-config.json. Set startUtc == endUtc to disable.

Rationale: fleet-wide pattern of midnight-UTC pile-ins after daily-cap reset. For Vulture specifically, small-cap order books are thinnest in this window and entry slippage compounds.



Thesis

Small-cap Hyperliquid perps have thicker trader-count signal-to-noise ratios than the majors. When Smart Money concentration on a small cap ALIGNS with a fresh 4h price trend AND 15m velocity is accelerating, enter in the direction of the trend and hold it via the DSL tier curve for days, not hours.

Key insight: The Arena winner's asset universe (HEMI, WLD, MON, XPL, AIXBT, ARB) is a fleet-wide blind spot. No current Senpi predator scans small-cap alts — they're all locked to 4-12 majors or single assets. Vulture v2.0 fills the gap.


Philosophy (copied from Arena winner #1)

  • Low win rate is fine (~38%) if winners are 5-10x bigger than losers
  • Tight loss cuts via DSL dead_weight_cut (60 min)
  • Long holds on winners via hard_timeout=10080 min (7 days)
  • Moderate leverage (5-7x) — small caps can't handle 20x (slippage kills you on low-liquidity books)
  • Signal-driven direction, NOT long-only bias. The Arena winner was long because April 2026 was a bullish regime, not because LONG is a rule. Vulture v2.0 takes SHORTs when signals support.
  • Max 2 concurrent positions

Asset Universe (25 small/mid-caps)

HYPE, HEMI, WLD, MON, XPL, AIXBT, ARB, ASTER, POLYX, LDO,
APT, DYDX, ONDO, SUI, kBONK, kPEPE, TAO, GRASS, ZEC, LIT,
FARTCOIN, MORPHO, NEAR, INJ, AVAX, LINK, DOGE

Banned: BTC, ETH, SOL (handled by other predators). XYZ DEX assets (handled by Bald Eagle).


Entry Scoring

Hard gates (all must pass)

  • Asset must be in TRACKED_ASSETS and not in BANNED_ASSETS
  • SM direction must be LONG or SHORT (not neutral)
  • pct >= 3.0 AND traders >= 15 (signal validity)
  • 4h price ALIGNED with SM direction by at least 1% (momentum confirmation)
  • 15m velocity > 0.3 (actively building, not flat)

Scoring contributors (max ~14 pts)

SignalPoints
SM concentration ≥18% (HEAVY_FLOW)+4
SM concentration ≥12% (STRONG_FLOW)+3
SM concentration ≥7% (MODERATE_FLOW)+2
SM concentration ≥3% (LIGHT_FLOW)+1
4h price aligned ≥8% (TREND_RUNNING)+3
4h price aligned ≥4% (TREND_STRONG)+2
4h price aligned ≥2% (TREND_BUILDING)+1
15m velocity ≥3.0 (15M_EXPLOSIVE)+3
15m velocity ≥1.0 (15M_STRONG)+2
15m velocity ≥0.5 (15M_BUILDING)+1
ACCELERATING pattern (15m > 1h > 0)+2
1h velocity ≥1.0 (1H_POSITIVE)+1
4h contribution ≥2.0 (4H_CONTINUATION)+1
Trader count ≥50 (DEEP_DEPTH)+1
Move ≥15% in direction (LATE_ENTRY_PENALTY)-3
Move ≥12% in direction (MOVE_EXTENDED)-2

MIN_SCORE: 7 — entry floor. The scoring dimensions (especially HEAVY_FLOW requiring ≥18% SM concentration) do the real quality work.


Conviction-Scaled Leverage

ScoreLeverage
≥117x
≥95x
≥73x

Capped at 7x because small-cap liquidity can't support 20x. Lemon can go 20x on BTC/ETH because slippage is <0.1%. Small caps can have 0.5%+ slippage per fill, which eats gains at 20x.


Exit (DSL)

The DSL tier curve is the single biggest difference from other Senpi predators. Winners need DAYS to develop. Arena winner #1 held HEMI for 8 days, WLD for 4 days, MON for 5 days.

