xai-crypto-sentiment
🎯Skillfrom adaptationio/skrillz
|xai-crypto-sentiment skill from adaptationio/skrillz
Installation
npx skills add https://github.com/adaptationio/skrillz --skill xai-crypto-sentimentSkill Details
Real-time cryptocurrency sentiment analysis using Twitter/X via Grok. Use when analyzing crypto sentiment, tracking whale activity, or gauging market fear/greed.
Overview
# xAI Crypto Sentiment Analysis
Real-time cryptocurrency sentiment from Crypto Twitter (CT) using Grok's native X integration.
Quick Start
```python
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("XAI_API_KEY"),
base_url="https://api.x.ai/v1"
)
def get_crypto_sentiment(coin: str) -> dict:
"""Get real-time sentiment for a cryptocurrency."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": f"""Analyze Crypto Twitter sentiment for {coin}.
Return JSON:
{{
"coin": "{coin}",
"sentiment": {{
"overall": "bullish" | "bearish" | "neutral",
"score": -1.0 to 1.0,
"confidence": 0.0 to 1.0
}},
"fear_greed": "extreme fear" | "fear" | "neutral" | "greed" | "extreme greed",
"metrics": {{
"bullish_percent": 0-100,
"bearish_percent": 0-100,
"mention_volume": "high" | "medium" | "low",
"trend": "increasing" | "stable" | "decreasing"
}},
"whale_mentions": {{
"detected": true/false,
"sentiment": "accumulating" | "distributing" | "neutral",
"notable": [...]
}},
"narratives": ["narrative1", "narrative2"],
"fud_alerts": [...],
"fomo_level": "high" | "medium" | "low" | "none"
}}"""
}]
)
return response.choices[0].message.content
# Example
sentiment = get_crypto_sentiment("Bitcoin")
print(sentiment)
```
Crypto Twitter Influencers
```python
CRYPTO_INFLUENCERS = [
# Bitcoin Maxis
"saborskip",
"michael_saylor",
# Analysts
"CryptoCapo_",
"Pentosh1",
"ColdBloodShill",
# News
"WatcherGuru",
"whale_alert",
# DeFi
"DefiIgnas",
"Route2FI",
# Altcoins
"AltcoinGordon",
"CryptoKaleo"
]
```
Sentiment Functions
Bitcoin Market Sentiment
```python
def bitcoin_sentiment() -> dict:
"""Get comprehensive Bitcoin sentiment analysis."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": """Analyze Bitcoin sentiment on Crypto Twitter.
Return JSON:
{
"bitcoin": {
"sentiment_score": -1 to 1,
"fear_greed_index": 0-100,
"fear_greed_label": "...",
"trend": "bullish/bearish/consolidating"
},
"market_structure": {
"support_levels_mentioned": [...],
"resistance_levels_mentioned": [...],
"key_levels": [...]
},
"whale_activity": {
"accumulation_signals": true/false,
"distribution_signals": true/false,
"notable_moves": [...]
},
"narratives": {
"bullish": [...],
"bearish": [...]
},
"influencer_consensus": {
"bullish_count": n,
"bearish_count": n,
"key_calls": [...]
},
"on_chain_mentions": {
"exchange_flows": "inflows/outflows/neutral",
"wallet_activity": "..."
},
"macro_sentiment": {
"correlation_to_stocks": "...",
"fed_mentions": "...",
"institutional_interest": "..."
}
}"""
}]
)
return response.choices[0].message.content
```
Altcoin Season Detection
```python
def detect_altseason() -> dict:
"""Detect if altcoin season is emerging."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": """Analyze Crypto Twitter for altcoin season signals.
Return JSON:
{
"altseason_status": "active" | "emerging" | "not present",
"confidence": 0 to 1,
"signals": {
"btc_dominance_sentiment": "...",
"altcoin_volume": "high/medium/low",
"rotation_patterns": "...",
"new_narratives": [...]
