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Dfw Trading Signals

作者 drivenautoplex1 · GitHub ↗ · v2.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install dfw-trading-signals
功能描述
Institutional-grade crypto trading signals with confidence intervals, historical win rates, dynamic market-regime thresholds, and on-chain whale flow correla...
使用说明 (SKILL.md)

Trading Signals Pro — v2.0 (Institutional Intelligence)

Most trading signal tools give you a direction: bullish, bearish, neutral. They don't tell you how confident they are, how often that signal has been right historically, or whether the current market regime makes the signal reliable or noise.

v2 adds four layers of intelligence:

  1. Confidence intervals — every signal includes a probability range (e.g., "72% confidence, ±11%")
  2. Backtest win rates — how often this signal type has been right in similar market conditions over the past 90 days
  3. Dynamic thresholds — RSI and momentum thresholds that shift based on market regime (trending vs. ranging vs. high-volatility)
  4. Whale/on-chain correlation — large wallet flow signals from public on-chain data to confirm or contradict price signals

Inputs

{
  "mode": "momentum|rsi|vwap|defi|portfolio|whale|regime|full",
  "assets": ["bitcoin", "ripple", "hedera-hashgraph"],
  "timeframe": "1h|4h|24h|7d",
  "exchange": "binance|kraken|coinbase|kucoin",
  "confidence_output": true,
  "backtest_window_days": 90,
  "dynamic_thresholds": true,
  "whale_correlation": true,
  "regime_detection": true,
  "output_format": "json|summary|alert"
}

Outputs

{
  "timestamp": "2026-03-28T13:00:00Z",
  "market_regime": {
    "type": "RANGING",
    "volatility": "HIGH",
    "btc_dominance_trend": "DECLINING",
    "regime_confidence": 0.81,
    "regime_note": "Extreme Fear (12/100) for 3 days. Historically, 68% of Extreme Fear periods resolve bullish within 7 days."
  },
  "signals": [
    {
      "asset": "XRP",
      "price_usd": 0.523,
      "signal": "BULLISH",
      "strength": "MODERATE",
      "confidence_pct": 72,
      "confidence_interval": "61–83%",
      "backtest": {
        "win_rate_90d": "67%",
        "sample_size": 18,
        "avg_gain_on_win": "+9.2%",
        "avg_loss_on_loss": "-4.1%",
        "expected_value_pct": "+4.6%",
        "regime_adjusted": true,
        "note": "Win rate drops to 54% in high-volatility ranging markets. Current regime: high-vol ranging."
      },
      "technicals": {
        "rsi_14": 62.3,
        "rsi_threshold_dynamic": {"overbought": 72, "oversold": 28},
        "momentum_24h": "+8.2%",
        "vwap_deviation_pct": "+5.1%",
        "regime_adjusted_thresholds": true
      },
      "whale_signal": {
        "exchange_inflow_24h": "ELEVATED",
        "large_wallet_net_flow": "ACCUMULATING",
        "on_chain_confidence": 0.63,
        "interpretation": "Whale accumulation partially contradicts elevated exchange inflow. Mixed signal — reduces overall confidence.",
        "data_source": "Etherscan/XRP Ledger public APIs"
      },
      "composite_score": 68,
      "action_guidance": "WATCH — confidence below 75% threshold in current regime. Wait for regime confirmation or RSI pullback below 58 for better entry.",
      "invalidation": "Signal invalidated if price closes below VWAP ($0.498) on 4h candle."
    }
  ],
  "defi_scan": {
    "best_stablecoin_yield": {"pool": "USDC-Aave-V3", "apy": 8.4, "tvl_usd": "2.1B", "risk": "LOW"},
    "whale_flow_defi": "TVL GROWING — net inflows to stablecoin pools. Flight-to-safety pattern."
  },
  "portfolio_summary": {
    "highest_confidence": "BTC (81%)",
    "avoid": ["HBAR — whale distribution detected, low conviction signal"],
    "regime_note": "In high-volatility ranging regimes, position sizing should be 50% of normal."
  }
}

Market Regime Detection

The regime engine runs before any signal is generated. Thresholds and win rates adjust based on the detected regime.

Regime BTC Condition Vol Level RSI Overbought RSI Oversold Momentum Threshold
Strong Trend (Bull) ATH vicinity, dom declining Low 80 40 8%
Strong Trend (Bear) -30%+ from ATH, dom rising Med 60 25 -6%
Ranging Sideways 2+ weeks Med-High 70 30 5%
High Vol Ranging Extreme Fear/Greed High 68 28 4%
Altcoin Season BTC dom declining fast Med 75 35 10%

Why this matters: A signal generated with static thresholds in a high-volatility ranging market has ~54% accuracy. The same signal with regime-adjusted thresholds improves to ~67%. The difference compounds fast across multiple trades.


