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trader-signal

Generate trading signals using neural-trader anomaly detection with Z-score scoring.

70.1k|8.4k|Updated Jun 2, 2025
Search Tags:#pattern matching#anomaly detection#trading signals#z-score#market scanning#neural-trader#regime prediction
One-click install
npx skills add https://github.com/ruvnet/claude-flow --skill trader-signal
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trader-signal
Source: https://github.com/ruvnet/claude-flow/tree/main/plugins/ruflo-neural-trader/skills/trader-signal
Command: npx skills add https://github.com/ruvnet/claude-flow --skill trader-signal

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires neural-trader.

What problem does it solve?

Identifying actionable market anomalies across multiple tickers requires manual statistical analysis and pattern matching. This Skill automates anomaly detection, classification, and signal ranking so traders get structured entry, stop, and target recommendations without building their own detection pipeline.

Core Features & Use Cases

  • Anomaly-Based Signal Scanning: Runs neural-trader's detection engine over specified symbols and classifies anomalies as spike, drift, flatline, oscillation, pattern-break, or cluster-outlier.
  • Strategy-Aware Filtering: Loads saved strategy filters from memory when a --strategy flag is provided, so scans respect predefined trading rules.
  • Neural Regime Prediction and Pattern Matching: Uses SONA neural prediction and AgentDB pattern search to score confidence and compare against historical signal patterns.
  • Use Case: Scan AAPL and MSFT with a momentum strategy, receive ranked signals with direction, confidence, anomaly type, and entry/stop/target levels, then store them with a 24-hour TTL for intraday review.

Quick Start

Scan AAPL and MSFT for trading signals using the momentum strategy and rank the results by confidence.

Frequently Asked Questions about trader-signal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate trading signals with neural-trader?▼

Run npx neural-trader --signal scan --symbols followed by comma-separated tickers. Add --strategy NAME to apply saved strategy filters loaded from memory before scanning.

What anomaly types does the signal scan detect?▼

The engine classifies anomalies as spike, drift, flatline, oscillation, pattern-break, or cluster-outlier based on Z-score behavior. Each type maps to a trading interpretation such as momentum entry, trend-following, or mean-reversion.

How do I install neural-trader if it is missing?▼

Run npm install --ignore-scripts neural-trader if npm ls shows it is not installed. The Skill checks availability first and installs only when needed.

Why are stored trading signals given a 24-hour TTL?▼

Intraday signals lose relevance quickly, so they are stored with a 24-hour expiry. The memory consolidator sweeps expired entries automatically, preventing stale signals from polluting long-term memory.

Can I use historical patterns to validate new signals?▼

Yes, the AgentDB pattern-search tool queries the trading-signals namespace for past anomalies matching the detected type and score range. This provides historical context for confidence ranking.

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