Automate nightly retrospective analysis of WOLF strategy trading activity and generate improvement reports.
npx skills add https://github.com/Senpi-ai/senpi-skills --skill wolf-howl
Please help me install this Agent Skill. Skill: wolf-howl Source: https://github.com/Senpi-ai/senpi-skills/tree/main/wolf-howl Command: npx skills add https://github.com/Senpi-ai/senpi-skills --skill wolf-howl
Automates nightly retrospective analysis of all trades to identify actionable improvements for the WOLF autonomous trading strategy, reducing manual review time and surfacing data-driven insights.
Configure HOWL to run nightly and generate the memory/howl-YYYY-MM-DD.md report along with MEMORY.md updates.
High-intent search queries and answers about installing and using this skill.
Automate nightly trading analysis by running a scheduled retrospective over the last 24 hours of activity. This computes win rate, net PnL, fees, and holding-period buckets to deliver data-driven strategy optimization recommendations.
An autonomous trading strategy retrospective includes metrics such as win rate, gross and net PnL, fees (FDR), DSL tier performance, holding-period buckets, and regime signals to surface actionable improvement opportunities.
Set up nightly drift detection by configuring a scheduled cron job to execute the analysis workflow. It evaluates regime signals and feature interactions, writing a structured memory report and a concise summary for quick visibility.
Nightly trading analysis requires access to memory, DSL state, and strategy configuration to execute properly. These dependencies are necessary to compute performance metrics and generate accurate improvement recommendations.
The best way to generate daily trading performance reports automatically is through a structured workflow that updates memory files and writes a dated report. This reduces manual review time and surfaces data-driven insights.
Nightly trading analysis is designed for daily optimization scenarios without manual review. It automates retrospective analysis of all trades to identify actionable improvements, reducing manual review time significantly.
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