cveasy 0.11.0

CLI tool to manage resume data and generate customized resumes for job applications

make-cveasy

Managing your resume in a single document and making endless copies to customize it for each job application is painful. Instead of juggling multiple versions, cveasy lets you maintain a single source of truth for your experiences and skills, then automatically generate and optimize customized resumes for any job application using git version control, keyword matching, and AI.

Features

• Project-based structure: Manage all your resume data in a single Git-friendly project
• Relationship tracking: Link skills and stories to experiences via frontmatter metadata
• AI-powered generation: Generate customized resumes using OpenAI, Anthropic, or OpenRouter
• Job application management: Track multiple job applications with custom resumes
• Quality checks: Keyword and skills matching with LLM comparison for resume optimization
• Iterative improvement: Update resumes based on check reports
• Export capabilities: Export resumes to PDF or Word documents
• Resume import: Import resume data from existing PDF or DOCX files using AI parsing
• Job description scraping: Automatically extract job details from URLs
• Token usage tracking: Monitor AI API usage with detailed token metrics

Getting Started

Install cveasy from PyPI using pip:

pip install cveasy

Verify the installation:

cveasy --help

This installs the cveasy CLI tool, which provides commands to manage your resume data and generate customized resumes for job applications. See the Quick Start section below to begin using the tool.

Quick Start

1. Initialize a Project

Create a new CVEasy project:

## Generate you resume repository
cveasy init -n my-resume

## Navigate to the root of your resume repository
cd my-resume

This creates a project directory with organized subdirectories for skills, experiences, stories, links, projects, education, applications, and resume files. See Project Structure for details.

2. Configure AI Provider

Configure your AI provider using the interactive command:

cveasy config

Or manually: copy .env.example to .env and edit it with your API keys. See Configuration for details.

3. Add Your Resume Data

Import from an existing resume (recommended):

cveasy import -f path/to/your/resume.pdf

Or add data manually using cveasy add commands. See Commands for all available options.

4. Generate and Optimize Resumes

# General resume (uses all your data)
cveasy generate

# Customized for a job application
cveasy generate --application software-engineer-20260125

# Check resume quality against job description
cveasy check --application software-engineer-20260125

# Update resume based on check report
cveasy generate --application software-engineer-20260125 --update

# Export to PDF or Word
cveasy export --application software-engineer-20260125 --format pdf

See Commands for detailed options and usage.

Project Structure

my-resume/
├── bio.md                 # Your name and location
├── skills/                # Your skills and competencies
│   └── python-{hash}.md
├── experiences/           # Work experience and positions
│   └── senior-software-engineer-{hash}.md
├── stories/              # Success stories and achievements
│   └── led-migration-to-microservices-{hash}.md
├── links/                # Professional links (LinkedIn, GitHub, etc.)
│   └── linkedin-{hash}.md
├── projects/             # Personal and professional projects
│   └── e-commerce-platform-{hash}.md
├── education/            # Educational background and credentials
│   └── bachelor-of-science-in-computer-science-{hash}.md
├── applications/         # Job applications with customized resumes
│   └── software-engineer-20260125/
│       ├── job-description.md
│       ├── resume.md
│       └── check-report.md
├── resume/               # General resume files
│   └── resume-20260125.md
├── .env                  # Your API keys (not in git)
├── .env.example          # Example configuration
└── README.md             # Project documentation

File Naming and Slugs

All resume data files (skills, experiences, stories, links, projects, education) are named using a slug attribute. The slug is a URL-safe string that:

• Converts the name/title to lowercase
• Replaces spaces with hyphens
• Appends a 6-character random hexadecimal hash at the end

For example:

• A skill named "Python Programming" might be saved as python-programming-a1b2c3.md
• An experience titled "Senior Software Engineer" might be saved as senior-software-engineer-d4e5f6.md

The slug is automatically generated when you create a new entry and is stored in the frontmatter of each markdown file. This ensures:

• Unique filenames: Even if two entries have similar names, they'll have different file names
• URL-safe: Slugs are safe to use in URLs and file systems
• Backward compatibility: Existing files without slugs will still load correctly, and slugs will be generated automatically

Note: The bio.md file uses a fixed filename and doesn't follow the slug naming pattern, though it still has a slug attribute stored in its frontmatter.

