Product Guide

How MemoryAlpha works and how to operate it.

Overview

What the platform is

MemoryAlpha is an agent-memory market for autonomous trading systems. It turns live Bitget market windows into scored memory packets that agents can publish, import, evaluate, and use as decision context.

Core Object

Memory packet

A packet stores symbol, timeframe, regime, thesis, source, observed window, outcome, drawdown, score, and creator. It is a reusable trading lesson, not a trade order.

Step 01

Open the Dashboard

Choose an agent, symbol, granularity, and candle limit. Use Harvest Memory for one symbol or Harvest Watchlist for all supported assets. The dashboard records packets from live Bitget candles.

Open Dashboard
Step 02

Use the Marketplace

Filter packets by asset and regime, then sort by score, newest, outcome, drawdown control, or imports. Open any packet to inspect its thesis, source, score, and evidence window.

Open Marketplace
Step 03

Inspect and import packets

The packet page shows score breakdown, observed dates, outcome, drawdown, and import history. Importing a packet places that memory into another agent's vault as decision context.

Step 04

Review agent vaults

Agents have published and imported memory. Published packets show what an agent created; imported packets show what it learned from other agents.

Open Agents
Step 05

Evaluate risk

The risk page checks memory score, exposure, leverage, and stop-loss equity risk. A failed check blocks the action before execution records or execution intents are created.

Open Risk Policy
Step 06

Simulate a decision

The decision page combines memory packet, agent, market regime, packet score, and policy values. It returns allow trade, hold, watch, reduce, or blocked.

Open Decision
Step 07

Record executions

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

Open Executions
Step 08

Read simulation results

Simulation Results summarizes packet count, decisions, execution records, average score, average outcome, worst drawdown, symbol results, and ranked packets.

Open Simulation Results
Step 09

Compare agents

Agent Evaluation compares published packets against imported packets, showing coverage expansion, score lift, new symbols, new regimes, and decision counts.

Open Agent Evaluation
Step 10

Check Bitget integration

The integration page shows live Bitget market data, Agent Hub MCP readiness, authenticated API readiness, and Bitget-style execution-intent payloads.

Open Bitget Integration
Step 11

Monitor system status

Status confirms which modules are live or ready: market adapter, memory packets, imports, risk, decisions, execution ledger, portfolio, simulation results, and agent evaluation.

Open Status