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TradeMemory Protocol

Skill Verified Active
Part of:Tradememory

Domain 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".

Purpose

To equip AI trading agents with persistent memory and an audit trail, enhancing decision-making, compliance, and risk management.

Features

  • Trade recall with outcome-weighted scoring
  • SHA-256 tamper-proof audit trail for all decisions
  • Behavioral analysis and risk detection (drawdown, streaks)
  • Multi-factor pre-trade legitimacy checks
  • Support for any market, broker, or AI platform

Use Cases

  • Before trading: recall past similar conditions and outcomes
  • After trading: record trade details and outcomes automatically
  • Compliance: provide tamper-proof audit trails for regulators
  • Risk management: detect losing streaks and trigger stop-loss conditions

Non-Goals

  • Executing trades or accessing user funds
  • Directly optimizing trading strategy parameters
  • Replacing the core AI agent's decision-making logic
  • Performing real-time market analysis or charting

Practices

  • Memory Management
  • Audit Trail Generation
  • Risk Management
  • AI Compliance

Prerequisites

  • Python 3.8+
  • ANTHROPIC_API_KEY (for integrated LLM functionalities)
  • Claude Code or Claude Desktop environment for integration

Installation

/plugin install tradememory-plugin@mnemox-ai-tradememory-protocol

Quality Score

Verified
100 /100
Analyzed about 15 hours ago

Trust Signals

Last commitabout 1 month ago
Stars877
LicenseMIT
Status
View Source

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