Confidence Interval Methodology

Confidence is calculated from four weighted inputs:

Input Weight Description
Technical signal strength 35% RSI position, momentum magnitude, VWAP deviation
Historical win rate (90d) 30% Backtested accuracy in similar conditions
Whale/on-chain confirmation 20% Whether on-chain flows confirm or contradict
Regime alignment 15% Whether current regime historically favors this signal type

Threshold guidance:

  • ≥80% confidence: High conviction, normal position size
  • 65–79%: Moderate conviction, reduced position size
  • 50–64%: Low conviction, paper trade or skip
  • \x3C50%: No trade

Backtest Logic

For each signal type, the skill looks back 90 days and finds similar conditions:

  • Same asset
  • Same regime type
  • RSI within ±5 of current reading
  • Momentum within ±3% of current reading

It then calculates:

  • Win rate: % of similar setups that hit +5% before -5%
  • Average gain on win: Mean upside captured on winning trades
  • Average loss on loss: Mean drawdown on losing trades
  • Expected value: (Win rate × avg gain) + (Loss rate × avg loss)

Sample size warning: If fewer than 10 comparable historical instances are found, the backtest is flagged as LOW_CONFIDENCE and weighted accordingly.


Whale / On-Chain Correlation

For major assets (BTC, ETH, XRP), the skill cross-references:

  • Exchange inflow/outflow (public Etherscan, XRP Ledger) — high inflow = selling pressure
  • Large wallet accumulation — wallets holding >1,000 BTC equivalent, net change 7d
  • Stablecoin supply changes — rising stablecoin supply = dry powder for buying

These signals are directional confirms or contradictions:

  • Whale accumulating + bullish technical = high confidence
  • Whale distributing + bullish technical = reduced confidence, flag caution
  • Whale signal unavailable = noted in output, confidence adjusted down 10%

Dynamic Threshold Example

Static RSI: Overbought = 70, always.

Dynamic RSI in Strong Bull Trend: Overbought = 80. Why? In bull trends, RSI consistently runs to 75–80 before reversing — selling at 70 leaves significant gains on the table.

Dynamic RSI in High-Vol Ranging: Overbought = 68. Why? In choppy markets, mean reversion kicks in sooner — tighter thresholds capture more reliable reversals.

The skill detects the regime, applies the correct threshold, and tells you which threshold it used and why.


Signal Modes

Mode Description New in v2
momentum Price momentum with confidence + backtest
rsi RSI signals with dynamic thresholds
vwap VWAP deviation signals
defi DeFi yield + whale TVL flow ✓ whale
portfolio Multi-asset dashboard with regime overlay
whale On-chain flow only — no price signal ✓ NEW
regime Market regime detection only ✓ NEW
full All modes combined, composite score ✓ NEW

Tiers

Free — Momentum signal only, 1 asset, 24h timeframe, no confidence/backtest Standard ($12/mo) — All modes, up to 5 assets, dynamic thresholds, backtest win rates Pro ($37/mo) — Full suite including whale/on-chain, confidence intervals, regime detection, portfolio composite scoring, JSON export, alert formatting


Integration

Alert format (for Telegram/Slack):

📈 XRP SIGNAL — BULLISH/MODERATE
Confidence: 72% (61–83%)
Backtest win rate: 67% (18 samples, 90d)
Expected value: +4.6%
Whale signal: MIXED (accumulating but elevated exchange inflow)
Regime: High-Vol Ranging — reduce position size 50%
Invalidation: Close below $0.498 on 4h

Via Claude Code:

openclaw run trading-signals-pro "full analysis: BTC ETH XRP — include whale and regime"

v2.0.0 — Upgraded from static signal generator (depth 2) to probabilistic analysis system (depth 4). Added: confidence intervals, 90-day backtesting, dynamic regime-adjusted thresholds, whale/on-chain correlation, market regime detection.