},
"hot_sectors": [
{"sector": "...", "sentiment": ..., "top_coins": [...]}
],
"coins_trending": [
{"coin": "...", "sentiment": ..., "catalyst": "..."}
],
"risk_level": "high/medium/low",
"recommendation": "..."
}"""
}]
)
return response.choices[0].message.content
```
Token Sentiment Analysis
```python
def analyze_token(token: str, chain: str = None) -> dict:
"""Analyze sentiment for a specific token."""
chain_context = f" on {chain}" if chain else ""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": f"""Analyze Crypto Twitter sentiment for {token}{chain_context}.
Return JSON:
{{
"token": "{token}",
"chain": "{chain or 'unknown'}",
"sentiment": {{
"score": -1 to 1,
"label": "...",
"volume": "high/medium/low"
}},
"community_health": {{
"engagement": "high/medium/low",
"holder_sentiment": "...",
"developer_activity_mentions": "..."
}},
"narratives": [...],
"catalysts": {{
"upcoming": [...],
"recent": [...]
}},
"risks": {{
"fud_topics": [...],
"concerns_raised": [...],
"rug_risk_mentions": true/false
}},
"influencer_mentions": [...],
"comparison_to_competitors": "..."
}}"""
}]
)
return response.choices[0].message.content
```
DeFi Protocol Sentiment
```python
def defi_protocol_sentiment(protocol: str) -> dict:
"""Analyze sentiment for a DeFi protocol."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": f"""Analyze Crypto Twitter sentiment for {protocol} DeFi protocol.
Return JSON:
{{
"protocol": "{protocol}",
"sentiment": {{
"score": -1 to 1,
"trend": "improving/declining/stable"
}},
"tvl_sentiment": "growing/stable/declining concern",
"security_mentions": {{
"concerns": [...],
"audits_mentioned": [...],
"exploit_risk_perception": "high/medium/low"
}},
"yield_sentiment": "attractive/fair/unattractive",
"community_growth": "...",
"governance_sentiment": "...",
"competitors_mentioned": [...]
}}"""
}]
)
return response.choices[0].message.content
```
NFT Market Sentiment
```python
def nft_sentiment(collection: str = None) -> dict:
"""Analyze NFT market sentiment."""
target = f"the {collection} collection" if collection else "the NFT market"
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": f"""Analyze Crypto Twitter sentiment for {target}.
Return JSON:
{{
"target": "{collection or 'NFT Market'}",
"sentiment": {{
"score": -1 to 1,
"market_phase": "bull/bear/recovery/mania"
}},
"volume_sentiment": "high/medium/low",
"floor_price_sentiment": "stable/rising/falling concern",
"trending_collections": [...],
"whale_activity": {{
"notable_buys": [...],
"notable_sales": [...]
}},
"narratives": [...],
"mint_sentiment": "hot/cooling/cold"
}}"""
}]
)
return response.choices[0].message.content
```
Whale Alert Monitoring
```python
def monitor_whale_alerts() -> dict:
"""Monitor whale activity mentions on CT."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": """Search Crypto Twitter for recent whale alerts and large transactions.
Focus on @whale_alert and similar accounts.
Return JSON:
{
"timestamp": "...",
"recent_whale_moves": [
{
"coin": "...",
"amount_usd": "...",
"direction": "exchange_inflow/exchange_outflow/wallet_transfer",
"interpretation": "bullish/bearish/neutral",
"source": "..."
}
],
"exchange_flow_summary": {
"net_flow": "inflows/outflows/balanced",
"interpretation": "..."
},
"accumulation_signals": [...],
"distribution_signals": [...],
"notable_wallet_activity": [...]
}"""
}]
)
return response.choices[0].message.content
```
FOMO/FUD Detection
```python
def detect_fomo_fud(coin: str) -> dict:
"""Detect FOMO or FUD patterns for a cryptocurrency."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": f"""Analyze Crypto Twitter for FOMO and FUD signals around {coin}.
