Prompt Skill

Prompt Skill

Purpose

Create beautiful, interactive terminal prompts using questionary.

Instructions

Custom Style

import questionary
from questionary import Style

# Retro cyberpunk style
PROMPT_STYLE = Style([
    ('qmark', 'fg:#FF00FF bold'),       # Question mark
    ('question', 'fg:#00FFFF bold'),     # Question text
    ('answer', 'fg:#00FF00 bold'),       # Answer text
    ('pointer', 'fg:#FF00FF bold'),      # Selection pointer
    ('highlighted', 'fg:#00FFFF bold'),  # Highlighted option
    ('selected', 'fg:#00FF00'),          # Selected checkbox
    ('separator', 'fg:#888888'),         # Separator line
    ('instruction', 'fg:#888888'),       # Instructions
    ('text', 'fg:#FFFFFF'),              # Regular text
])

Text Input

def prompt_title() -> str:
    """Prompt for task title."""
    return questionary.text(
        "Task title:",
        validate=lambda t: len(t.strip()) > 0 or "Title cannot be empty",
        style=PROMPT_STYLE
    ).ask()

def prompt_description() -> str:
    """Prompt for optional description."""
    return questionary.text(
        "Description (optional):",
        multiline=False,
        style=PROMPT_STYLE
    ).ask() or ""

Selection Menu

def prompt_priority() -> str:
    """Prompt for priority selection."""
    choices = [
        questionary.Choice("🟢 Low", value="low"),
        questionary.Choice("🟡 Medium", value="medium"),
        questionary.Choice("🟠 High", value="high"),
        questionary.Choice("🔴 Urgent", value="urgent"),
    ]
    return questionary.select(
        "Priority level:",
        choices=choices,
        default="medium",
        style=PROMPT_STYLE
    ).ask()

def prompt_main_menu() -> str:
    """Main menu selection."""
    choices = [
        questionary.Choice("📝 Add Task", value="add"),
        questionary.Choice("📋 List Tasks", value="list"),
        questionary.Choice("🔍 Search", value="search"),
        questionary.Choice("✅ Complete Task", value="complete"),
        questionary.Choice("🗑️ Delete Task", value="delete"),
        questionary.Choice("⚙️ Settings", value="settings"),
        questionary.Choice("👋 Exit", value="exit"),
    ]
    return questionary.select(
        "What would you like to do?",
        choices=choices,
        style=PROMPT_STYLE
    ).ask()

Checkbox (Multiple Selection)

def prompt_tags(existing_tags: list = None) -> list:
    """Prompt for tag selection."""
    default_tags = ["work", "personal", "urgent", "shopping", "health"]
    all_tags = list(set(default_tags + (existing_tags or [])))
    
    choices = [questionary.Choice(tag, value=tag) for tag in sorted(all_tags)]
    
    return questionary.checkbox(
        "Select tags:",
        choices=choices,
        style=PROMPT_STYLE
    ).ask() or []

Confirmation

def confirm_action(message: str, default: bool = False) -> bool:
    """Confirm an action."""
    return questionary.confirm(
        message,
        default=default,
        style=PROMPT_STYLE
    ).ask()

def confirm_delete(task_title: str) -> bool:
    """Confirm task deletion."""
    return confirm_action(
        f"Delete '{task_title}'? This cannot be undone.",
        default=False
    )

Autocomplete

def prompt_search(suggestions: list = None) -> str:
    """Search with autocomplete."""
    return questionary.autocomplete(
        "Search tasks:",
        choices=suggestions or [],
        style=PROMPT_STYLE
    ).ask()

Complete Task Form

def prompt_add_task(existing_tags: list = None) -> dict:
    """Complete form for adding a task."""
    
    # Get title
    title = questionary.text(
        "Task title:",
        validate=lambda t: len(t.strip()) > 0 or "Title is required",
        style=PROMPT_STYLE
    ).ask()
    
    if not title:  # User cancelled
        return None
    
    # Get description
    description = questionary.text(
        "Description (optional):",
        style=PROMPT_STYLE
    ).ask()
    
    # Get priority
    priority = questionary.select(
        "Priority:",
        choices=[
            questionary.Choice("🟢 Low", value="low"),
            questionary.Choice("🟡 Medium", value="medium"),
            questionary.Choice("🟠 High", value="high"),
            questionary.Choice("🔴 Urgent", value="urgent"),
        ],
        default="medium",
        style=PROMPT_STYLE
    ).ask()
    
    # Get tags
    tags = questionary.checkbox(
        "Tags:",
        choices=list(set(["work", "personal", "urgent"] + (existing_tags or []))),
        style=PROMPT_STYLE
    ).ask() or []
    
    # Ask about due date
    has_due = questionary.confirm(
        "Set a due date?",
        default=False,
        style=PROMPT_STYLE
    ).ask()
    
    due_date = None
    if has_due:
        due_date = questionary.text(
            "Due date (YYYY-MM-DD):",
            validate=lambda d: _validate_date(d),
            style=PROMPT_STYLE
        ).ask()
    
    return {
        "title": title.strip(),
        "description": description.strip() if description else None,
        "priority": priority,
        "tags": tags,
        "due_date": due_date
    }

def _validate_date(date_str: str) -> bool:
    """Validate date format."""
    if not date_str:
        return True
    try:
        from datetime import datetime
        datetime.strptime(date_str, "%Y-%m-%d")
        return True
    except ValueError:
        return "Invalid date format. Use YYYY-MM-DD"

Task Selection

def prompt_select_task(tasks: list) -> int:
    """Select a task from list."""
    if not tasks:
        return None
    
    choices = [
        questionary.Choice(
            f"[{t['id']}] {t['title']} ({t['priority']})",
            value=t['id']
        )
        for t in tasks
    ]
    
    return questionary.select(
        "Select a task:",
        choices=choices,
        style=PROMPT_STYLE
    ).ask()

Best Practices

• Always provide a custom style for consistency
• Add validation to text inputs
• Use Choice objects for cleaner value mapping
• Handle None returns (user cancellation)
• Group related prompts into form functions
• Use icons for visual appeal
• Provide sensible defaults
• Add confirmation for destructive actions

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