Looking at how the prompt and tool access affects quality
After looking at the 6 Key Principles For Production AI Agents, I was interested in a certain question which I had to answer myself:
How useful are prompts and tools really?
This sounds like a silly question. Of course they are important, it has allowed a number of innovations and the general increase of quality prompts (especially consider the context revolution we are seeing).
So I propose looking into the response by a given prompt by 3 factors:
- The quality of the response
- The reliability/ reproducibility of a response
- How many tokens did it use? (ie how expensive was the response)
In order to make this a fair test, I will need to consider a number of factors to ensure fair testing;
- The Large Language Model used - this idea is key to the principle of “Investing in your system prompt” as Arseni Kravchenko mentioned.
- The length of the initial prompt
- The tools available
- The type of response it needs to answer with
- The type and amount of context going into the LLM.
(The type and amount of context goes hand in hand with the length of the prompt and the tools that are being able to be used.)
Let us first compare the quality of the responses given these factors.
In order to test these prompts I used my previous work that uses the Claude API to essentially be a chatbot. Here is a link to the repository: here!
Problem Solving Task
First we need to consider a basic task: Solving an simple maths equation. This is a good baseline for a repeatable, reliable high accuracy response.
This will be the prompt I will use initially:
I need help solving this quadratic equation step-by-step: 2x² + 5x - 3 = 0. Please show your work using the quadratic formula, explain each step clearly, verify your answer by substituting back into the original equation.
Then I will provide an average and low level quality prompt:
Can you solve 2x² + 5x - 3 = 0 using the quadratic formula? Please show the steps so I can understand how to do similar problems.
solve 2x² + 5x - 3 = 0
We will try each prompt 2 times.
High Quality prompt
First try:
I'll solve the quadratic equation 2x² + 5x - 3 = 0 using the quadratic formula and show each step clearly.
## Step 1: Identify the coefficients
For a quadratic equation in the form ax² + bx + c = 0:
- a = 2
- b = 5
- c = -3
## Step 2: Apply the quadratic formula
The quadratic formula is: x = (-b ± √(b² - 4ac)) / (2a)
## Step 3: Calculate the discriminant (b² - 4ac)
b² - 4ac = 5² - 4(2)(-3)
= 25 - 4(2)(-3)
= 25 - (-24)
= 25 + 24
= 49
## Step 4: Substitute into the quadratic formula
x = (-5 ± √49) / (2·2)
x = (-5 ± 7) / 4
## Step 5: Solve for both solutions
**First solution:** x₁ = (-5 + 7) / 4 = 2/4 = 1/2
**Second solution:** x₂ = (-5 - 7) / 4 = -12/4 = -3
## Step 6: Verify by substitution
**Checking x = 1/2:**
2(1/2)² + 5(1/2) - 3
= 2(1/4) + 5/2 - 3
= 1/2 + 5/2 - 3
= 6/2 - 3
= 3 - 3 = 0 ✓
**Checking x = -3:**
2(-3)² + 5(-3) - 3
= 2(9) - 15 - 3
= 18 - 15 - 3
= 0 ✓
## Final Answer
The solutions are x = 1/2 and x = -3.
Both solutions check out when substituted back into the original equation, confirming our work is correct.Second try:
I'll solve this quadratic equation step-by-step using the quadratic formula.
Given equation: **2x² + 5x - 3 = 0**
## Step 1: Identify the coefficients
For a quadratic equation in the form ax² + bx + c = 0:
- a = 2
- b = 5
- c = -3
## Step 2: Apply the quadratic formula
The quadratic formula is: x = (-b ± √(b² - 4ac)) / (2a)
## Step 3: Calculate the discriminant
First, let's find b² - 4ac:
- b² = 5² = 25
- 4ac = 4(2)(-3) = -24
- b² - 4ac = 25 - (-24) = 25 + 24 = 49
## Step 4: Substitute into the formula
x = (-5 ± √49) / (2 × 2)
x = (-5 ± 7) / 4
## Step 5: Find both solutions
**First solution:** x₁ = (-5 + 7) / 4 = 2/4 = 1/2
**Second solution:** x₂ = (-5 - 7) / 4 = -12/4 = -3
## Step 6: Verify by substitution
**For x = 1/2:**
2(1/2)² + 5(1/2) - 3 = 2(1/4) + 5/2 - 3 = 1/2 + 5/2 - 3 = 6/2 - 3 = 3 - 3 = 0 ✓
**For x = -3:**
2(-3)² + 5(-3) - 3 = 2(9) - 15 - 3 = 18 - 15 - 3 = 0 ✓
## Final Answer
The solutions are **x = 1/2** and **x = -3**.
