COMPREHENSIVE_TEST_GUIDE.md

Comprehensive Token Metrics Plugin Test Guide

🧪 Complete Endpoint Testing - All 17 Endpoints

📋 Core Data Endpoints (Direct API Access)

1. Tokens List (getTokens)

npm run example:tokens

What it does: Get list of all supported cryptocurrencies with their TOKEN_IDs Use case: Find token IDs for other API calls

2. Top Market Cap Tokens (getTopMarketCapTokens)

npm run example:top-market-cap

What it does: Get top cryptocurrencies by market capitalization Use case: Identify market leaders and trending tokens

3. Price Data (getPriceData)

npm run example:price-data

What it does: Get current prices for specific token IDs Use case: Real-time price monitoring

4. Trader Grades (getTraderGrades)

npm run example:trader-grades

What it does: AI-generated trading scores for tokens Use case: Short-term trading decisions

5. Investor Grades (getInvestorGrades)

npm run example:investor-grades

What it does: Long-term investment ratings Use case: Portfolio building and investment decisions

6. Market Metrics (getMarketMetrics)

npm run example:market-metrics

What it does: Overall market indicators and trends Use case: Market timing and macro analysis

7. Quantmetrics (getQuantmetrics)

npm run example:quantmetrics

What it does: Quantitative analysis and metrics Use case: Advanced technical analysis

8. Hourly OHLCV (getHourlyOhlcv)

npm run example:hourly-ohlcv

What it does: Hourly price data (Open, High, Low, Close, Volume) Use case: Short-term technical analysis

9. Daily OHLCV (getDailyOhlcv)

npm run example:daily-ohlcv

What it does: Daily price data for longer-term analysis Use case: Long-term trend analysis

10. AI Reports (getAiReports)

npm run example:ai-reports

What it does: Comprehensive AI-generated analysis reports Use case: Deep fundamental analysis

11. Crypto Investors (getCryptoInvestors)

npm run example:crypto-investors

What it does: Institutional investor data and insights Use case: Following smart money

12. Resistance/Support (getResistanceSupport)

npm run example:resistance-support

What it does: Technical analysis support and resistance levels Use case: Entry/exit point identification

13. Trading Signals (getTradingSignals)

npm run example:trading-signals

What it does: AI-generated buy/sell recommendations Use case: Automated trading decisions

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🚀 New Advanced Endpoints (Chat Interface + Direct)

14. Token Metrics AI Chat (getTokenMetricsAi)

npm run example:tokenmetrics-ai

Chat prompts:

• "What is the next 100x coin?"
• "How does DeFi work?"
• "Should I invest in Bitcoin?"
• "AI explain blockchain technology"

15. Sentiment Analysis (getSentiments)

npm run example:sentiments

Chat prompts:

• "market sentiment"
• "sentiment analysis"
• "social media sentiment"
• "twitter sentiment"

16. Scenario Analysis (getScenarioAnalysis)

npm run example:scenario-analysis

Chat prompts:

• "price prediction"
• "scenario analysis"
• "bitcoin price scenarios"
• "price forecast"

17. Correlation Analysis (getCorrelation)

npm run example:correlation

Chat prompts:

• "correlations"
• "portfolio correlations"
• "diversification analysis"
• "token relationships"

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🎯 Quick Test Sequence

Method 1: Individual Examples (All 17)

# Core data endpoints
npm run example:tokens
npm run example:top-market-cap
npm run example:price-data
npm run example:trader-grades
npm run example:investor-grades
npm run example:market-metrics
npm run example:quantmetrics
npm run example:hourly-ohlcv
npm run example:daily-ohlcv
npm run example:ai-reports
npm run example:crypto-investors
npm run example:resistance-support
npm run example:trading-signals

# New advanced endpoints
npm run example:tokenmetrics-ai
npm run example:sentiments
npm run example:scenario-analysis
npm run example:correlation

Method 2: Interactive Chat Interface

npm run chat

Then test these prompts in order:

1. Basic AI Chat: "What is Bitcoin?"
2. Trading Signals: "trading signals"
3. Sentiment: "market sentiment"
4. Price Prediction: "bitcoin price scenarios"
5. Correlations: "portfolio correlations"
6. Market Overview: "market overview"

Method 3: Automated Test Suite

# Run all tests
npm run test:all

# Individual test suites
npm run test:individual
npm run test:integration

Method 4: Demo Scenarios

# Trading bot simulation
npm run demo:trading-bot

# Research agent simulation
npm run demo:research-agent

# New endpoints showcase
npm run demo:new-endpoints

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📊 Expected Results for Each Endpoint

Tokens List:

• List of 50+ cryptocurrencies
• TOKEN_ID, name, symbol, category
• Used to find IDs for other calls

Top Market Cap:

• Top 10-100 tokens by market cap
• Current rankings and values
• Market leaders identification

Price Data:

• Real-time prices for specified tokens
• Current market values
• Price change indicators

Trader/Investor Grades:

• AI scores (0-100)
• Buy/sell/hold recommendations
• Risk assessments

Trading Signals:

• Buy/sell signals with strength
• AI-generated recommendations
• Signal confidence levels

Sentiment Analysis:

• Twitter, Reddit, News sentiment
• Sentiment scores and summaries
• Social media insights

Scenario Analysis:

• Multiple timeframe predictions
• Bear/base/bull scenarios
• ROI calculations and insights

Correlations:

• Token relationship analysis
• Portfolio diversification insights
• Risk management data

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✅ Success Indicators

For each test, look for:

• ✅ No errors in API calls
• ✅ Real-time data with current timestamps
• ✅ Proper formatting (tables, charts, colors)
• ✅ Correct endpoint URLs in logs
• ✅ Rate limiting working (no 429 errors)
• ✅ Data completeness (all expected fields)

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🚀 Quick Start Testing

Start here for fastest comprehensive test:

# 1. Test basic functionality
npm run example:tokens

# 2. Test price data
npm run example:price-data

# 3. Test trading features
npm run example:trading-signals

# 4. Test new advanced features
npm run chat
# Then type: "trading signals"
# Then type: "market sentiment"
# Then type: "bitcoin price scenarios"

This will verify all core functionality is working correctly!