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/trader-signal

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

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claude-flow
67k200 skills157 agents194 commands1 MCP
Install
$ npx -y skills add ruvnet/ruflo --skill trader-signal --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/trader-signal

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

SKILL.md

trader-signal.SKILL.md
name: trader-signal
description: Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction
allowed-tools: Bash Read mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_retrieve mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_delete mcp__plugin_ruflo-core_ruflo__neural_predict mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search
argument-hint: "[--strategy NAME] [--symbols AAPL,MSFT]"

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__plugin_ruflo-core_ruflo__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__plugin_ruflo-core_ruflo__neural_predict({ input: "anomaly types: [DETECTED], scores: [SCORES]" })` 6. Search historical pattern matches: `mcp__plugin_ruflo-core_ruflo__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__plugin_ruflo-core_ruflo__memory_store({ key: "signal-TIMESTAMP", value: "SIGNALS_JSON", namespace: "trading-signals", expiresAt: Date.now() + 24 * 60 * 60 * 1000 })`

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