You built a simple AI agent in Part 1 that summarizes a text file. Now let's take everything you learned and build something that actually helps with your career: a CV & Cover Letter Agent that reads your experience, analyzes a job description, rewrites your CV with quantified impact, and generates a polished cover letter — all as a single reusable command.
You started with browser-based AI (copy-paste, re-type, hope for the best). Now we are building an AI that does work for you, in your project, with your tools.
This is Part 2 of a two-part series. If you missed Part 1, it covered the fundamentals: what an AI coding agent is, why OpenCode beats the alternatives, multi-model via OpenRouter, and how to write your first command with predictable output.
cv_cover_letter_agent/
├── .opencode/
│ └── commands/
│ └── build_cv_coverletter.md ← the main command (4-step workflow)
├── inputs/
│ ├── experience.md ← your raw career data
│ └── jd.md ← job description to match against
├── playbooks/
│ ├── cv_analysis.md ← CV rules & bullet formula
│ ├── cover_letter_analysis.md ← cover letter 4-layer structure
│ ├── cv_template.typ ← CV header template
│ └── cv_body.typ ← CV body template
├── outputs/ ← generated files go here
└── README.md
inputs/experience.md — Your unpolished career history, exactly as it appears in your CV. The agent cleans it up and transforms it into professional content. Don't polish it yourself — let the AI do that work.
Personal Details:
Name: Tony Cheung
Phone: +852 9123 4567
Email: [email protected]
LinkedIn: linkedin.com/in/tonycheung
GitHub: github.com/tonycheung
Location: Hong Kong (Right to work in HK, open to relocation)
Education:
MSc Industrial Engineering & Decision Analytics, HK Top University (expected 2026) — top 5%
BSc Data Science, HK Top University (2023) — First Class Honors, top 3 students
Work Experience:
Data Analytics Intern, TechFlow Solutions (Jun 2023 - Sep 2023)
- Built automated dashboards in Python (Plotly/Dash) for supply chain KPIs, reducing reporting time from 8 hours to 30 minutes weekly
- Analyzed customer churn patterns across 5,000+ users and identified retention factors that saved $120K annually
- Collaborated with 3 product teams to integrate ML recommendations into dashboard workflows
Operations Analytics Intern, Global Logistics Corp (Jan 2023 - Apr 2023)
- Optimized route planning for 80+ delivery routes using Python optimization algorithms, reducing fuel costs by 18%
- Designed A/B testing framework for warehouse slotting, increasing picking efficiency by 22%
- Presented findings to Director level, leading to $250K process improvement initiative
Projects:
Capstone Project: Demand Forecasting with LLM-Powered Feature Engineering
- Developed a time-series forecasting model using XGBoost and LLM-extracted features from unstructured demand notes
- Achieved 14% lower MAPE compared to baseline ARIMA on 10K+ SKU dataset
- Deployed model to cloud function serving 500+ daily predictions
Supply Chain Optimization - HK Top University Supply Chain Course
- Modeled facility location problem for regional distribution network using Gurobi and Python
- Recommended 3 facility closures and 2 new sites, saving $2.1M annually in fixed costs
- Built sensitivity analysis for demand growth scenarios (5%, 10%, 15%)
Data Visualization Dashboard — HK Top University Career Services
- Created interactive Tableau dashboard tracking 200+ student internship outcomes and salary progression
- Automated ETL pipeline using Python (Pandas) to clean and merge data from 5 university systems
- Dashboard adopted by career office for annual report — reduced manual reporting time by 75%
Skills:
Programming: Python (Pandas, NumPy, Scikit-learn, XGBoost, PyTorch), SQL
Data Science: Machine Learning, Time Series Forecasting, A/B Testing, Optimization
Visualization: Tableau, Power BI, Plotly, Dash
Tools: Gurobi, Git, AWS (S3, EC2, SageMaker), Docker, Airflow
Languages: Fluent English and Cantonese (Written & Verbal), Conversational Mandarin
Honors & Awards:
Dean's List — HK Top University (Fall 2021, Spring 2022, Fall 2022, Spring 2023)
HK Top University Data Science Competition — 1st Place (2023)
MSc Scholarship — HK Top University (2025)
inputs/jd.md — Copy-paste the exact job description from the posting. The agent's entire value is in understanding this document and extracting what's truly important.
Junior Data Scientist (Welcome Fresh Graduate)
Top Retail Company · Hong Kong, Hong Kong SAR (On-site)
About the job:
Top Retail Company is an internationally renowned luxury department store with over 175 years of success, delivering an exceptional and eclectic product curation with dynamic Asian spirit and values. As the Data Scientist, you will be part of the team leveraging machine learning and statistical analysis to develop data-driven solutions and improve business decision-making.
The Role:
- Mine, manipulate and perform statistical analysis on multiple data sets to build scalable enterprise analytics solutions
- Select features, build, and optimize classifiers using various machine learning techniques
- Applies advanced statistical and machine learning techniques to build, maintain, and improve on multiple real-time decision systems
- Generate and validate hypotheses with variety of testing methods (A/B, multi-variate) to measure the impact of ongoing campaigns and retail initiatives
The Ideal Candidate:
- Bachelors / Master's Degree in relevant field (i.e. Mathematics, Statistics, Computer Science, Business Analytics, Econometrics)
- Fresh graduates are welcome to apply
- Basic knowledge on programming language such as Python or SQL to manipulate data and draw insights from large data sets
- Must have exposure in statistical concepts, such as distributions, hypothesis testing and linear regression is preferred
- Exposure in basic machine learning techniques including clustering, decision trees including knowing the mechanism behind them and real-world advantages/drawbacks
- Optional exposure in basics of CNN and RNN
- Proficient in English
Playbooks are external rule files that separate what the AI should do from how it does it. Think of them as the AI's "persona" and "rulebook":
Why playbooks matter:
playbooks/cv_analysis.md — The CV writing rules and formulas: