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SpartanLabsXyz
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simmer-tradejournal

Log Simmer trades with contextual metadata and generate calibration reports.

48|14|Updated Jan 10, 2026
Search Tags:#analytics#simulation#calibration#journal#pnl#trade#simmer
One-click install
npx skills add https://github.com/SpartanLabsXyz/simmer-sdk --skill simmer-tradejournal
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: simmer-tradejournal
Source: https://github.com/SpartanLabsXyz/simmer-sdk/tree/main/skills/tradejournal
Command: npx skills add https://github.com/SpartanLabsXyz/simmer-sdk --skill simmer-tradejournal

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Auto-log trades with context to enable outcome tracking and calibration, reducing manual logging and improving strategic visibility.

Core Features & Use Cases

  • Auto-sync trades from the Simmer API and store locally with outcomes
  • Attach contextual data to trades via log_trade(), including thesis and confidence
  • Generate calibration reports and export data for deeper analysis

Quick Start

Log a completed trade with log_trade() after executing a trade to attach context and begin calibration.

Frequently Asked Questions about simmer-tradejournal

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automatically log trades with context for outcome tracking?▼

You can automatically log trades with context by using the log_trade() function to attach thesis and confidence metadata, which enables outcome tracking and reduces manual data entry.

Can I sync my trades directly from the Simmer API?▼

Yes, you can sync trades directly from the Simmer API to store them locally with outcomes, enriching the contextual data needed for accurate calibration and analysis.

How do I generate calibration reports from my trade journal?▼

To generate calibration reports, log your trades with contextual metadata using log_trade(), and the system will track outcomes across sessions to produce strategic visibility reports.

What is the best way to attach thesis data to my trade logs?▼

The best way to attach thesis data to your trade logs is by executing log_trade() after a trade, which captures contextual metadata like confidence levels to improve your strategic edge.

Do I need local storage to track PnL across trading sessions?▼

Yes, local JSON storage is used to save your trades and outcomes, which works with API-synced data to track PnL and calibration across multiple trading sessions.

Can I export my trade journal data for deeper analysis?▼

Yes, you can export your locally stored trade journal data, including contextual metadata and outcomes, to perform deeper analysis and improve your trading insights.

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