Scrub Trading Signals Pro

Crypto trading signals using CoinGecko price data, DeFiLlama TVL trends, and CCXT exchange order flow — momentum, RSI, VWAP signals for XRP, HBAR, BTC, ETH,...

Security Scan

The skill's description and runtime instructions claim to run a Python script (trade_signals.py) and install Python packages, but the package contains no code files — this mismatch is a clear coherence problem and needs clarification before use.

Purpose & Capability

The skill's stated purpose (compute momentum/RSI/VWAP using CoinGecko, DeFiLlama, and ccxt) is internally consistent with requiring python3, requests and ccxt and the COINGECKO_API_KEY. However, the SKILL.md repeatedly references and documents a local script (trade_signals.py) and concrete Python implementations as if the code is included — but the skill package contains no code files. That is an important inconsistency: either the agent is expected to run a non-existent script, or the skill is only documentation and cannot perform the promised actions without missing files.

Instruction Scope

Instructions direct the agent to call external APIs (CoinGecko, DeFiLlama, SaucerSwap) and optionally use ccxt public endpoints — those network calls are expected for this functionality. The problematic part is that SKILL.md instructs running trade_signals.py and shows CLI examples and code snippets but provides no runtime code. If the agent or user runs those commands as-is they will fail or attempt to run code that does not exist. The instructions otherwise do not attempt to read unrelated local secrets or system files.

Install Mechanism

The install spec requests two Python packages (requests and ccxt), which are appropriate for the described tasks. The install 'kind' is listed as 'uv' which is non-standard/unfamiliar in this context (typical would be pip). This could be a harmless naming detail in the registry, but it should be confirmed that the install mechanism fetches packages from a trusted index (PyPI) rather than an arbitrary URL or custom source.

Credentials

Only COINGECKO_API_KEY is required and declared as the primary credential. That aligns with using CoinGecko for price data. No unrelated secrets or broad cloud credentials are requested.

Persistence & Privilege

The skill does not request always:true and uses default invocation settings. It does not declare any persistent system-wide modifications or access to other skills' configs.

What to consider before installing

Do not install or provide credentials yet. Key issues to resolve before use: - Missing code: SKILL.md repeatedly refers to trade_signals.py and shows code snippets, but the published package contains no code files. Ask the publisher for the actual script or a source tarball. Without the code the skill cannot perform the promised actions and CLI examples will fail. - Confirm install source: the install 'kind' is 'uv' (unfamiliar). Verify the installer will fetch requests and ccxt from a trusted PyPI source (not a custom URL) and confirm what filesystem changes occur during install. - API key scope: CoinGecko often works without an API key for public data; if you must provide COINGECKO_API_KEY, prefer a read-only or limited key and consider rotating it after testing. Expect that asset symbols and query parameters will be sent to CoinGecko, DeFiLlama, SaucerSwap and exchange public endpoints (these are external network calls). If you have privacy concerns, do not supply the key until you can review the actual code. - Trust boundaries: the skill may call ccxt or agent-to-agent MCP functions to fetch exchange data. Only run this skill in environments where outbound API calls and use of those libraries are acceptable and where the agent/other agents involved are trusted. If the author provides the missing trade_signals.py and confirms the install pulls from PyPI, re-evaluate — with the current package contents the skill is incoherent and should be treated as suspicious.

Trading Signals Skill

Get trading signals for crypto assets — momentum, mean reversion, DeFi yield arbitrage, and on-chain TVL trends.

What this skill does

Analyze:

• Price momentum — 1h/4h/24h momentum scoring for any CoinGecko-listed token
• RSI-style signals — overbought/oversold detection from OHLCV data
• VWAP signals — price vs volume-weighted average (exchange data via ccxt)
• DeFi yield scan — highest-yield stablecoin pools, TVL momentum (DeFiLlama)
• XRP/HBAR ecosystem — SaucerSwap LP signal, staking yield vs market rate
• Portfolio scan — multi-asset signal dashboard for a watchlist

Input contract

Tell me:

1. Mode: momentum / rsi / vwap / defi / portfolio / scan
2. Asset(s): coin IDs (CoinGecko format: "bitcoin", "ripple", "hedera-hashgraph") or tickers
3. Timeframe (optional): 1h / 4h / 24h / 7d (default: 24h)
4. Exchange (optional for ccxt modes): binance / kraken / coinbase / kucoin (default: binance public)
5. Threshold (optional): signal sensitivity 1-10 (default: 5)

Example prompts:

• "Momentum signal for XRP and HBAR over last 24h"
• "RSI scan on BTC, ETH, XRP — flag anything overbought or oversold"
• "DeFi yield scan — best stablecoin yield right now"
• "Portfolio dashboard for: BTC, ETH, XRP, HBAR, MATIC"
• "VWAP signal for ETH on Binance 4h"
• "SaucerSwap LP scan — current HBAR pool yields"

Output contract

Returns JSON + human-readable summary:

{
  "timestamp": "2026-03-27T12:00:00Z",
  "signals": [
    {
      "asset": "XRP",
      "coingecko_id": "ripple",
      "price_usd": 0.523,
      "momentum_24h": "+8.2%",
      "momentum_7d": "+12.4%",
      "rsi_14": 62.3,
      "signal": "BULLISH",
      "strength": "MODERATE",
      "notes": "Breaking above 30-day MA. Volume spike on 4h. Watch $0.55 resistance."
    }
  ],
  "market_context": "Risk-on sentiment. BTC dominance declining — altcoin rotation in progress.",
  "top_picks": ["XRP", "HBAR"],
  "avoid": [],
  "defi_best_yield": {
    "pool": "USDC-Aave-V3-Ethereum",
    "apy": 8.4,
    "tvl_usd": "2.1B"
  }
}

