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Agent Skill · AI 工具

market-regimes(市场制度)

market-regimes 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。

market-regimes 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 203。

总安装 11,710周安装 503GitHub Stars 4下载 4,104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
MIT

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:market-regimes(市场制度)
来源仓库:https://github.com/0xhubed/agent-trading-arena
仓库路径:skills/market-regimes
安装命令:
npx skills add https://github.com/0xhubed/agent-trading-arena --skill market-regimes
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/0xhubed/agent-trading-arena --skill market-regimes

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

检测市场状况并根据历史表现模式应用数据驱动的交易策略。

识别 32 个活跃市场状态(趋势上涨、温和牛市、混合震荡、看跌、横盘持平、低波动性),信心得分高达 93% 建议针对具体制度的策略:波动/看跌市场中的零交易资本保全,每天活跃 120-200 笔交易,并在已确认的上升趋势中进行风险验证,根据动量确定资产选择优先级 强调关键模式:交易频率与横盘市场表现成反比;技术信号(MACD、RSI、多时间框架调整)在混合状态下产生虚假信号;资产选择(ETH 与 BTC、BNB 与 SOL)显着影响回报 提供置信度阈值 (60%+) 和历史观察计数,以帮助根据其他交易信号权衡建议

来源仓库内路径:skills/market-regimes

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/0xhubed/agent-trading-arena --skill market-reg…;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

    它需要需要联网,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

market-regimes 怎么安装?

在终端执行 npx skills add https://github.com/0xhubed/agent-trading-arena --skill market-regimes。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

market-regimes 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。

market-regimes 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

market-regimes 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

market-regimes 用的人多吗?

公开数据是累计安装 11,710 次,近一周安装 503 次,下载 4,104 次,GitHub 4 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。

market-regimes 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
market-regimes

市场制度 · 本页

11,7104需要联网MIT通过

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

Market Regimes

Last updated: 2026-03-09 20:08 UTC Active patterns: 38 Total samples: 0 Confidence threshold: 60%

How to Use This Skill

  1. Identify the current market regime using price action and volatility
  2. Look up the recommended strategy for that regime below
  3. Adjust your trading approach accordingly
  4. Monitor for regime changes

Regime Strategies

Uniform Bearish

Recommended approach (95% confidence, seen 1x):

HIGH-frequency SHORT-biased strategy (150-200 trades/24h) with multi-timeframe bearish confirmation. skill_aware_oss achieved +$2911.52 with 200 trades. Focus on highest-volatility losers: SOLUSDT (-11.31%), ETHUSDT (-9.62%).
  • Total observations: 0
  • First identified: 2026-02-01

Uniform Bearish

Recommended approach (92% confidence, seen 1x):

Avoid LONG positions entirely regardless of oversold signals. RSI ~28 oversold readings are continuation signals in strong downtrends, not reversal signals. skill_aware_oss correctly used oversold RSI as SHORT confirmation.
  • Total observations: 0
  • First identified: 2026-02-01

Uniform Bullish

Recommended approach (92% confidence, seen 1x):

ZERO trading or passive LONG-only allocation. When ALL assets gain (+1.33% to +3.82%), any SHORT-biased strategy loses. index_fund's $0 PnL beats all active agents. If must trade, use <20 trades/24h with LONG bias only.
  • Total observations: 0
  • First identified: 2026-02-02

Uniform Bearish

Recommended approach (90% confidence, seen 1x):

Trade frequency sweet spot is 149-200 trades/24h. Below 20 trades (ta_baseline: -$99, gpt_simple: -$163) fails to capture momentum. Zero trades (index_fund) misses directional opportunity entirely.
  • Total observations: 0
  • First identified: 2026-02-01

Uniform Bullish

Recommended approach (90% confidence, seen 1x):

CRITICAL: Multi-timeframe bearish alignment on lower timeframes (15m, 1h, 4h) does NOT override daily/weekly bullish regime. Agents must incorporate higher timeframe trend before acting on short-term signals.
  • Total observations: 0
  • First identified: 2026-02-02

Uniform Bearish

Recommended approach (88% confidence, seen 1x):

Position sizing at 2% equity risk with 2:1 reward ratio SUCCEEDS when combined with trend-aligned entries. skill_aware_oss consistently cited this framework in high-confidence decisions.
  • Total observations: 0
  • First identified: 2026-02-01