Both solutions check out when substituted back into the original equation, confirming our work is correct.They are very similar in quality, and it is also very similar in content and style. So this is a good response to the prompt. It used around 800 tokens (255 input, 560 output).
Medium Quality prompt
First try:
I'll solve this quadratic equation step by step using the quadratic formula.
For a quadratic equation in the form ax² + bx + c = 0, the quadratic formula is:
x = (-b ± √(b² - 4ac)) / (2a)
Step 1: Identify the coefficients
From 2x² + 5x - 3 = 0:
a = 2
b = 5
c = -3
Step 2: Calculate the discriminant (b² - 4ac)
b² - 4ac = (5)² - 4(2)(-3)
= 25 - 4(2)(-3)
= 25 - (-24)
= 25 + 24
= 49
Step 3: Apply the quadratic formula
x = (-5 ± √49) / (2 × 2)
x = (-5 ± 7) / 4
Step 4: Solve for both solutions
x₁ = (-5 + 7) / 4 = 2/4 = 1/2
x₂ = (-5 - 7) / 4 = -12/4 = -3
Step 5: Check your answers (optional but recommended)
For x = 1/2: 2(1/2)² + 5(1/2) - 3 = 2(1/4) + 5/2 - 3 = 1/2 + 5/2 - 3 = 3 - 3 = 0 ✓
For x = -3: 2(-3)² + 5(-3) - 3 = 2(9) - 15 - 3 = 18 - 18 = 0 ✓
Therefore, the solutions are x = 1/2 and x = -3.Second try:
I'll solve this quadratic equation step by step using the quadratic formula.
For a quadratic equation in the form ax² + bx + c = 0, the quadratic formula is:
x = (-b ± √(b² - 4ac)) / (2a)
Step 1: Identify the coefficients
From 2x² + 5x - 3 = 0:
a = 2
b = 5
c = -3
Step 2: Calculate the discriminant (b² - 4ac)
b² - 4ac = (5)² - 4(2)(-3)
= 25 - 4(2)(-3)
= 25 - (-24)
= 25 + 24
= 49
Step 3: Apply the quadratic formula
x = (-5 ± √49) / (2·2)
x = (-5 ± 7) / 4
Step 4: Find both solutions
x₁ = (-5 + 7) / 4 = 2/4 = 1/2
x₂ = (-5 - 7) / 4 = -12/4 = -3
Step 5: Verify the solutions
For x = 1/2: 2(1/2)² + 5(1/2) - 3 = 2(1/4) + 5/2 - 3 = 1/2 + 5/2 - 3 = 3 - 3 = 0 ✓
For x = -3: 2(-3)² + 5(-3) - 3 = 2(9) - 15 - 3 = 18 - 18 = 0 ✓
Therefore, the solutions are x = 1/2 and x = -3.It still produced a sufficient response to the prompt, with a detailed answer (albeit slightly less detailed) and reliably answered correctly. This prompt however only used about 500 tokens, a ~40% decrease in tokens for a minimal trade off in quality.
Low Quality prompt
First try:
I'll solve this quadratic equation using the quadratic formula.
For the equation 2x² + 5x - 3 = 0, I have:
a = 2
b = 5
c = -3
Using the quadratic formula: x = (-b ± √(b² - 4ac)) / (2a)
First, I'll calculate the discriminant:
b² - 4ac = 5² - 4(2)(-3) = 25 + 24 = 49
Now I can find the solutions:
x = (-5 ± √49) / (2·2)
x = (-5 ± 7) / 4
This gives me two solutions:
x₁ = (-5 + 7) / 4 = 2/4 = 1/2
x₂ = (-5 - 7) / 4 = -12/4 = -3
Therefore, the solutions are x = 1/2 and x = -3.Second try:
I'll solve this quadratic equation using the quadratic formula.