How the skill works

The skill calls trade_signals.py (included in this skill folder) which:

1. CoinGecko API — price history, market cap, volume, 24h change (free tier via COINGECKO_API_KEY or demo key)
2. DeFiLlama API — TVL, yield pools, protocol health (no auth)
3. ccxt — public order book + OHLCV from any supported exchange (no auth for public endpoints)

# Signal logic overview (see trade_signals.py for full implementation)

def momentum_signal(prices: list[float], volumes: list[float]) -> dict:
    """
    Returns: signal (BULLISH/BEARISH/NEUTRAL), strength (STRONG/MODERATE/WEAK),
             momentum_pct, rsi_14, vwap_deviation
    """
    rsi = calculate_rsi(prices, period=14)
    momentum = (prices[-1] - prices[-24]) / prices[-24] * 100  # 24h %
    vwap = sum(p * v for p, v in zip(prices, volumes)) / sum(volumes)
    vwap_dev = (prices[-1] - vwap) / vwap * 100

    if rsi > 70: signal = "OVERBOUGHT"
    elif rsi < 30: signal = "OVERSOLD/BULLISH_SETUP"
    elif momentum > 5 and prices[-1] > vwap: signal = "BULLISH"
    elif momentum < -5 and prices[-1] < vwap: signal = "BEARISH"
    else: signal = "NEUTRAL"

    strength = "STRONG" if abs(momentum) > 10 else "MODERATE" if abs(momentum) > 5 else "WEAK"
    return {"signal": signal, "strength": strength, "rsi_14": round(rsi, 1),
            "momentum_pct": round(momentum, 2), "vwap_deviation_pct": round(vwap_dev, 2)}

Integration with agent infrastructure

Via Telegram (direct command):

@openclaw trading-signals momentum "XRP HBAR BTC" 24h

Via Claude Code:

openclaw run trading-signals "portfolio dashboard: BTC ETH XRP HBAR"

Via Python (direct script):

python3 trade_signals.py --mode=momentum --assets=ripple,hedera-hashgraph --timeframe=24h
python3 trade_signals.py --mode=defi --min-tvl=100 --min-apy=5
python3 trade_signals.py --mode=portfolio --assets=bitcoin,ethereum,ripple,hedera-hashgraph

Via existing ccxt MCP (agent-to-agent):

# Agents with ccxt MCP access can call:
mcp__ccxt__fetchOHLCV(symbol="XRP/USDT", timeframe="1h", limit=100)
mcp__ccxt__fetchTicker(symbol="XRP/USDT")
mcp__ccxt__fetchOrderBook(symbol="XRP/USDT", limit=20)
# Then pipe results into trade_signals.py for signal calculation

Signal interpretation guide

Signal	RSI	Action
STRONG BULLISH	50-65	Entry zone, momentum confirmed
OVERBOUGHT	>70	Wait for pullback, tighten stops
OVERSOLD/BULLISH_SETUP	<30	Watch for reversal confirmation
STRONG BEARISH	35-50	Exit or hedge
NEUTRAL	45-55	Range-bound, wait for breakout

SaucerSwap LP Integration

For HBAR ecosystem signals, the skill also checks SaucerSwap pool yields:

# SaucerSwap public API (no auth)
SAUCER_POOLS_URL = "https://api.saucerswap.finance/pools"

def saucer_lp_signal(pools: list) -> dict:
    """Returns best LP opportunities with impermanent loss risk rating."""
    scored = []
    for p in pools:
        apy = p.get('apr7d', 0)
        tvl = p.get('tvlUsd', 0)
        il_risk = estimate_il_risk(p['token0'], p['token1'])
        score = apy - (il_risk * 10)  # penalize high IL pairs
        scored.append({**p, 'score': score, 'il_risk': il_risk})
    return sorted(scored, key=lambda x: x['score'], reverse=True)[:5]

Example outputs

Momentum scan — XRP + HBAR

TRADING SIGNALS — 2026-03-27 12:00 UTC
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

XRP  $0.523  ↑ +8.2% (24h)  RSI: 62  BULLISH/MODERATE
  Volume: 2.1x avg | VWAP: $0.498 (price above) | Watch: $0.55 resistance

HBAR $0.082  ↑ +5.1% (24h)  RSI: 57  BULLISH/WEAK
  Volume: 1.4x avg | VWAP: $0.079 (price above) | Wyoming integration catalysts

MARKET: Risk-on. BTC dominance -1.2% → altcoin rotation. XRP leads on volume.

TOP SIGNAL: XRP — strongest momentum + volume confirmation this week.

DeFi yield scan

DEFI YIELD SCAN — 2026-03-27 12:00 UTC
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

STABLECOIN YIELDS (no IL risk):
1. USDC / Aave V3 / Ethereum    8.4% APY  TVL: $2.1B  ✓ Safe
2. USDT / Compound / Base       7.2% APY  TVL: $890M  ✓ Safe
3. DAI  / Spark / Ethereum      6.8% APY  TVL: $1.4B  ✓ Safe
4. USDS / Sky / Ethereum        5.9% APY  TVL: $780M  ✓ Safe

VOLATILE PAIRS (IL risk noted):
5. ETH/WETH / Curve / Ethereum  12.1% APY  TVL: $3.2B  IL: minimal (correlated pair)
6. WBTC/ETH / Uniswap V3       9.4% APY   TVL: $445M  IL: moderate

AVOID: Pools <$10M TVL, APY >50% (likely unsustainable emissions)