MechanismValueRationale
hard_timeout10080 min (7 days)Let momentum runners run a full week
dead_weight_cut60 minFaster than Owl's 90, slower than Lemon's 20 (small-cap wick tolerance)
weak_peak_cut120 min @ 2% minCatch fades that stalled
Phase 1 max_loss_pct20%Wider than Lemon's 15%, tighter than Owl's 35%
Phase 1 retrace8%Standard
Phase 1 breaches3Standard
Phase 2 tier 15% trigger → 20% lockCapture first leg (Lemon-pattern learning)
Phase 2 tier 210% → 35% lock
Phase 2 tier 320% → 55% lock
Phase 2 tier 435% → 70% lock
Phase 2 tier 550% → 80% lock
Phase 2 tier 675% → 88% lock
Phase 2 tier 7100% → 92% lockInfinite trail on massive winners

Risk Management

RuleValue
Max positions2 concurrent
Max entries/day4 (dynamic, scales with P&L)
Per-asset cooldown240 min (4h sniper cadence)
Margin per position40% of account
Leverage range3-7x
Asset blocklistBTC, ETH, SOL, all XYZ
Daily loss capHARD STOP at -25% drawdown

Differences from Lemon

Both agents are "fleet alpha extractors" but via opposite philosophies:

DimensionLemon v1.1 (Degen Fader)Vulture v2.0 (Long-Tail Rider)
Asset universe12 majors25 small caps
Direction vs SMFades (counter-trade)Follows (momentum)
Entry conditionSM high + 15m collapsingSM high + 15m accelerating
Avg hold time235 min24h to 7 days
hard_timeout480 min10,080 min (21x longer)
dead_weight_cut20 min60 min
Max leverage20x (apex)7x (liquidity limit)
MIN_SCORE87

Both are bets on asymmetric payoff — low win rate + big winners / tiny losers — but Lemon bets on mean reversion of exhausted crowds while Vulture bets on continuation of small-cap trends.


Runtime Setup

Step 1: Install package files:

mkdir -p /data/workspace/skills/vulture-strategy/{config,scripts,state}

curl -s https://raw.githubusercontent.com/Senpi-ai/senpi-skills/main/vulture/runtime.yaml -o /data/workspace/skills/vulture-strategy/runtime.yaml
curl -s https://raw.githubusercontent.com/Senpi-ai/senpi-skills/main/vulture/SKILL.md -o /data/workspace/skills/vulture-strategy/SKILL.md
curl -s https://raw.githubusercontent.com/Senpi-ai/senpi-skills/main/vulture/config/vulture-config.json -o /data/workspace/skills/vulture-strategy/config/vulture-config.json
curl -s https://raw.githubusercontent.com/Senpi-ai/senpi-skills/main/vulture/scripts/vulture-scanner.py -o /data/workspace/skills/vulture-strategy/scripts/vulture-scanner.py
curl -s https://raw.githubusercontent.com/Senpi-ai/senpi-skills/main/vulture/scripts/vulture_config.py -o /data/workspace/skills/vulture-strategy/scripts/vulture_config.py

Step 2: Set strategy wallet and telegram chat:

sed -i 's/${WALLET_ADDRESS}/<STRATEGY_WALLET_ADDRESS>/' /data/workspace/skills/vulture-strategy/runtime.yaml
sed -i 's/${TELEGRAM_CHAT_ID}/<CHAT_ID>/' /data/workspace/skills/vulture-strategy/runtime.yaml

Step 3: Install runtime:

openclaw senpi runtime create --path /data/workspace/skills/vulture-strategy/runtime.yaml
openclaw senpi runtime list

Step 4: Create scanner cron (3-minute interval):

# In openclaw: create a cron scanning every 3 minutes
# Command: python3 /data/workspace/skills/vulture-strategy/scripts/vulture-scanner.py

Bootstrap Gate

On EVERY session start, verify:

  1. senpi-trading-runtime SKILL is loaded
  2. Senpi MCP is connected
  3. Runtime is installed (openclaw senpi runtime list)
  4. Scanner cron is active (3 min interval)

Send: "🦅 VULTURE v2.0 online. Long-Tail Momentum Rider. Riding small-cap trends. Silence = no momentum confluence."


Changelog

v2.0 (2026-04-15) — COMPLETE REWRITE

  • Thesis flipped: contrarian fader → momentum rider
  • Universe expanded: 4 majors → 25 small caps
  • DSL hard_timeout: 360 min → 10,080 min (7 days)
  • Leverage: 5-7x (unchanged, appropriate for small caps)
  • MIN_4H_MOVE_PCT gate removed (was unreachable)
  • New MIN_15M_VELOCITY=0.3 hard gate (actively-building confirmation)
  • Max positions: 1 → 2
  • Signal-driven direction (not bias)
  • Based on Arena winner #1 3-week playbook

v1.0 (pre-2026-04-15)

  • Initial release. Contrarian SM-exhaustion fader on 4 majors. 0 trades produced.

License

MIT — Built by Senpi (https://senpi.ai). Source: https://github.com/Senpi-ai/senpi-skills


Skill Attribution

When creating a strategy, include skill_name and skill_version in the call. See references/skill-attribution.md for details.

平台分布

Codex

35.03%
按下载量换算36

Claude

31.07%
按下载量换算32

Cursor

17.6%
按下载量换算18

Gemini CLI

8.93%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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