Uniform Bullish

Recommended approach (88% confidence, seen 1x):

Technical analysis baseline with LOW frequency (38 trades/24h) minimizes losses when agent bias conflicts with market direction. ta_baseline lost only -$120 vs -$963 for high-frequency SHORT agents.
  • Total observations: 0
  • First identified: 2026-02-02

Uniform Bearish

Recommended approach (87% confidence, seen 1x):

SHORT-biased strategy with 150-183 trades/24h is optimal IF position management focuses on 'locking in profits' rather than 'cutting losses to free margin'. skill_aware_oss: +$1682.05 with 183 trades. Focus shorts on highest-volatility losers: ETHUSDT (-16.34%), DOGEUSDT (-15.79%), SOLUSDT (-14.28%).
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish

Recommended approach (85% confidence, seen 1x):

Avoid LONG positions entirely. agentic_gptoss opened BTC long with 0.93 confidence during -7.95% BTC decline, contributing to -$246.40 loss. Market indicators showing 'bullish bias' are false signals in uniform bearish conditions.
  • Total observations: 0
  • First identified: 2026-01-31

Mixed Mostly Bullish

Recommended approach (83% confidence, seen 1x):

SHORT-biased strategy ONLY works when agent has strong conviction and holds through noise. skill_aware_oss succeeded (+$409) while agentic_gptoss failed (-$619) with similar trade counts. Key differentiator: skill_aware_oss maintained position discipline.
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish

Recommended approach (83% confidence, seen 1x):

index_fund's $0 PnL with 0 trades is suboptimal when all assets decline 7-16%. Any SHORT exposure would have been profitable. Passive long-only allocation fails in bearish regimes.
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish

Recommended approach (80% confidence, seen 1x):

SHORT-biased strategy with 45-55 trades/24h. Use RSI oversold + bearish MACD + price below SMA as entry confirmation. skill_aware_oss achieved +$691.44 vs index_fund $0.
  • Total observations: 0
  • First identified: 2026-01-30

Uniform Bullish

Recommended approach (80% confidence, seen 1x):

Focus LONG positions on highest momentum assets: DOGEUSDT (+3.82%) and SOLUSDT (+3.38%) outperformed BTC/ETH. Momentum leaders in bull markets offer best risk/reward.
  • Total observations: 0
  • First identified: 2026-02-02

Mixed Mostly Bullish

Recommended approach (80% confidence, seen 1x):

Focus shorts on the ONE bearish asset (ETHUSDT -0.99%) rather than fighting bullish momentum on BTC/SOL. Agents shorting BTC (+1.57%) and SOL (+3.90%) suffered.
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish

Recommended approach (80% confidence, seen 1x):

Low trade frequency (20 trades) with simple technical signals (SMA crossover, ROE targets) provides consistent positive returns. ta_baseline: +$20.54. Avoid complex multi-timeframe analysis that creates 'conflicting signals' in clearly directional markets.
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish

Recommended approach (78% confidence, seen 1x):

Avoid LONG positions entirely. index_fund's long-only allocation with 1.0 confidence failed to generate returns despite 'conviction'. Market direction trumps allocation strategy.
  • Total observations: 0
  • First identified: 2026-01-30

Mixed Mostly Bullish

Recommended approach (77% confidence, seen 1x):

Trade frequency sweet spot is 36-172 trades/24h. Below 36 (gpt_simple: 7) limits upside. Above 165 with poor discipline (agentic_gptoss) creates excessive churn.
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish

Recommended approach (75% confidence, seen 1x):

Trade frequency sweet spot is 48-63 trades/24h. Below 10 trades misses opportunities (gpt_simple -$73.60, ta_baseline $0). Above 60 trades shows diminishing returns (agentic_gptoss only +$79.87 with 63 trades).
  • Total observations: 0
  • First identified: 2026-01-30

Mixed Mostly Bullish

Recommended approach (75% confidence, seen 1x):

index_fund's $0 PnL with 0 trades is suboptimal when 4/5 assets are positive. Passive long exposure would have captured +1.45% average gain.
  • Total observations: 0
  • First identified: 2026-01-31

Uniform Bearish Mild

Recommended approach (75% confidence, seen 1x):

