| name | crypto-radar |
| description | 🛰️ Enterprise-grade multi-chain crypto market intelligence for Hermes Agent — tracks 49 tokens across 31 chains with 26 technical indicators, divergence detection, ADX trend filter, RSS news aggregation from 11 feeds, DeFiLlama on-chain metrics, WebSocket real-time prices, warm daemon for sub-50ms tool calls, SVG candlestick/dashboard charts, and XLSX/CSV/JSON/MD/HTML export. 8 full-spectrum agent tools for token scanning, signal generation, news analysis, chart rendering, daemon management, on-chain queries, and real-time price streams. |
| context | This is an enterprise-grade multi-chain crypto market intelligence plugin for Hermes Agent, providing comprehensive tools for token scanning, signal generation, news analysis, chart rendering, daemon management, on-chain queries, and real-time price streams. It tracks 49 tokens across 31 chains with 26 technical indicators, divergence detection, ADX trend filter, RSS news aggregation from 11 feeds, DeFiLlama on-chain metrics, WebSocket real-time prices, warm daemon for sub-50ms tool calls, SVG candlestick/dashboard charts, and XLSX/CSV/JSON/MD/HTML export. |
| argument-hint | crypto-radar <tool> [options] |
| metadata | {"keywords":["crypto","trading","binance","defi","signals","technical-analysis","hermes-plugin","market-intelligence","enterprise"],"name":"Hermes Crypto Radar","author":"Sam","version":"2.3.0"} |
| user-invocable | true |
| compatibility | {"hermes":">=0.1.0","node":">=22.0.0","uv":">=0.0.0"} |
| disable-model-invocation | false |
🛰️ Hermes Crypto Radar
Enterprise-grade multi-chain crypto market intelligence — Hermes Agent plugin
✨ Features
📊 49 tokens · 31 chains · 26 technical indicators
🧠 3-strategy signal engine with divergence detection + ADX trend filter
🤖 CatBoost ML direction classifier with SHAP explanations + ensemble voting
📰 11 RSS news feeds with relevance scoring + sentiment analysis
⛓️ DeFiLlama on-chain metrics (protocol TVL, chain TVL, DEX fees)
📈 SVG candlestick/dashboard charts with shared-svg.ts rendering engine
💾 XLSX/CSV/JSON/MD/HTML export with frozen headers + conditional formatting
🥇 Warm daemon for sub-50ms tool calls with TCP keep-alive
🔄 Concept drift detection with auto-retrain trigger (ADWIN/PageHinkley/KSWIN)
⚡ River online learning layer for real-time model updates
🔬 Backtesting engine, correlation matrix, candlestick pattern recognition
🛡️ Circuit breaker, rate limiter, log rotation, SHA-256 checksums
🔌 8 full-spectrum agent tools + ML API returning structured JSON for agent reasoning
🛠️ Tools (8 agent tools)
| Tool | Description |
|---|
crypto_radar_scan | 🛰️ Full market scan — auto-dynamic top-30 tokens by volume, 26 indicators, on-chain metrics |
crypto_radar_signals | 🚀 Composite trading signals from 3-strategy engine + divergence + ADX filter |
crypto_radar_news | 📰 11 RSS feeds with relevance scoring, sentiment, dedup, poison filtering |
crypto_radar_tokens | 📋 Query by chain, symbol, or ID — 49 tokens across 31 chains |
crypto_radar_chart | 📊 SVG candlestick/line/multi-panel dashboard with responsive viewBox |
crypto_radar_daemon | ⚙️ Start/stop/status warm daemon (<50ms cached responses) |
crypto_radar_onchain | ⛓️ DeFiLlama protocol TVL, chain TVL, DEX fees |
crypto_radar_ws | 🔌 Real-time WebSocket price streams on port 9878 |
📦 Installation
ML Pipeline Architecture
flowchart TB
subgraph Data["Data Layer"]
A[Klines<br/>Binance] --> B[Feature Engineering<br/>80+ features]
C[26 Indicators<br/>+ 12 TA indicators] --> B
D[Cross-Asset<br/>Funding Rate<br/>Order Book] --> B
E[Forward Returns] --> F[Label Generation<br/>Volatility-adjusted]
F --> G[Dataset Assembly<br/>Z-score normalization]
B --> G
end
subgraph Train["Training Pipeline"]
G --> H[Feature Selection<br/>SelectKBest MI]
