Crypto Social Intel

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Crypto social intelligence skill for AI agents. Activate when user mentions social trends, sentiment analysis, KOL signals, mention surge, Fear & Greed Index, 社交热度, 情绪分析, 恐惧贪婪指数, 热词爆发, KOL提及, 舆情监控, which tokens are trending on social media, is sentiment bullish or bearish, unusual social activity around a token, crypto social alpha, what's the Fear and Greed Index today.

Install

openclaw skills install crypto-social-intel

Crypto Social Intel

Social intelligence layer for crypto tokens. Powered by Santiment GraphQL API + alternative.me Fear & Greed Index.

5 Tools:

  • crypto-social-trending — Top tokens by social volume
  • crypto-sentiment-score — Sentiment score for a specific token
  • crypto-kol-signals — Social dominance anomaly (KOL proxy, v1.0: social dominance as proxy, not real Twitter KOL data)
  • crypto-mention-surge — Detect abnormal mention spikes
  • crypto-fear-greed — Fear & Greed Index (real-time, free)

MCP Endpoint

https://mcp-skills.ai.antalpha.com/mcp

Environment switching: For local dev/test, replace with http://localhost:3000/mcp.

Protocol: MCP Streamable HTTP (JSON-RPC over HTTP with mcp-session-id header).

Connection Flow

1. POST /mcp → initialize (get mcp-session-id from response header)
2. POST /mcp → tools/call  (with mcp-session-id header)

Data Sources

ToolSourceReal-timeAPI Key
crypto-social-trendingSantiment⚠️ Free tier: ~35-day lagRequired
crypto-sentiment-scoreSantiment⚠️ Free tier: ~35-day lagRequired
crypto-kol-signalsSantiment⚠️ Free tier: ~35-day lagRequired
crypto-mention-surgeSantiment⚠️ Free tier: ~35-day lagRequired
crypto-fear-greedalternative.me✅ Real-timeNone

Note: Santiment free tier has ~35-day data lag. For real-time social data, upgrade to Santiment Basic ($49/mo) and update SANTIMENT_API_KEY on the server — no code changes needed.

MCP Tools (5)

crypto-social-trending

Get top crypto tokens ranked by social volume.

Parameters:

  • limit (optional): 1-50, default 10
  • time_range (optional): "24h" | "7d", default "7d"

Response example:

{
  "items": [
    {
      "rank": 1,
      "slug": "bitcoin",
      "symbol": "BTC",
      "social_volume": 2413,
      "sentiment_score": 57,
      "signal_level": "LOW",
      "trend_change": "N/A",
      "data_source": "santiment"
    }
  ],
  "meta": { "data_source": "santiment", "note": "Free tier: ~35-day lag" }
}

crypto-sentiment-score

Get sentiment score and trend for a specific token.

Parameters:

  • symbol (required): Token symbol or slug, e.g. "BTC", "ETH", "bitcoin"
  • time_range (optional): "7d" | "30d", default "7d"

Response example:

{
  "symbol": "BTC",
  "sentiment_score": 57,
  "social_volume": 19301,
  "trend_direction": "down",
  "change_vs_prev": "-17.4%",
  "signal_level": "LOW",
  "data_source": "santiment"
}

crypto-kol-signals

Detect social dominance anomalies as KOL activity proxy.

v1.0 uses social_dominance_total as KOL proxy. Real Twitter KOL data planned for v2.0.

Parameters:

  • symbol (required): Token symbol or slug
  • time_range (optional): "7d" | "30d", default "7d"
  • threshold (optional): Surge multiplier threshold, 1-10, default 1.5

Response example:

{
  "symbol": "BTC",
  "social_dominance": 1.16,
  "dominance_change": -33,
  "surge_ratio": 0.67,
  "sentiment_direction": "bullish",
  "signal_level": "LOW",
  "note": "Social dominance anomaly used as KOL proxy. Real KOL data (Twitter API) planned for v2.0."
}

crypto-mention-surge

Detect tokens with abnormal social mention spikes.

Parameters:

  • threshold (optional): Surge ratio vs historical avg, default 2.0
  • time_window (optional): "7d" | "30d", default "7d"
  • limit (optional): 1-50, default 10

Response example:

{
  "items": [
    {
      "rank": 1,
      "symbol": "SOL",
      "current_volume": 1200,
      "historical_avg": 400,
      "surge_ratio": 3.0,
      "sentiment_direction": "bullish",
      "signal_level": "HIGH"
    }
  ],
  "total_found": 1
}

crypto-fear-greed

Get the Crypto Fear & Greed Index. Real-time, no API key required.

