/record-trade
Record a completed trade into all memory layers with full context
$ npx -y skills add mnemox-ai/tradememory-protocol --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/record-trade
Context preview
What this command does when you run it.
Record a completed trade into all memory layers with full context
Command definition
record-trade.mddescription: Record a completed trade into all memory layers with full context
argument-hint: "[symbol] [direction] [entry] [exit] [pnl]"
Record Trade
Store a completed trade into TradeMemory with full context. This writes to all 5 OWM memory layers (episodic, semantic, procedural, affective, prospective) and updates behavioral baselines.
Workflow
Step 1: Gather Trade Details
If trade details are provided in the argument, parse them. Otherwise ask for:
- **Symbol**: e.g., XAUUSD, BTCUSDT, EURUSD
- **Direction**: long or short
- **Entry price** and **Exit price**
- **Lot size** (optional, defaults to strategy default)
- **P&L** in dollars
Step 2: Gather Context
Ask for or infer:
- **Strategy**: Which strategy triggered this trade (e.g., VolBreakout, IntradayMomentum)
- **Market context**: Session (London/NY/Asian), volatility regime, trend state
- **Reflection**: Why did you enter? What was the signal? Would you take it again?
- **Confidence**: 0.0-1.0, how confident were you at entry?
Step 3: Store via MCP
Use the `remember_trade` MCP tool to store across all OWM layers:
remember_trade({
symbol, direction, entry_price, exit_price, pnl,
strategy, lot_size, market_context, reflection, confidence
})This automatically: 1. Creates an episodic memory (the raw trade event) 2. Updates semantic memory (strategy knowledge base) 3. Adjusts procedural memory (hold times, lot sizing patterns) 4. Updates affective state (confidence, drawdown, streak tracking) 5. Evaluates active prospective plans
Step 4: Confirm and Summarize
Report back:
- Trade stored successfully
- Updated affective state (new confidence level, streak)
- Any active trading plans that were affected
- Similar past trades (top 3 by OWM score) for quick comparison
Example
User: /record-trade XAUUSD long 5180 5210 +$150
Read more
description: Record a completed trade into all memory layers with full context argument-hint: "[symbol] [direction] [entry] [exit] [pnl]"
Record Trade
Store a completed trade into TradeMemory with full context. This writes to all 5 OWM memory layers (episodic, semantic, procedural, affective, prospective) and updates behavioral baselines.
Workflow
Step 1: Gather Trade Details
If trade details are provided in the argument, parse them. Otherwise ask for:
- **Symbol**: e.g., XAUUSD, BTCUSDT, EURUSD
- **Direction**: long or short
- **Entry price** and **Exit price**
- **Lot size** (optional, defaults to strategy default)
- **P&L** in dollars
Step 2: Gather Context
Ask for or infer:
- **Strategy**: Which strategy triggered this trade (e.g., VolBreakout, IntradayMomentum)
- **Market context**: Session (London/NY/Asian), volatility regime, trend state
- **Reflection**: Why did you enter? What was the signal? Would you take it again?
- **Confidence**: 0.0-1.0, how confident were you at entry?
Step 3: Store via MCP
Use the `remember_trade` MCP tool to store across all OWM layers:
remember_trade({
symbol, direction, entry_price, exit_price, pnl,
strategy, lot_size, market_context, reflection, confidence
})This automatically: 1. Creates an episodic memory (the raw trade event) 2. Updates semantic memory (strategy knowledge base) 3. Adjusts procedural memory (hold times, lot sizing patterns) 4. Updates affective state (confidence, drawdown, streak tracking) 5. Evaluates active prospective plans
Step 4: Confirm and Summarize
Report back:
- Trade stored successfully
- Updated affective state (new confidence level, streak)
- Any active trading plans that were affected
- Similar past trades (top 3 by OWM score) for quick comparison
Example
User: /record-trade XAUUSD long 5180 5210 +$150
Decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, tamper-evident SHA-256 chain with RFC 3161 anchoring, 20 MCP tools.
Other commands on tradememory-protocol.
- /daily-review
Run a daily reflection on recent trades and behavioral patterns
Open command - /evolve
Run the Evolution Engine to discover and validate trading strategies
Open command - /performance
Generate a strategy performance report with key metrics
Open command - /recall
Recall similar past trades using outcome-weighted memory
Open command

