Trading Memory
Skill Verified ActiveDomain knowledge for AI trading memory — Outcome-Weighted Memory (OWM) architecture, 5 memory types, recall scoring, and behavioral analysis. Use when recording trades, recalling similar contexts, analyzing performance, or checking behavioral drift. Triggers on "record trade", "remember trade", "recall", "similar trades", "performance", "behavioral", "disposition", "affective state", "confidence".
To equip AI trading agents with a persistent, intelligent memory that learns from past trades to inform future decisions, improve performance, and meet regulatory documentation requirements.
Features
- Outcome-Weighted Memory (OWM) architecture
- Five distinct memory types (Episodic, Semantic, Procedural, Affective, Prospective)
- Recall scoring based on P&L, context similarity, recency, and confidence
- Automated trade recording and analysis
- Tamper-proof SHA-256 audit trail for regulatory compliance
Use Cases
- Recording every trade with full context for later analysis.
- Recalling similar past trading situations to inform current decisions.
- Analyzing trading performance per strategy and identifying behavioral patterns.
- Setting up trading plans with conditional triggers and risk parameters.
Non-Goals
- Executing trades or accessing user funds/wallets.
- Providing real-time market data feeds (though it uses market context).
- Replacing a core trading execution platform; it's a memory layer.
Installation
/plugin install tradememory-plugin@mnemox-ai-tradememory-protocolQuality Score
VerifiedTrust Signals
Similar Extensions
Trader Regime
100Detect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy
TradeMemory Protocol
100Domain knowledge for the Evolution Engine — LLM-powered autonomous strategy discovery from raw OHLCV data. Covers the generate-backtest-select-evolve loop, vectorized backtesting, out-of-sample validation, and strategy graduation. Use when discovering trading patterns, running backtests, evolving strategies, or reviewing evolution logs. Triggers on "evolve", "discover patterns", "backtest", "evolution", "strategy generation", "candidate strategy".
Risk Management
100Risk management domain knowledge for trading agents — affective state monitoring, position sizing, drawdown management, tilt detection, and behavioral guardrails. Use when checking risk before trades, managing drawdowns, detecting behavioral drift, or enforcing discipline. Triggers on "risk", "drawdown", "tilt", "position size", "lot size", "confidence", "revenge trading", "overtrading", "discipline".
Agentdb Memory Patterns
99Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Trader Signal
99Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction
Tradememory Bridge
99Bridge between Binance trading events and TradeMemory Protocol. Automatically journals trades, recalls similar past setups, detects behavioral biases, and provides outcome-weighted recall for AI trading agents. Use this skill after executing Binance spot trades to build persistent memory.