For the equation 2x² + 5x - 3 = 0, I have:
a = 2
b = 5
c = -3
Using the quadratic formula: x = (-b ± √(b² - 4ac)) / (2a)
First, I'll calculate the discriminant:
b² - 4ac = 5² - 4(2)(-3) = 25 + 24 = 49
Now I can find the solutions:
x = (-5 ± √49) / (2·2)
x = (-5 ± 7) / 4
This gives me two solutions:
x₁ = (-5 + 7) / 4 = 2/4 = 1/2
x₂ = (-5 - 7) / 4 = -12/4 = -3
Therefore, x = 1/2 and x = -3.Finally, this prompt produced a correct answer, but an answer lacking detail. It only answered the question, and gave no insight on a number of things (such as what is a discriminant, what we know from it, steps to take etc). Moreover it still used 350-450 tokens, so only a minimal decrease of tokens for a huge drop in quality content.
Overall it is shown here that it does pay to invest in the quality of the prompt, and to follow the second key principle of providing the minimal amount of context. In hindsight this is a poor test to see the quality drop as it was a relatively simple question. I may come back and try a much harder question.
Creative Writing Task
Next we will consider natural language. This is a good test of the difference in quality depending on the quality of the prompt, as humans can physically see the difference in the response and objectively compare them. These are the 3 prompts I will use:
Write a 10-line unrhymed iambic pentameter poem (blank verse) exploring the theme of memory and time. Each line should follow the unstressed-stressed syllable pattern (da-DUM da-DUM da-DUM da-DUM da-DUM) for exactly 10 syllables. Focus on creating vivid, concrete imagery rather than abstract concepts. Please scan one line to demonstrate the meter, mark any intentional variations you use for emphasis, and briefly explain your word choices for maintaining natural speech patterns while adhering to the strict meter. The poem should tell a small story or capture a specific moment.
Write 8-10 lines of unrhymed iambic pentameter about memories. Make sure each line has 10 syllables following the unstressed-stressed pattern. Try to keep the language natural while following the meter. Include some imagery and make it feel like real speech.
Write some unrhymed iambic pentameter about memory
High Quality prompt
First try:
**"The Photograph"** She holds the yellowed photograph at dawn, Her mother's face now younger than her own. The garden gate stands open in the frame Where roses climbed, now tangled weeds remain. She traces lines around those smiling eyes That watched her grow through summers long since passed. The morning light reveals her trembling hands— The same thin veins, the same gold wedding band. Time folds upon itself in this still room As past and present merge in morning's glow. **Scansion of line 4:** Where RO- | ses CLIMBED, | now TAN- | gled WEEDS | re-MAIN **Metrical Analysis:** I maintained natural speech patterns while adhering to iambic pentameter through careful word selection: - "yellowed photograph" flows naturally as "the YEL-lowed PHO-to-GRAPH" - "morning light reveals" creates smooth iambs: "The MOR-ning LIGHT re-VEALS" - Monosyllabic words like "dawn," "frame," "hands," and "band" provide stressed anchors I used one subtle variation in line 9 where "Time folds" creates a spondee (two stressed syllables) for emphasis, highlighting the poem's central metaphor of time collapsing. This variation mimics natural speech emphasis while maintaining the overall iambic flow. Word choices like "tangled" over "twisted" and "trembling" over "shaking" preserve the unstressed-stressed pattern while creating vivid imagery. The poem tells the story of a daughter discovering her physical resemblance to her mother through an old photograph, making time's passage tangible through concrete details rather than abstract meditation.Second try:
**"The Photograph"** She finds the photograph beneath her bed, Its corners bent from years of being held. Her mother's face looks up through yellowed glass— That summer dress with roses, pink and full. The kitchen table set for Sunday lunch, White plates arranged like moons against dark wood. She hears her father's laughter through the years, Can taste the lemon cake they used to share. But empty chairs now circle where they sat, And time has stolen more than it has saved. **Scansion of line 3:** Her MO- | ther's FACE | looks UP | through YEL- | lowed GLASS (da-DUM | da-DUM | da-DUM | da-DUM | da-DUM) **Intentional variation:** Line 9: "But empty chairs now circle where they sat" The stress on "empty" creates a trochee (DUM-da) at the beginning, emphasizing