Parameters:

  • days (optional): History days to return, 1-30, default 7

Response example:

{
  "current": {
    "value": 23,
    "classification": "Extreme Fear",
    "date": "2026-04-15"
  },
  "trend": "improving",
  "signal_level": "MEDIUM",
  "market_note": "市场偏恐慌,情绪面有支撑,注意底部信号。",
  "history": [...],
  "data_source": "alternative.me"
}

Contrarian signal logic:

  • Extreme Fear (≤20) → 🔴 HIGH (historical buy opportunity)
  • Fear (21-40) → 🟡 MEDIUM
  • Neutral (41-60) → 🟢 LOW
  • Greed (61-79) → 🟢 LOW
  • Extreme Greed (≥80) → 🔴 HIGH (caution, potential top)

Signal Levels

LevelConditionBadge
HIGHsentiment>70 + surge>3x, OR Extreme Fear/Greed🔴
MEDIUMsentiment≥50 + surge≥2x, OR Fear🟡
LOWotherwise🟢

Note: crypto-kol-signals signal_level is based on dominance_change (independent of the sentiment+surge rule above). Extreme dominance change (>50% or <-50%) → HIGH; moderate change → MEDIUM; otherwise LOW.

Workflow

Check Market Sentiment (most common)

1. crypto-fear-greed { days: 7 }           ← overall market mood
2. crypto-social-trending { limit: 10 }    ← what's hot
3. Present combined view to user

Analyze Specific Token

1. crypto-sentiment-score { symbol: "ETH" }
2. crypto-kol-signals { symbol: "ETH", threshold: 1.5 }
3. Combine: sentiment score + dominance signal → final assessment

Early Warning Scan

1. crypto-mention-surge { threshold: 2.0, limit: 10 }
2. For tokens with HIGH/MEDIUM signals → crypto-sentiment-score to confirm
3. Alert user to tokens with multiple converging signals

Combined with Smart Money

When social signal + on-chain signal converge:

1. crypto-mention-surge detects abnormal spike
2. → Call smart-money-signal to check if whales are buying
3. Two signals converging → stronger conviction

Message Template

When presenting social intel to user:

📊 市场情绪总览
恐惧贪婪指数: 23 — Extreme Fear 🔴
趋势: improving ↗
注记: 历史上极度恐慌区间往往是逆向机会,但需结合链上数据确认。

🔥 社交热榜 Top 5
#1 BTC  vol=2413  sentiment=57  🟢 LOW
#2 ETH  vol=491   sentiment=52  🟢 LOW
#3 SOL  vol=386   sentiment=52  🟢 LOW

Mention surge alert:

🚨 社交提及暴增预警
SOL: 当前3000 vs 均值400 → 7.5x ↑ 🔴 HIGH (bullish)
建议: 关注链上是否有聪明钱跟进

Agent Behavior Rules

On "市场情绪怎么样" / "market sentiment"

  1. Call crypto-fear-greed first (real-time, fast)
  2. Optionally call crypto-social-trending for top tokens
  3. Present combined view
  4. When Santiment data is involved, always append: ⚠️ 社交数据来自 Santiment 免费层,存在约 35 天延迟,仅供参考。

On "BTC情绪" / "SOL sentiment" / specific token

  1. Call crypto-sentiment-score { symbol }
  2. If signal_level is HIGH or MEDIUM, also call crypto-kol-signals
  3. Present score + trend + signal
  4. Always append disclaimer: ⚠️ 数据来自 Santiment 免费层,存在约 35 天延迟,仅供参考,勿作实时决策依据。
  5. For kol-signals output, always note: 注:v1.0 KOL 信号以社交主导度代理,非真实 Twitter KOL 数据,v2.0 将接入 Twitter API。

On "哪些币在暴涨社交" / "mention surge" / "异常热度"

  1. Call crypto-mention-surge { threshold: 2.0 }
  2. For HIGH signal items, offer to do deeper analysis
  3. Always append disclaimer: ⚠️ 数据来自 Santiment 免费层,存在约 35 天延迟,仅供参考。

On "恐惧贪婪" / "fear greed" / "市场贪婪指数"

  1. Directly call crypto-fear-greed
  2. Present value, classification, trend, market note

Supported Token Slugs

Common symbol → slug mapping (Santiment):

SymbolSlug
BTCbitcoin
ETHethereum
SOLsolana
BNBbinance-coin
XRPripple
DOGEdogecoin
ADAcardano
AVAXavalanche
DOTpolkadot
LINKchainlink
UNIuniswap
ARBarbitrum
OPoptimism
SUIsui

For unlisted tokens, pass the full Santiment slug directly (e.g. "pepe", "floki").


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