skills.rest
phanTian2026
phanTian2026COMMUNITY
Explore all skills by this author →
GitHub

coin-quant-mentor-skill

Generate Pandas factors and audit backtests for cryptocurrency trading strategies.

Updated Apr 28, 2026
Search Tags:#risk-management#cryptocurrency#prompt-engineering#quantitative-trading#factor-generation#backtest-analysis#dual-persona
One-click install
npx skills add https://github.com/phanTian2026/mobiletrading --skill coin-quant-mentor-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: coin-quant-mentor-skill
Source: https://github.com/phanTian2026/mobiletrading/tree/main/yonghu%20trae/skills/coin-quant-mentor-skill
Command: npx skills add https://github.com/phanTian2026/mobiletrading --skill coin-quant-mentor-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cryptocurrency trading requires expert guidance for building robust, testable quantitative strategies and auditing backtest results. This Skill provides a dual-persona mentor to help you craft factor code, review backtests, and reason about risk in crypto markets.

Core Features & Use Cases

  • Factor Generation: generate executable Pandas factors with multi-asset support and built-in safety checks.
  • Backtest Analysis: perform deep backtest audits, compare metrics, and produce Markdown reports.
  • Consultation: explain concepts, provide actionable guidance, and adjust tone based on the current persona.

Quick Start

Request factor generation, backtest analysis, or consult instructions by switching personas with /mode nagging or /mode toxic.

Frequently Asked Questions about coin-quant-mentor-skill

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

FAQPage Schema
How do I generate executable Pandas factors for cryptocurrency quantitative trading?▼

Generate executable Pandas factors for cryptocurrency quantitative trading by requesting factor code creation. The mentor outputs multi-asset factor scripts with built-in safety checks for immediate backtesting integration.

What is backtest analysis and how does it audit crypto trading strategies?▼

Backtest analysis audits crypto trading strategies by deeply evaluating performance metrics and comparing results. It produces reproducible Markdown reports to help you identify weaknesses and validate quantitative strategy robustness.

Can I switch mentoring personas for crypto risk management consultation?▼

Yes, you can switch mentoring personas for crypto risk management consultation using /mode nagging or /mode toxic. This adjusts the mentor's tone to deliver actionable guidance and explain concepts based on your preference.

What is the best way to reason about risk in cryptocurrency quantitative trading?▼

The best way to reason about risk in cryptocurrency quantitative trading is through the dual-persona mentor's consultation feature. It provides risk-focused guidance and audits backtest results to ensure your factor strategies remain robust.

Does this quantitative trading mentor support multi-asset factor generation?▼

Yes, the quantitative trading mentor supports multi-asset factor generation. It crafts executable Pandas factor code specifically designed for multi-asset cryptocurrency markets with built-in safety checks for reproducible results.

Related Skills

Explore More Data & Analytics Skills→
hxhyyyhxhyyy

akshare

Aggregate financial market data into structured pandas DataFrames via akshare.

Community
Intermediate
20YN0420YN04

vnpy-export

Translate Vibe-Trading backtest strategies into executable vnpy CtaTemplate Python classes.

Community
Advanced
hxhyyyhxhyyy

onchain-analysis

Analyze public blockchain data to generate investment signals from network activity and valuation metrics.

Community
Advanced
kayzaakayzaa
5

Quant Engine

Run quantitative trading algorithms and backtest strategies on historical market data using Python.

Community
Advanced