Prepare smarter for TCF Canada with your personal AI exam coach. Practice TCF-style exercises, improve your written and oral expression, get detailed corrections, identify your weaknesses and follow a personalized study plan based on your level and exam date.
Hands-on prompt engineering and LLM evaluation. Built around a diagnose-then-ship loop: forensic transcript critique ▎ that names the exact failure mode, paired with a fixer that produces complete, deployment-ready rewrites — not ▎ vague advice.
This skill combines ATS optimization frameworks, recruiter review methodologies, resume scoring techniques, keyword matching, job-description analysis, and interview preparation workflows. It helps job seekers identify weaknesses, improve ATS compatibility, close skill gaps, optimize resumes for specific roles, and prepare for interviews using practical, recruiter-focused recommendations and structured career improvement plans.
拥有20年招聘经验、审阅过数十万份简历的资深HR的实战判断框架，用于简历筛选评估与面试教练。适用两类场景：(1) 求职者请求"帮我看看这份简历""这份简历有什么问题""帮我准备面试""陪我模拟面试""这个面试问题该怎么回答"；(2) 招聘方/HR/面试官请求"帮我筛选这些简历""这个候选人怎么样""帮我设计面试题""这份简历有什么疑点/红旗"。只要用户提到简历诊断、简历评估、面试准备、模拟面试、候选人评估、面试题设计、识别简历造假/注水/跳槽风险等，都应主动使用此技能，即使用户没有明确说"用这个技能"。尤其适合科技/研发/技术类岗位，但招聘判断逻辑对通用岗位同样适用。
Know if your backtest is a real edge or overfit noise. Runs bar-permutation MCPT, Deflated Sharpe, PBO/CSCV, Hansen SPA, Romano-Wolf StepM, a stationary bootstrap and an out-of-sample split on your own returns — no market feed, no API keys.
Academic sanity-check with interactive HTML dashboard. Detects look-ahead bias, over-parameterization, and benchmarks against 10 canonical blueprints via animated SVG gauges and color-coded KPI cards. Parses natural language, code, or CSV uploads. Output auto-adapts (EN/ZH-TW/ZH-CN). Built on De Prado (2018). For students and strategy developers. Not financial advice.
A scan tells you what is wrong. This tells you what to do. Same engine as the ADA Website Risk Scanner — 14 WCAG 2.2 AA check families. But instead of a defect list, you get a work plan: findings grouped into batches, ordered by exposure reduced per hour of developer time, each with before/after code, effort estimate, required skill, and a verification step. Three phases. Quick wins first. A project manager can assign it as-is.
Built from hands-on Expo / React Native development workflows using AI coding agents. This skill focuses on reviewing AI work reports, spotting risks, and turning them into clear verification steps before keeping or continuing changes.
marketingskills/skills/ab-testing. Corey Haines`s expert-level skill. It checks detectable lift, traffic limits, safe metrics, QA risk, and locked decision rules before launch. When you provide baseline rate, MDE, power, and traffic, it runs Python sample-size math to estimate required sample size and test duration, so you avoid wasted traffic, broken tracking, peeking, and fake wins. Support Corey Haines on https://buymeacoffee.com/coreyhaines