TradeMemory
Skill Verified ActiveCompliance-grade decision audit trail for AI trading agents. Records every trading decision with full context (conditions, filters, indicators, risk state), SHA-256 tamper detection, and structured export for MiFID II / EU AI Act readiness. Works alongside Binance Spot, Futures, and Web3 skills — they execute trades, TradeMemory records why.
To provide AI trading agents with a compliance-grade, tamper-evident audit trail of every trading decision, fulfilling regulatory requirements and enabling better risk management and decision analysis.
Features
- Records full trading decision context
- SHA-256 tamper detection for records
- Structured export for regulatory compliance (MiFID II, EU AI Act)
- Local, secure operation with no external data calls
- Integration with execution skills (e.g., Binance)
Use Cases
- Auditing AI trading decisions for regulatory compliance
- Analyzing past trading performance and decision-making processes
- Implementing pre-trade checklists to ensure discipline
- Recalling past trade outcomes to inform future decisions
Non-Goals
- Executing trades or managing funds
- Accessing user API keys or wallets
- Sending data to third-party services
- Replacing execution-based trading skills
Workflow
- AI agent makes a trading decision.
- Agent calls TradeMemory to record decision context.
- TradeMemory stores the record with a SHA-256 hash.
- Later, retrieve records via API/MCP for audit or analysis.
- Verify record integrity using the stored hash.
Practices
- Compliance
- Security
- Decision Auditing
- AI Agent Memory
Prerequisites
- Python 3.8+
- pip package manager
Installation
npx skills add mnemox-ai/tradememory-protocolRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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