Market was uniformly bearish but with mild declines (BNB -1.50%, BTC -1.18%, ETH -0.78%, SOL -2.53%, DOGE -0.81%). Best performers used moderate-frequency SHORT-biased trading (31-32 trades) with selective entries. Forum-aware sentiment filtering and agentic multi-step reasoning both profited. Momentum and contrarian strategies lost money. Zero trading preserved capital perfectly.
  • Total observations: 0
  • First identified: 2026-03-07

Mixed Low Volatility

Recommended approach (75% confidence, seen 1x):

Market was mixed with small daily moves (BNB -0.23%, BTC +0.30%, ETH +0.36%, SOL -0.30%, DOGE -0.48%). Best approach: selective moderate-frequency trading with sentiment/forum filtering (24-31 trades). Forum-aware's +$232.17 dominated. Avoid momentum-following and contrarian strategies which both lost money. Zero trading is safe but suboptimal when forum-aware can extract alpha.
  • Total observations: 0
  • First identified: 2026-03-08

Uniform Bullish Moderate

Recommended approach (75% confidence, seen 1x):

Self-reflective position management (journal-aware) is the ONLY approach that profited among active agents. Meta-cognitive exits ('we are overtrading', 'close to reduce exposure') preserved gains and limited losses from wrong-direction entries.
  • Total observations: 0
  • First identified: 2026-03-09

Uniform Bearish Moderate

Recommended approach (73% confidence, seen 1x):

Avoid LONG-biased strategies entirely. Momentum (+8 trades, -$34.40) and contrarian (+9 trades, -$15.04) strategies that likely entered LONGs all lost money. Even low-frequency LONG entries (qwen35_simple, 4 trades, -$99.44) suffered large losses.
  • Total observations: 0
  • First identified: 2026-03-06

Uniform Bearish Mild

Recommended approach (73% confidence, seen 1x):

SOL was the worst performer (-2.53%) and BNB second worst (-1.50%), making them the best SHORT targets. ETH had the smallest decline (-0.78%), making it the worst SHORT target. Focus SHORT entries on highest-beta assets.
  • Total observations: 0
  • First identified: 2026-03-07

Uniform Bearish Mild

Recommended approach (70% confidence, seen 1x):

Trade frequency sweet spot in this mild bearish window was 31-32 trades/24h. Below that (11 trades contrarian) still lost money due to wrong direction. Above that is not represented. The key differentiator was directional alignment (SHORT bias) combined with selective entry filtering.
  • Total observations: 0
  • First identified: 2026-03-07

Mixed Low Volatility

Recommended approach (70% confidence, seen 1x):

In low-volatility mixed markets, trade frequency sweet spot is 24-31 trades/24h. Below that (2-16 trades) either breaks even or loses small amounts. Above that (33 trades for momentum) loses more. The key differentiator is signal quality, not frequency.
  • Total observations: 0
  • First identified: 2026-03-08

Uniform Bearish

Recommended approach (65% confidence, seen 1x):

Focus shorts on highest-volatility losers: ETHUSDT (-2.31%) offered best short opportunity vs SOLUSDT (-1.31%). Volatility creates profit potential.
  • Total observations: 0
  • First identified: 2026-01-30

Uniform Bearish Moderate

Recommended approach (65% confidence, seen 1x):

HIGH-frequency SHORT-biased trading with self-reflective position management (30-48 trades/24h). Journal-aware's 48 trades (+$296.01) and agentic's 30 trades (+$193.68) both profited by aligning with the bearish trend. Self-reflective exits helped capture profits and limit drawdowns. This CONTRADICTS prior patterns suggesting ultra-low frequency is optimal in bearish markets — when agents correctly identify the bearish regime, higher frequency with SHORT bias is profitable.
  • Total observations: 0
  • First identified: 2026-03-06

Uniform Bearish Moderate

Recommended approach (60% confidence, seen 1x):

Focus SHORT entries on highest-beta assets. ETHUSDT (-4.72%) and SOLUSDT (-4.40%) had the largest declines, offering the most profit potential. BTCUSDT (-4.29%) was also a strong SHORT candidate. BNBUSDT (-2.99%) had the smallest decline.
  • Total observations: 0
  • First identified: 2026-03-06

Uniform Bearish Moderate

Recommended approach (55% confidence, seen 1x):

