Slash Command

Analyze Sentiment

Analyze market sentiment from social media, news, and on-chain metrics

Type: Slash Command
Repository: jeremylongshore/tons-of-skills-marketplace
GitHub stars: 2.8k
License: MIT
Repo last updated: Sep 27, 2026
Source file: plugins/crypto/market-sentiment-analyzer/commands/analyze-sentiment.md

What Analyze Sentiment is

Analyze Sentiment is a slash command published in the jeremylongshore/tons-of-skills-marketplace repository on GitHub, which has about 2.8k stars. The repository describes itself as: “Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.”

A slash command is a reusable prompt saved as a markdown file and run by typing its name after a slash. In Claude Code, custom commands have been merged into skills: a file in .claude/commands/ and a skill folder in .claude/skills/ both create the same kind of command, and existing command files keep working.

Analyze Sentiment gives you a repeatable way to run the same instructions without retyping them, optionally with arguments.

How to install Analyze Sentiment

Claude Code

Download analyze-sentiment.md from the repository.
Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md.
Run it by typing / followed by its name.

Claude Cowork

Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it.
In Customize → Skills, click +, then upload the ZIP.
Run it from any task with / and the skill name.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from plugins/crypto/market-sentiment-analyzer/commands/analyze-sentiment.md, shared under the repository's MIT license. Read the full file on GitHub.

Comprehensive multi-source sentiment analysis system that aggregates data from social media platforms, news outlets, on-chain metrics, derivatives markets, and whale tracking to predict market movements and identify trading opportunities.

Overview

Market sentiment analysis combines quantitative on-chain data with qualitative social signals to measure the collective mood of market participants. This command provides a sophisticated sentiment aggregation framework that:

Monitors 6+ data sources including Twitter/X, Reddit, Telegram, Discord, news feeds, and blockchain metrics
Calculates Fear & Greed Index using weighted multi-factor analysis
Analyzes derivatives markets through funding rates and options sentiment
Tracks whale behavior via large holder movements and exchange flows
Correlates sentiment shifts with historical price action for predictive insights
Generates weighted sentiment scores with confidence intervals and statistical significance

The analyzer uses natural language processing (NLP), time-series analysis, and machine learning to identify sentiment extremes that often precede major price reversals, making it invaluable for contrarian trading strategies.

Data Sources & Weighting

Social Media Sentiment (35% weight)

Twitter/X Analysis (15%)

Real-time tweet monitoring for crypto-specific keywords and cashtags
Sentiment scoring using VADER and FinBERT NLP models
Influencer tracking with follower-weighted sentiment
Engagement metrics (likes, retweets, quote tweets)
Trending topics and hashtag velocity analysis

Reddit Sentiment (10%)

r/CryptoCurrency, r/Bitcoin, r/ethereum analysis
Post and comment sentiment with upvote weighting
Daily discussion thread analysis
Subreddit activity levels (posts per hour)
Cross-post momentum tracking

Telegram & Discord (10%)

Group message sentiment analysis
Active user count and engagement rate
Admin/moderator sentiment filtering
Message velocity and panic indicators
Voice chat activity monitoring

News & Media Sentiment (20% weight)

Mainstream Media Coverage

Automated news scraping from CoinDesk, CoinTelegraph, Bloomberg Crypto
Headline sentiment analysis with clickbait filtering
Source credibility scoring
Publication frequency tracking
Fear/uncertainty/doubt (FUD) detection

Regulatory News Impact

Government announcement tracking
SEC filing monitoring
Central bank statement analysis
Regulatory sentiment classification
Geographic regulatory heat maps

Derivatives Market Sentiment (25% weight)

Funding Rates Analysis (12%)

Perpetual futures funding rate tracking across exchanges
Historical funding rate comparison
Funding rate divergence alerts
Long/short ratio calculation
Liquidation cascade prediction

Options Market Sentiment (13%)

Put/Call ratio analysis for major strikes
Implied volatility skew interpretation
Options open interest distribution
Max pain price calculation
Gamma squeeze potential detection

Whale & Smart Money Tracking (15% weight)

Large Holder Movements

Whale wallet transaction monitoring (>$1M transfers)
Exchange deposit/withdrawal flow analysis
Cold wallet accumulation patterns
Smart money address tracking
Whale sentiment divergence from retail

Exchange Flow Analysis

Net flow (deposits minus withdrawals)
Exchange reserve levels
Miner selling pressure
OTC desk activity indicators
Stablecoin flow correlation

On-Chain Sentiment Indicators (5% weight)

Network Value Metrics

MVRV ratio (Market Value to Realized Value)
NVT ratio (Network Value to Transactions)
Spent Output Age analysis
Long-term holder behavior
Realized cap momentum

Fear & Greed Index Calculation

The Fear & Greed Index aggregates multiple data sources into a single 0-100 score:

Score Interpretation:

0-25: Extreme Fear (potential buying opportunity)
25-45: Fear (cautious sentiment)
45-55: Neutral (balanced market)
55-75: Greed (risk appetite increasing)
75-100: Extreme Greed (potential correction ahead)

Calculation Methodology:

Social Sentiment Component (35 points)

Twitter sentiment: 15 points (scaled -1 to +1 → 0 to 15)
Reddit sentiment: 10 points
Telegram/Discord: 10 points

Market Momentum Component (20 points)

Price volatility (25% of component)

Before you install

Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
Try it in a test project or a copy of your files before pointing it at real work.
Pin the version you tested, and review changes before updating.
Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Analyze Sentiment?

Analyze Sentiment is a slash command for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Analyze market sentiment from social media, news, and on-chain metrics

How do I install Analyze Sentiment in Claude Code?

Download analyze-sentiment.md from the repository. Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md. Run it by typing / followed by its name.

Can I use Analyze Sentiment in Claude Cowork?

Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it. In Customize → Skills, click +, then upload the ZIP. Run it from any task with / and the skill name.

Is Analyze Sentiment safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.