Commands

cveasy config

Configure CVEasy environment variables interactively.

Options:

• --project <path>: Project directory path (optional)

Examples:

cveasy config
cveasy config --project /path/to/project

Prompts you through setting up environment variables and saves them to .env in your project root.

cveasy init

Initialize a new CVEasy project.

Options:

• -n, --name <name>: Name of the project directory (default: my-cveasy-resume)
• --project <path>: Path where to create the project directory (optional)

Examples:

cveasy init
cveasy init -n my-resume
cveasy init --name professional-resume
cveasy init -n my-resume --project /path/to/projects

Creates a project directory with required subdirectories, initializes a git repository, and sets up configuration files.

cveasy add

Add resume data entries. All subcommands support the --project <path> flag.

cveasy add bio

Add or update your bio information (name and location).

cveasy add bio --name "Your Name" [--location "City, State"]

cveasy add skill

Add a new skill entry.

cveasy add skill --name "Python"

After creation, edit the file to add category, years of experience, proficiency level, and description.

cveasy add experience

Add a new work experience entry.

cveasy add experience --name "Senior Software Engineer"

After creation, edit the file to add organization, dates, location, and description.

cveasy add story

Add a new success story or achievement.

cveasy add story --name "Led Migration to Microservices"

After creation, edit the file to add context, outcome, and detailed description.

cveasy add link

Add a professional link (LinkedIn, GitHub, portfolio, etc.).

cveasy add link --name "LinkedIn" --description "Professional profile" --url "https://linkedin.com/in/username"

Required flags:

• --name: Link name
• --description: Link description
• --url: Link URL

cveasy add project

Add a new project entry.

cveasy add project --name "E-commerce Platform" --description "Full-stack application" [--link "https://github.com/user/project"]

Required flags:

• --name: Project name
• --description: Project description

Optional flags:

• --link: Project URL

cveasy add education

Add a new education entry.

cveasy add education --name "Bachelor of Science in Computer Science" [--organization "University Name"] [--degree "Bachelor of Science"] [--start_date "2018-09-01"] [--end_date "2022-05-15"] [--certificate "Certificate Name"]

Required flags:

• --name: Education name/title

Optional flags:

• --organization: School/institution name
• --degree: Degree type
• --start_date: Start date (YYYY-MM-DD)
• --end_date: End date (YYYY-MM-DD) or "Present"
• --certificate: Certificate name

cveasy add job

Add a new job application.

cveasy add job --name "Software Engineer Position" [--url "https://example.com/job"]

Required flags:

• --name: Job application name

Optional flags:

• --url: URL to scrape job description from

If --url is provided, the command automatically scrapes the job description from the URL. Otherwise, it creates an empty job-description.md file for manual entry.

The application ID is automatically generated as {slugified-name}-{date} (e.g., software-engineer-20260125).

cveasy generate

Generate resumes using AI.

Options:

• -a, --application <app-id>: Application ID to generate customized resume for (optional)
• -u, --update: Update resume based on check report (requires --application)
• -p, --project <path>: Project directory path (optional)

Examples:

# Generate general resume from all available data
cveasy generate

# Generate customized resume for a job application
cveasy generate --application software-engineer-20260125
cveasy generate -a software-engineer-20260125

# Update resume based on check report recommendations
cveasy generate --application software-engineer-20260125 --update
cveasy generate -a software-engineer-20260125 -u

General resumes are saved to resume/resume-{date}.md, application resumes to applications/{app-id}/resume.md. All commands display token usage statistics.

cveasy cover-letter

Generate personalized cover letters for job applications using AI.

