Structured 10-step diagnostic for go/no-go feature evaluation in production ML pipelines. Covers outcome gradient, coverage gaps, entropy/gain ratio, conditional MI, incremental CV AUC, and 9-point temporal safety. Claude Code skill.
npx skills add wan-huiyan/ml-feature-evaluatorStructured 10-step diagnostic for go/no-go feature evaluation in production ML pipelines. Covers outcome gradient, coverage gaps, entropy/gain ratio, conditional MI, incremental CV AUC, and 9-point temporal safety. Claude Code skill.
Analyze Claude Code’s BUDDY pet system from leaked source, listing all 18 ASCII pets, render logic, and system details
Samuel v2 — Rails for AI coding assistants. Thin framework + plugin loader, agent-agnostic via AGENTS.md, three-tier plugin model (skill/WASM/OCI), TOON-encoded runtime, methodology hooks.
Connect AI agents to MATLAB with expert workflows, idiomatic code, testing, and error handling for faster engineering and science tasks
Convert any Claude skill into a ready-to-use Codex skill — automatically. Search by name, fetch, transform, validate, and install in one command.
由于本人在UESTC SICE读的三年本科写了无数个MATLAB实验报告，终于忍无可无决定实现自动化工作流，这是一下午捣鼓出的小玩意，希望大家能学会使用agent不要再手搓没有用的通信实验报告了。。。
Comprehensive guide for FinLab quantitative trading package across global stock markets (TW, US, KR, JP, HK; both single-name equities and ETFs/funds). Use when working with trading strategies, backtesting, stock data, FinLabDataFrame, factor analysis, stock selection, or when the user mentions FinLab, trading, quant trading, US equity, S&P 500 / NASDAQ 100, SPY / QQQ, sector or leveraged ETFs, ETF rotation, 美股, or stock market analysis. Includes data access, strategy development, backtesting workflows, best practices, and US-market specifics (data availability map, filing-date-aligned quarterly fundamentals, US universe construction, USMarket vs. USFundMarket defaults, and ETF backtesting).