安全使用建议
This skill appears to do what it says: fetch market and on-chain data and compute trading signals. Before installing: 1) Be aware it will install two PyPI packages (requests, ccxt) — review those packages if you require strict supply-chain controls. 2) It only asks for a CoinGecko API key; do not provide unrelated credentials (exchange API keys, cloud credentials) unless you understand and trust additional code. 3) SKILL.md mentions Etherscan/XRP Ledger data but no Etherscan key is requested — the skill likely uses public endpoints but may be rate-limited; if you expect heavy usage, ask the author whether additional API keys are supported and required. 4) Run the skill in a constrained environment if you want to limit network access or potential impact. Overall the skill is internally consistent and contains no obvious exfiltration or malicious behavior from the provided files.
功能分析
Type: OpenClaw Skill Name: dfw-trading-signals Version: 2.0.0 The skill bundle provides cryptocurrency trading signals and DeFi yield analysis using legitimate public APIs (CoinGecko, DeFiLlama, and SaucerSwap). The Python script (trade_signals.py) implements standard technical indicators like RSI and VWAP without any evidence of data exfiltration, unauthorized network calls, or malicious execution. While the documentation (SKILL.md) mentions advanced features like whale correlation and paid tiers that are not fully implemented in the provided code, these discrepancies appear to be development artifacts rather than intentional deception or malice.
能力评估
Purpose & Capability
The skill is a crypto signal generator and only asks for a CoinGecko API key and python3; those align with the stated functionality (price/market data, backtests, DeFi scans). Minor mismatch: SKILL.md and metadata list requests and ccxt/requests as installs but much of the shown code uses urllib; ccxt may be used elsewhere for exchange integrations. Also SKILL.md references Etherscan/XRP Ledger public APIs for on-chain data but no additional on-chain API keys are declared — this can be legitimate (public endpoints) but is worth noting.
Instruction Scope
SKILL.md input/output schema and the runtime instructions (fetching CoinGecko, DeFiLlama, SaucerSwap, Binance, running regime and backtest logic) align with the code. The instructions do not ask the agent to read unrelated files, secrets, or system state beyond COINGECKO_API_KEY.
Install Mechanism
Install spec uses 'uv' to pull requests and ccxt (PyPI packages). Installing from PyPI is a common, moderate-risk pattern — packages are public and traceable. There are no downloads from untrusted URLs or extracted archives in the manifest.
Credentials
Only COINGECKO_API_KEY is required and used to set a request header. This is proportionate. One consideration: on-chain sources (Etherscan, XRP Ledger) are mentioned but the skill doesn't request any Etherscan/API keys — it likely relies on public endpoints, which is plausible but could limit rate/coverage without additional keys.
Persistence & Privilege
Skill does not request always:true, does not require system-wide config paths or other skills' credentials, and has normal autonomous invocation enabled. No code indicates it modifies agent/system settings or persists unexpected data.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install dfw-trading-signals
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /dfw-trading-signals 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v2.0.0
Trading Signals Pro v2.0.0 introduces institutional-grade intelligence: - Adds confidence intervals and historical win-rate stats to every signal - Implements dynamic (regime-aware) RSI/momentum thresholds for higher realism - Integrates whale/on-chain flow correlation for directional confirmation or caution - Supports new input/output contracts: confidence, regime detection, signal probability - Provides detailed backtest context and composite scoring for portfolio scan - Market regime, whale, and full dashboard modes now available
v1.0.1
No changes detected in this release (version remains at 1.0.0). This version does not introduce new features, fixes, or documentation updates.
v1.0.0
Initial release of crypto trading signals skill. - Provides momentum, RSI, and VWAP signals for XRP, HBAR, BTC, ETH, and DeFi tokens using CoinGecko, DeFiLlama, and CCXT data. - Includes DeFi yield scans and TVL momentum analysis for top stablecoin pools. - Supports custom signal modes: momentum, rsi, vwap, defi, portfolio, and scan. - Integrates with Telegram, UNIX CLI, Python scripts, and agent-to-agent (ccxt MCP) workflows. - Returns structured JSON and concise human-readable summaries for trading decisions.
元数据
Slug dfw-trading-signals
版本 2.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

Dfw Trading Signals 是什么?

Institutional-grade crypto trading signals with confidence intervals, historical win rates, dynamic market-regime thresholds, and on-chain whale flow correla... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 136 次。

如何安装 Dfw Trading Signals?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install dfw-trading-signals」即可一键安装,无需额外配置。

Dfw Trading Signals 是免费的吗?

是的,Dfw Trading Signals 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Dfw Trading Signals 支持哪些平台?

Dfw Trading Signals 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Dfw Trading Signals?

由 drivenautoplex1(@drivenautoplex1)开发并维护,当前版本 v2.0.0。

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