Options:

• -a, --application <app-id>: Application ID to generate cover letter for (required)
• -r, --reason <text>: Optional reason for interest in the job application
• -p, --project <path>: Project directory path (optional)

Examples:

# Generate cover letter for a job application
cveasy cover-letter --application software-engineer-20260125
cveasy cover-letter -a software-engineer-20260125

# Generate cover letter with a reason for interest
cveasy cover-letter --application software-engineer-20260125 --reason "I'm excited about the company's mission"
cveasy cover-letter -a software-engineer-20260125 -r "I'm excited about the company's mission"

Generates a personalized cover letter (max 500 words) tailored to the job application and saves it to applications/{app-id}/cover-letter.md.

cveasy check

Check resume quality against job description.

Options:

• -a, --application <app-id>: Application ID to run resume check for (required)
• --project <path>: Project directory path (optional)

Examples:

cveasy check --application software-engineer-20260125
cveasy check -a software-engineer-20260125

Automatically generates a resume if needed, performs keyword and skills matching, uses LLM to compare against the job description, and saves a detailed report to applications/{app-id}/check-report.md.

Tip: After reviewing the check report, run cveasy generate --application <app-id> --update to improve your resume.

cveasy import

Import resume data from PDF or DOCX files. Uses AI to automatically extract and parse skills, experiences, projects, stories, education, links, and bio from your existing resume.

Options:

• -f, --file <path>: Path to PDF or DOCX resume file (required)
• --project <path>: Project directory path (optional)

Examples:

cveasy import -f resume.pdf
cveasy import --file resume.docx
cveasy import -f /path/to/resume.pdf --project /path/to/project

Extracts and parses resume content from PDF or DOCX files using AI, automatically creating bio, skills, experiences, projects, stories, education, and links. Skips existing entries to avoid overwriting.

cveasy export

Export resume to PDF or Word document.

Options:

• -a, --application <app-id>: Application ID to export resume for
• -f, --file <path>: Path to resume markdown file
• --format <format>: Export format: pdf or docx (default: pdf)
• --output <path>: Output file path (optional, defaults to same location as source)
• --project <path>: Project directory path (optional)

Important: You must specify exactly one source: either --application or --file.

Examples:

# Export application resume to PDF (default)
cveasy export --application software-engineer-20260125

# Export application resume to Word
cveasy export --application software-engineer-20260125 --format docx --output resume.docx

# Export specific resume file
cveasy export --file applications/software-engineer-20260125/resume.md --format pdf

# Export general resume
cveasy export --file resume/resume-20260125.md --format docx

Configuration

Project Path

All commands support a --project <path> flag to specify the project directory if you're not running from within it. If not specified, CVEasy automatically searches for the project root by looking for:

• A .git directory with expected CVEasy subdirectories
• Required subdirectories (skills, experiences, stories, links, projects, applications)

The search starts from the current working directory and walks up the directory tree.

Environment Variables

Configuration is managed through a .env file in your project root. You can configure it using the cveasy config command (recommended) or by manually editing the .env file.

CVEasy automatically loads the .env file from:

1. The project root directory
2. Any parent directory (searches up the directory tree)
3. The current working directory (fallback)

Required Configuration

CVEASY_AI_PROVIDER (required)

• AI provider to use: openai, anthropic, or openrouter
• Must be set for the CLI to work

CVEASY_API_KEY (required)

• Your API key for the selected provider
• Used for all providers (OpenAI, Anthropic, OpenRouter)

Optional Configuration

CVEASY_MODEL (optional)

• Model to use (provider-specific defaults)
• OpenAI default: gpt-4
  • Common options: gpt-4, gpt-4-turbo, gpt-4o, gpt-3.5-turbo
• Anthropic default: claude-3-haiku-20240307
  • Common options: claude-3-5-sonnet-20241022, claude-3-opus-20240229, claude-3-sonnet-20240229, claude-3-haiku-20240307
• OpenRouter default: openai/gpt-4
  • Format: provider/model-name (e.g., openai/gpt-4, anthropic/claude-3-opus)

CVEASY_MAX_TOKENS (optional)

• Maximum tokens for responses (default: 8192)
• Note: Model limits vary (claude-3-5-sonnet supports 8192, older models typically 4096)

Note: The spaCy language model (en_core_web_sm) is automatically included and downloaded on first use. Required for the cveasy check command.