H --> I[Correlation Filter<br/>>0.98 dropped]
I --> J[CatBoost Training<br/>GPU auto-detect]
J --> K[Optuna HPO<br/>TPE sampler]
J --> L[purgedcv CV<br/>Purge + embargo]
K --> M[Ensemble Voting<br/>N seeds → soft vote]
L --> M
M --> N[Calibration<br/>Isotonic Regression]
N --> O[SHAP Analysis<br/>Per-feature importance]
O --> P[MANIFEST.json<br/>Model registry]
end
subgraph Infer["Inference Pipeline"]
Q[Latest Klines] --> R[buildFeatures]
R --> S[Z-score Normalize]
S --> T{--explain?}
T -->|Yes| U[SHAP Explainer]
T -->|No| V[CatBoost Predict]
U --> V
V --> W[Prediction Result<br/>direction, confidence, explanation]
end
subgraph Online["Online Learning"]
W --> X[SQLite predictions]
X --> Y[River LogisticRegression<br/>AdaptiveStandardScaler]
Y --> Z[Streaming Accuracy<br/>partial_fit / metrics]
end
subgraph Drift["Drift Detection"]
X --> AA[ADWIN / PageHinkley / KSWIN]
AA --> AB[Drift Events<br/>SQLite drift_events]
AB --> AC{Auto-Retrain?}
AC -->|Drift + 1h cooldown| H
X --> AD[Calibration Monitor<br/>ECE per bucket]
end
subgraph API["API & CLI"]
P --> AE[GET /api/ml/status]
P --> AF[GET /api/ml/models]
AB --> AG[GET /api/ml/drift]
X --> AH[GET /api/ml/predictions]
AD --> AI[GET /api/ml/calibration]
Z --> AJ[GET /api/ml/online]
AK[CLI: ml train|predict|status|drift] --> Train
AK --> Infer
AK --> Drift
end
Linux / macOS (one-liner)
Linux / macOS (one-liner)
bash <(curl -fsSL https://raw.githubusercontent.com/ssdeanx/Hermes-Crypto-Radar/main/scripts/install.sh)
Windows (PowerShell)
powershell -c "irm https://raw.githubusercontent.com/ssdeanx/Hermes-Crypto-Radar/main/scripts/install.ps1 | iex"
Manual Hermes Agent install
git clone https://github.com/ssdeanx/Hermes-Crypto-Radar.git
cd Hermes-Crypto-Radar
npm install && npm run build
ln -sf "$PWD" ~/.hermes/plugins/crypto-radar
Via npm (standalone CLI)
npm install -g hermes-crypto-radar
crypto-radar scan
⏰ Cron Automation
The plugin ships with a production-ready collector script:
bash scripts/crypto-radar-collector.sh
node dist/cli.js scan --dynamic 30 --onchain --no-news --format json --quiet
For Hermes cron:
hermes cron create "0 */2 * * *" \
--script crypto-radar-collector.sh \
--no-agent \
--workdir /path/to/hermes-crypto-radar
📋 CLI Commands
crypto-radar scan
crypto-radar signals
crypto-radar news
crypto-radar tokens
crypto-radar chart SOL
crypto-radar daemon
crypto-radar onchain
crypto-radar health
crypto-radar backtest
crypto-radar search
crypto-radar benchmark
crypto-radar export
crypto-radar ml train
crypto-radar ml predict
crypto-radar ml status
crypto-radar ml drift
⚙️ Configuration
Edit radar.config.json or use RADAR__* environment variables:
| Variable | Default | Description |
|---|
RADAR__DATA_DIR | ~/.hermes/data/crypto-radar | Data/log directory |
RADAR__DAEMON_PORT | 9877 | Daemon HTTP port |
RADAR__WS_PORT | 9878 | WebSocket stream port |
RADAR__LOG_LEVEL | info | Log level (trace/debug/info/warn/error) |
RADAR__CACHE_TTL_MS | 300000 | Cache TTL in ms |
RADAR__LOG_RETENTION_DAYS | 30 | Auto-prune logs after N days |
RADAR__WEBHOOK_URL | — | Discord/Telegram webhook URL |
RADAR__STRATEGY_WEIGHTS | — | JSON strategy weight overrides |
RADAR__TIMEFRAME_WEIGHTS | — | JSON timeframe weight overrides |
📄 Included Files
hermes-crypto-radar-2.0.0.tar.gz
├── dist/ # Compiled TypeScript
├── plugin/ # Python Hermes bridge
├── plugin.yaml # Plugin metadata
├── package.json # npm package
├── README.md # Full documentation
├── CHANGELOG.md # Release history
├── SPEC.md # Architecture & design
├── LICENSE # MIT license
├── SECURITY.md # Vulnerability disclosure
├── main-banner.png # Project banner image
└── scripts/
├── install.sh # Linux/macOS one-liner installer
├── install.ps1 # Windows PowerShell installer
└── crypto-radar-collector.sh # Cron automation script
📃 License
MIT © Sam