the absence and loneliness. This mirrors natural speech emphasis while creating emotional weight. **Word choice notes:** - "beneath her bed" instead of "under the bed" maintains iambic flow - "looks up through yellowed glass" uses natural prepositions that fall on unstressed beats - "Can taste" at the beginning of line 8 preserves the iambic pattern better than "She tastes" - Chose concrete, sensory details (photograph, roses, lemon cake, empty chairs) over abstract terms about memory - Used simple past tense and present tense to create temporal contrast while maintaining meterInput tokens: 148, Output tokens: 403, Total: 551 Input tokens: 149, Output tokens: 373, Total: 522
These responses are both very good. They both have an in depth explanation for each line, they have rigorous iambic pentameter, with a concrete narrative that is complex and not cliche, and integrates both the technical and creative features well. As it also uses around 530 tokens, it is not computationally demanding, so a quality prompt for little real cost.
Medium Quality prompt
First try:
The photographs grow yellow in their frames, While faces blur like watercolor paint. I catch myself forgetting how you laughed, Though once that sound could fill an empty room. The mind selects which moments it will keep— A summer dress, the smell of brewing tea, Your hand upon my shoulder, warm and brief. What strange economy of love and loss That lets us hold so little of so much, These fragments all that time has left behind.Second try:
The photographs grow yellow in their frames, While faces blur like watercolor paint. I try to hold the sound of Mother's voice, But years have worn the edges of her laugh. That summer by the lake returns to me— The wooden dock, the smell of pine and rain. We swam until our fingertips turned blue, Then built a fire and watched the sparks rise up. These fragments come unbidden in the night, Like guests who've traveled far to reach my door.Input tokens: 74, Output tokens: 104, Total: 178 Input tokens: 76, Output tokens: 112, Total: 188
These responses are definitely a decrease in quality. It obviously has no explanation for its choices, its choices in the narrative is a more standard style of writing, but is still on theme and emotionally rich. It also suits the task of iambic pentameter. Definitely less good but uses a lot less tokens (around 180) so is definitely good cost benefit wise.
Low Quality prompt
First try:
Here are some lines of unrhymed iambic pentameter about memory: The mind preserves what time would steal away, Though faces blur and voices grow more faint. I grasp at shadows dancing in my thoughts, Each fragment tells a story incomplete. The photograph reminds me who we were Before the years transformed us into strangers. A scent can pull me backward through the dark To find myself within my mother's arms. What stays with us? What fades beyond recall? The heart remembers what the mind forgets, While trivial moments cling like stubborn ghosts And crucial words dissolve like morning mist. Perhaps we are the sum of what we keep, These hoarded treasures locked inside our skulls, Or maybe we become what we release— The memories we let go set us freeSecond try:
Here are some lines of unrhymed iambic pentameter about memory: The past returns in fragments through the mind, A scent of roses brings my mother back. I close my eyes and see that summer day When light fell golden on the garden wall. What stays, what fades—who knows the reason why One moment burns while decades turn to mist? The brain selects which treasures it will keep, Discarding hours like forgotten leaves. Perhaps we are the sum of what remains: These broken pieces, sharp and beautiful, That cut us when we hold them to the light. Memory builds a palace made of air Where we can walk through rooms that are no more And speak to ghosts who answer in our voice.Input tokens: 28, Output tokens: 189, Total: 217 Input tokens: 28, Output tokens: 168, Total: 196
These responses are poor. Like with the medium prompt, it also does not provide any explanation for its choices, and fails to provide iambic pentameter at times in the lines. It also used more tokens than the previous prompt.
Overall the best prompt is clearly the higher quality prompt, and this showed me that the lower quality cost more tokens than the medium quality prompt, as it was more vague the API had to work harder to provide an adequate response, which also was not as good, so the quality is definitely dependent on the prompt, solidifying the key principle.