Ultra-low frequency trading (13-16 trades/24h) with simple strategies. Market was uniformly bearish (BNB -1.70%, BTC -3.47%, ETH -4.63%, SOL -4.70%, DOGE -8.71%). Only qwen35 simple models profited. Zero trading also preserved capital. Avoid high-frequency trading (27-62 trades) which amplified losses. DOGE had the largest decline (-8.71%), making it the highest-beta SHORT target.
  • Total observations: 0
  • First identified: 2026-03-05

Uniform Bearish Moderate

Recommended approach (52% confidence, seen 1x):

If trading actively, cap at 16 trades/24h maximum. qwen35_122b_simple's 16 trades (+$50.27) was the sweet spot. Above 20 trades, all agents lost money. The relationship: 0 trades = $0, 13-16 trades = +$35-50, 14 trades (ta_bot) = -$64, 24 trades = -$6, 27 trades = -$229, 62 trades = -$71.
  • Total observations: 0
  • First identified: 2026-03-05

Uniform Bearish Moderate

Recommended approach (48% confidence, seen 1x):

Focus SHORT entries on highest-beta assets. DOGE (-8.71%) had nearly 5x the decline of BNB (-1.70%). SOL (-4.70%) and ETH (-4.63%) were also strong SHORT candidates. BNB was the most resilient, suggesting it should be avoided for SHORT entries.
  • Total observations: 0
  • First identified: 2026-03-05

Uniform Bullish

Recommended approach (47% confidence, seen 1x):

Passive index fund allocation or zero trading. When ALL assets are positive (BNB +1.23%, BTC +1.49%, ETH +1.08%, SOL +0.22%, DOGE +0.26%), active trading destroys value through transaction costs. index_fund achieved $0.00 vs -$134.51 for most active trader
  • Total observations: 0
  • First identified: 2026-01-28

Uniform Bullish

Recommended approach (45% confidence, seen 1x):

If trading, use extremely low frequency (<10 trades/24h) and hold positions longer. The 8 trades from index_fund vs 166 from agentic_gptoss shows 20x frequency difference with $134.51 performance gap
  • Total observations: 0
  • First identified: 2026-01-28

Uniform Bullish Strong

Recommended approach (45% confidence, seen 1x):

ZERO shorting rule. When ALL 5 assets gain >5% in 24h, any short position is catastrophic. This single rule would have prevented ~$838 in combined losses from gptoss_agentic and gptoss_forum_aware.
  • Total observations: 0
  • First identified: 2026-03-04

Mixed Slightly Bullish

Recommended approach (43% confidence, seen 1x):

Technical analysis baseline with moderate frequency (30-40 trades/24h) outperforms LLM-based multi-timeframe analysis. ta_baseline lost only $45.95 vs $134.51 for agentic_gptoss
  • Total observations: 0
  • First identified: 2026-01-28

Uniform Bullish Moderate

Recommended approach (15% confidence, seen 2x):

Trade frequency inversely correlates with losses when directional bias is wrong: 0 trades = $0, 6 trades = -$22.72, 15 trades = -$25.04, 27 trades = -$86 to +$55, 30-31 trades = -$97 to -$341. Each additional wrong-direction trade costs approximately $3-11.
  • Total observations: 0
  • First identified: 2026-03-02

Uniform Bullish Moderate

Recommended approach (13% confidence, seen 2x):

Zero trading or ultra-low frequency LONG-only entries. Market was uniformly bullish (BNB +3.31%, BTC +2.68%, ETH +3.90%, SOL +5.07%, DOGE +2.46%). Only journal-aware with self-reflective management profited (+$55.48). All other active agents lost money, suggesting most were SHORT-biased. SOL was the best performer (+5.07%), making it the top LONG target.
  • Total observations: 0
  • First identified: 2026-03-02

Confidence Guide

ConfidenceInterpretation
90%+High confidence - strong historical support
70-90%Moderate confidence - use with other signals
60-70%Low confidence - consider as one input
<60%Experimental - needs more data

*This skill is automatically generated and updated by the Observer Agent.*

平台分布

Claude Code

28.22%
按下载量换算1,158

OpenCode

22.94%
按下载量换算941

Gemini CLI

18.11%
按下载量换算743

Antigravity

12.26%
按下载量换算503

Codex

7.5%
按下载量换算308

Cursor

3.12%
按下载量换算128

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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