File contents 📊 Sentiment Analyzer
K.I.T.'s Social Intelligence - Know what the market FEELS before it moves!
Features
🐦 Twitter/X Sentiment
Real-time crypto tweets analysis
Influencer tracking (Elon, CZ, Vitalik, etc.)
Hashtag volume monitoring
Viral tweet detection
🤖 Reddit Sentiment
r/wallstreetbets analysis
r/cryptocurrency monitoring
r/Bitcoin, r/ethereum tracking
Meme coin detection
FOMO/FUD scoring
📰 News Sentiment
Crypto news headlines
Bloomberg, Reuters, CoinDesk
Breaking news alerts
Regulatory news detection
😱 Fear & Greed Index
Alternative.me integration
Historical correlation analysis
Extreme fear = BUY signals
Extreme greed = SELL signals
📈 Social Volume
Mention volume tracking
Unusual activity detection
Pump group monitoring
Whale wallet tracking mentions
Usage
from sentiment_analyzer import SentimentEngine
engine = SentimentEngine()
# Get overall sentiment
sentiment = await engine.analyze(
symbol="BTC",
sources=["twitter", "reddit", "news"]
)
print(f"Overall: {sentiment.score:.2f}") # -1 to 1
print(f"Mood: {sentiment.mood}") # BULLISH/BEARISH/NEUTRAL
print(f"Fear & Greed: {sentiment.fear_greed}")
print(f"Social Volume: {sentiment.volume_change:+.1%}")
# Track specific influencer
alerts = await engine.track_influencer("elonmusk")
# Get trending topics
trending = await engine.get_trending(limit=10)
Sentiment Signals
Score
Interpretation
Action
> 0.7
Extreme Greed
Consider selling
0.3-0.7
Bullish
Hold/accumulate
-0.3-0.3
Neutral
Wait for signal
-0.7--0.3
Bearish
Reduce exposure
< -0.7
Extreme Fear
Consider buying
Configuration
sentiment_analyzer:
twitter:
api_key: ${TWITTER_API_KEY}
influencers:
- elonmusk
- caborek
- VitalikButerin
keywords:
- bitcoin
- crypto
- ethereum
reddit:
client_id: ${REDDIT_CLIENT_ID}
client_secret: ${REDDIT_CLIENT_SECRET}
subreddits:
- wallstreetbets
- cryptocurrency
- Bitcoin
news:
sources:
- coindesk
- cointelegraph
- bloomberg
alerts:
extreme_sentiment: true
influencer_tweets: true
unusual_volume: true
Dependencies
tweepy>=4.14.0
praw>=7.7.0
transformers>=4.35.0
nltk>=3.8.0
textblob>=0.17.0
1 --- 2 name: sentiment-analyzer 3 description: 📊 Sentiment Analyzer 4 --- 5 # 📊 Sentiment Analyzer 6 7 **K.I.T.'s Social Intelligence - Know what the market FEELS before it moves!** 8 9 ## Features 10 11 ### 🐦 Twitter/X Sentiment 12 - Real-time crypto tweets analysis 13 - Influencer tracking (Elon, CZ, Vitalik, etc.) 14 - Hashtag volume monitoring 15 - Viral tweet detection 16 17 ### 🤖 Reddit Sentiment 18 - r/wallstreetbets analysis 19 - r/cryptocurrency monitoring 20 - r/Bitcoin, r/ethereum tracking 21 - Meme coin detection 22 - FOMO/FUD scoring 23 24 ### 📰 News Sentiment 25 - Crypto news headlines 26 - Bloomberg, Reuters, CoinDesk 27 - Breaking news alerts 28 - Regulatory news detection 29 30 ### 😱 Fear & Greed Index 31 - Alternative.me integration 32 - Historical correlation analysis 33 - Extreme fear = BUY signals 34 - Extreme greed = SELL signals 35 36 ### 📈 Social Volume 37 - Mention volume tracking 38 - Unusual activity detection 39 - Pump group monitoring 40 - Whale wallet tracking mentions 41 42 ## Usage 43 44 ```python 45 from sentiment_analyzer import SentimentEngine 46 47 engine = SentimentEngine() 48 49 # Get overall sentiment 50 sentiment = await engine.analyze( 51 symbol="BTC", 52 sources=["twitter", "reddit", "news"] 53 ) 54 55 print(f"Overall: {sentiment.score:.2f}") # -1 to 1 56 print(f"Mood: {sentiment.mood}") # BULLISH/BEARISH/NEUTRAL 57 print(f"Fear & Greed: {sentiment.fear_greed}") 58 print(f"Social Volume: {sentiment.volume_change:+.1%}") 59 60 # Track specific influencer 61 alerts = await engine.track_influencer("elonmusk") 62 63 # Get trending topics 64 trending = await engine.get_trending(limit=10) 65 ``` 66 67 ## Sentiment Signals 68 69 | Score | Interpretation | Action | 70 |-------|----------------|--------| 71 | > 0.7 | Extreme Greed | Consider selling | 72 | 0.3-0.7 | Bullish | Hold/accumulate | 73 | -0.3-0.3 | Neutral | Wait for signal | 74 | -0.7--0.3 | Bearish | Reduce exposure | 75 | < -0.7 | Extreme Fear | Consider buying | 76 77 ## Configuration 78 79 ```yaml 80 sentiment_analyzer: 81 twitter: 82 api_key: ${TWITTER_API_KEY} 83 influencers: 84 - elonmusk 85 - caborek 86 - VitalikButerin 87 keywords: 88 - bitcoin 89 - crypto 90 - ethereum 91 92 reddit: 93 client_id: ${REDDIT_CLIENT_ID} 94 client_secret: ${REDDIT_CLIENT_SECRET} 95 subreddits: 96 - wallstreetbets 97 - cryptocurrency 98 - Bitcoin 99 100 news: 101 sources: 102 - coindesk 103 - cointelegraph 104 - bloomberg 105 106 alerts: 107 extreme_sentiment: true 108 influencer_tweets: true 109 unusual_volume: true 110 ``` 111 112 ## Dependencies 113 - tweepy>=4.14.0 114 - praw>=7.7.0 115 - transformers>=4.35.0 116 - nltk>=3.8.0 117 - textblob>=0.17.0
commit db8bae839b
Frequently asked questions How do I install the Sentiment Analyzer skill? Run npx skillmds@latest add signal-execution-labs/sentiment-analyzer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.
What does the Sentiment Analyzer skill do? 📊 Sentiment Analyzer It is listed under Coding & Dev Tools on SkillMD.
Is Sentiment Analyzer safe to use? This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.
Which AI agents work with Sentiment Analyzer? This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.
Is Sentiment Analyzer free to use? Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.
Who published Sentiment Analyzer? Signal-Execution-Labs (@signal-execution-labs) published this skill. Their other Agent Skills are listed on their SkillMD profile.
Signal-Execution-Labs