Example .env File

# AI Provider Configuration (REQUIRED)
CVEASY_AI_PROVIDER=openai

# Unified API Configuration
CVEASY_API_KEY=sk-your-key-here

# Model Configuration (optional)
CVEASY_MODEL=gpt-4

# Maximum tokens (optional, defaults to 8192)
CVEASY_MAX_TOKENS=8192

Usage Examples

Working with Multiple Projects

All commands support the --project <path> flag to work with projects from any directory:

cveasy add skill --name "Python" --project ~/resumes/tech-resume
cveasy generate --project ~/resumes/tech-resume
cveasy check --application engineer-20260125 --project ~/resumes/tech-resume

Services (For Developers)

CVEasy is built with a service-oriented architecture. The following services handle different aspects of the application:

• ResumeService: Resume generation and management

  • generate_general_resume(): Generate resume from all available data
  • generate_customized_resume(): Generate resume customized for a job application
  • update_resume_from_check_report(): Update resume based on check report feedback

• ApplicationService: Job application management

  • create_application(): Create new job application with optional URL scraping
  • scrape_job_description(): Scrape job description from URL
  • list_applications(): List all job applications

• DataService: CRUD operations for resume data

  • create_skill(), create_experience(), create_story(), etc.
  • create_or_update_bio(): Manage bio information

• ImportService: Resume import from PDF/DOCX

  • import_resume(): Extract and parse resume from PDF or DOCX file

• ExportService: Resume export to PDF/Word

  • export_application_resume(): Export application resume
  • export_file_resume(): Export any resume markdown file

• CheckService: Resume quality checking

  • check_resume(): Perform comprehensive resume quality analysis

• ProjectService: Project initialization

  • initialize_project(): Create new CVEasy project structure

• MeteringService: Token usage tracking

  • Tracks AI API token usage across all operations

Development

Installing the CLI Tool

First, install the CVEasy CLI tool on your system:

Using UV (Recommended)

# Install UV if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone the repository
git clone <repository-url>
cd make-cveasy-cli

# Install dependencies and CLI in development mode
uv sync --extra dev
uv pip install -e .

# If downloading the spaCy model fails, you may need:
uv pip install -U pip setuptools wheel

Note: uv sync automatically creates a virtual environment if one doesn't exist. You can also explicitly create one with uv venv first.

Using pip

# Clone the repository
git clone <repository-url>
cd make-cveasy-cli

# Install CLI and dependencies
pip install -e ".[dev]"

Verifying Installation

After installation, verify the CLI is working:

cveasy --help

Setting Up for Development

Follow the Installing the CLI Tool instructions above. Development setup is the same as regular installation.

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=src/cveasy --cov-report=html

# Run specific test file
pytest tests/test_commands/test_add.py

# Run with verbose output
pytest -v

Code Quality

The project uses ruff for linting and formatting:

# Check code style
ruff check src/

# Format code
ruff format src/

# Check and fix
ruff check --fix src/

Project Structure

make-cveasy-cli/
├── src/
│   └── cveasy/
│       ├── ai/              # AI provider implementations
│       ├── analysis/         # Resume analysis and checking
│       ├── commands/         # CLI command implementations
│       ├── models/           # Data models
│       ├── parsing/         # Resume parsing
│       ├── scraping/        # Web scraping utilities
│       ├── services/        # Business logic services
│       ├── storage/          # Data storage layer
│       ├── cli.py           # Main CLI entry point
│       └── config.py        # Configuration management
├── tests/                   # Test suite
├── example/                 # Example resume project
├── pyproject.toml          # Project configuration
└── README.md               # This file

Contributing

1. Create a feature branch
2. Make your changes
3. Run tests: pytest
4. Check code style: ruff check src/
5. Submit a pull request

License

MIT