Return JSON:
{{
"coin": "{coin}",
"fomo_analysis": {{
"level": "extreme/high/moderate/low/none",
"triggers": [...],
"warning_signs": [...],
"sustainability": "likely/unlikely"
}},
"fud_analysis": {{
"level": "extreme/high/moderate/low/none",
"sources": [...],
"legitimacy": "valid concerns/coordinated/mixed",
"topics": [...]
}},
"manipulation_signals": {{
"detected": true/false,
"type": "pump/dump/coordinated/organic",
"evidence": [...]
}},
"contrarian_signal": {{
"extreme_fear": true/false,
"extreme_greed": true/false,
"actionable": "..."
}}
}}"""
}]
)
return response.choices[0].message.content
```
Crypto Market Dashboard
```python
def crypto_market_dashboard() -> dict:
"""Get overall crypto market sentiment dashboard."""
response = client.chat.completions.create(
model="grok-4-1-fast",
messages=[{
"role": "user",
"content": """Create a comprehensive Crypto Twitter market dashboard.
Return JSON:
{
"timestamp": "...",
"market_sentiment": {
"overall": -1 to 1,
"fear_greed": 0-100,
"trend": "bullish/bearish/neutral"
},
"bitcoin": {
"sentiment": ...,
"key_levels": [...]
},
"ethereum": {
"sentiment": ...,
"key_topics": [...]
},
"top_trending_coins": [
{"coin": "...", "sentiment": ..., "reason": "..."}
],
"sector_performance": [
{"sector": "L1/L2/DeFi/NFT/Meme", "sentiment": ...}
],
"hot_narratives": [...],
"risk_alerts": [...],
"whale_summary": "...",
"recommended_focus": [...]
}"""
}]
)
return response.choices[0].message.content
```
Best Practices
1. Crypto-Specific Considerations
- CT is highly volatile - sentiment can shift quickly
- Bot activity is prevalent - look for organic signals
- Influencer manipulation is common - verify across sources
2. Timing Matters
- US/EU overlap often sees highest activity
- Asian session can have different sentiment
- Weekend sentiment differs from weekdays
3. Filter for Quality
```python
# Focus on accounts with history, not fresh accounts pumping
"Focus on accounts older than 6 months with consistent posting history"
```
4. Watch for Coordinated Activity
```python
# Detect potential pump and dump schemes
"Flag any coordinated posting patterns or sudden volume spikes from new accounts"
```
Related Skills
xai-stock-sentiment- Stock analysisxai-x-search- Raw X searchxai-sentiment- General sentimentxai-financial-integration- Price data integration
References
- [xAI Agent Tools](https://x.ai/news/grok-4-1-fast/)
- [Crypto Sentiment Guide](https://docs.x.ai/cookbook)
More from this repository10
Performs comprehensive analysis of code, skills, processes, and data to extract actionable insights, identify patterns, and drive data-driven improvements.
Automates comprehensive installation and setup of Auto-Claude across Windows, macOS, Linux, and WSL with multi-platform support and dependency management.
Authenticates and configures xAI Grok API access using Twitter/X account credentials, enabling seamless integration with OpenAI-compatible SDK methods.
Retrieve and integrate xAI Grok sentiment with financial data APIs to generate comprehensive market insights and analysis.
Retrieves comprehensive financial market data including stocks, forex, crypto, and technical indicators using the Twelve Data API.
Automatically diagnoses and resolves Auto-Claude installation, configuration, and runtime issues across different platforms and environments.
Enables real-time Twitter/X searches using Grok API to extract insights, track trends, monitor accounts, and analyze social discussions.
Enables autonomous agents to search X, web, execute code, and analyze documents with server-side tool management.
Optimizes Claude AI performance by reducing token usage, managing API costs, and improving build speed through intelligent model and context selection.
Enables persistent, cross-session memory with semantic search using a graph-based knowledge system across multiple AI providers.