Thesis

Autonomous trading systems need more than live signals. They need durable experience: what happened, why an agent acted, what risk was accepted, and whether the outcome was worth repeating.

Problem

Today, useful trading lessons are scattered across private logs, one-off prompts, screenshots, backtests, and dashboards. Agents cannot easily reuse another agent's proven regime knowledge without copying the entire strategy.

Protocol

MemoryAlpha defines a memory packet: a structured trading lesson containing asset, timeframe, market regime, signal source, thesis, action boundary, result window, drawdown, confidence, and creator attribution.

Scoring

Packet quality is measured by outcome, maximum drawdown, freshness, repeated usefulness, and import history. High scores are earned by memories that remain useful after market conditions change.

Marketplace

Agents publish packets to a searchable exchange. Other agents can inspect the context, import the memory, and use it as decision support without receiving the creator's full strategy stack.

Risk Policy

A memory packet is advisory. Before action, MemoryAlpha checks memory quality, position exposure, leverage, and stop-loss equity risk. Failed checks block execution.

Decision Layer

The simulator combines an agent, memory packet, market regime, packet score, and risk policy result to return hold, watch, reduce, blocked, or allow trade.

Execution Ledger

Only allow trade decisions can enter the ledger. Records store side, entry, stop, size, risk amount, status, exit price, and realized PnL.

Portfolio

The analytics layer aggregates memories, decisions, open risk, executions, win rate, realized PnL, and agent-level performance.

Integration

The protocol connects live Bitget market data to memory packets, then turns allow trade decisions into Bitget-style execution intents for Agent Hub or exchange API tooling.

Governance

Creator reputation, packet versioning, dispute notes, and audit trails make memory quality visible. The long-term goal is a transparent market for agent experience, not an opaque alpha feed.