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trader-signal

Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction

Stars
56,726
Source
ruvnet/claude-flow
Updated
2026-05-31
Slug
ruvnet--claude-flow--trader-signal
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/ruvnet/claude-flow/HEAD/plugins/ruflo-neural-trader/skills/trader-signal/SKILL.md -o .claude/skills/trader-signal.md

Drops the SKILL.md into .claude/skills/trader-signal.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

Generate trading signals using neural-trader's anomaly detection engine.

Steps:

  1. Ensure neural-trader is available: npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-trader
  2. Scan for signals:
    npx neural-trader --signal scan --symbols <TICKERS>
    With a specific strategy:
    npx neural-trader --signal scan --strategy <name> --symbols <TICKERS>
  3. If --strategy specified, load strategy filters: mcp__claude-flow__memory_retrieve({ key: "strategy-NAME", namespace: "trading-strategies" })
  4. neural-trader classifies anomalies automatically:
    • spike (maxZ > 5): breakout — momentum entry or mean-reversion fade
    • drift (sustained high Z): trend forming — trend-following signal
    • flatline (low Z): consolidation — prepare for breakout
    • oscillation (alternating): range-bound — mean-reversion at extremes
    • pattern-break (multiple dims): regime change — close and reassess
    • cluster-outlier (>50% dims): multi-factor dislocation — arbitrage
  5. Use SONA for regime prediction: mcp__claude-flow__neural_predict({ input: "anomaly types: [DETECTED], scores: [SCORES]" })
  6. Search historical pattern matches: mcp__claude-flow__agentdb_pattern-search({ query: "ANOMALY_TYPE score RANGE", namespace: "trading-signals" })
  7. Present ranked signals: instrument, direction, confidence, anomaly type, entry/stop/target
  8. Store signals with a 24-hour TTL (intraday signals shouldn't pollute long-running memory; the MemoryConsolidator.sweepExpired() pass introduced in ADR-125 Phase 4 — shipped in @claude-flow/memory@3.0.0-alpha.18 — sweeps them out after they expire): mcp__claude-flow__memory_store({ key: "signal-TIMESTAMP", value: "SIGNALS_JSON", namespace: "trading-signals", expiresAt: Date.now() + 24 * 60 * 60 * 1000 })