Coding Task
Next we will consider coding tasks. This is a good show of complex reasoning and ability to generate functioning code. I will test it, looking at what features it has, and the general front end. Token wise this will always be computationally dense, so I think I will come against some token limits that I set. This is okay, as I will ensure it has a fully made product depending on if it hits the limit or not.
Here is the prompts used:
Create a Python invoice generator that calculates totals with tax. The system should include: - A function to create line items with description, quantity, and unit price - Tax calculation (accept tax rate as parameter, default 8.5%) - Proper formatting for currency display (2 decimal places) - Input validation (positive numbers only, non-empty descriptions) - Generate a formatted invoice string with header, line items, subtotal, tax, and total - Include type hints and comprehensive docstrings - Add at least 3 unit tests covering normal cases and edge cases - Handle errors gracefully (invalid inputs, division by zero, etc.) - Make it extensible for future features like discounts Provide a usage example with a multi-item invoice and explain your design choices.
Write a Python function that creates a simple invoice. It should take a list of items (each with description, quantity, and price) and a tax rate, then return a formatted invoice string showing each line item, subtotal, tax amount, and total. Include some basic error checking for negative numbers and make sure currency is formatted properly. Show how to use it with an example.
Write code to make an invoice in python
High Quality prompt
First try:
"""
Invoice Generator Module
A flexible invoice generation system with tax calculation, proper formatting,
and extensibility for future features.
"""
from typing import List, Optional, Dict, Any
from dataclasses import dataclass
from decimal import Decimal, ROUND_HALF_UP
from datetime import datetime
import unittest
class InvoiceError(Exception):
"""Custom exception for invoice-related errors."""
pass
@dataclass
class LineItem:
"""
Represents a single line item in an invoice.
Attributes:
description: Item description
quantity: Number of units
unit_price: Price per unit
discount_percent: Optional discount percentage (0-100)
"""
description: str
quantity: Decimal
unit_price: Decimal
discount_percent: Decimal = Decimal('0')
def __post_init__(self):
"""Validate line item data after initialization."""
if not self.description or not self.description.strip():
raise InvoiceError("Description cannot be empty")
if self.quantity <= 0:
raise InvoiceError(f"Quantity must be positive, got {self.quantity}")
if self.unit_price < 0:
raise InvoiceError(f"Unit price cannot be negative, got {self.unit_price}")
if not 0 <= self.discount_percent <= 100:
raise InvoiceError(f"Discount must be between 0 and 100, got {self.discount_percent}")
@property
def subtotal(self) -> Decimal:
"""Calculate subtotal before discount."""
return self.quantity * self.unit_price
@property
def discount_amount(self) -> Decimal:
"""Calculate discount amount."""
return self.subtotal * (self.discount_percent / 100)
@property
def total(self) -> Decimal:
"""Calculate total after discount."""
return self.subtotal - self.discount_amount
class Invoice:
"""
Invoice generator with tax calculation and formatting capabilities.
Attributes:
invoice_number: Unique invoice identifier
customer_name: Name of the customer
tax_rate: Tax rate as a percentage (default 8.5%)
line_items: List of line items in the invoice
"""
def __init__(self, invoice_number: str, customer_name: str, tax_rate: float = 8.5):
"""
Initialize a new invoice.
Args:
invoice_number: Unique invoice identifier
customer_name: Name of the customer
tax_rate: Tax rate as a percentage (default 8.5%)
Raises:
InvoiceError: If inputs are invalid
"""
if not invoice_number or not invoice_number.strip():
raise InvoiceError("Invoice number cannot be empty")
if not customer_name or not customer_name.strip():
raise InvoiceError("Customer name cannot be empty")
if tax_rate < 0:
raise InvoiceError(f"Tax rate cannot be negative, got {tax_rate}")
self.invoice_number = invoice_number.strip()
self.customer_name = customer_name.strip()
self.tax_rate = Decimal(str(tax_rate))
self.line_items: List[LineItem] = []
self.created_date = datetime.now()
def add_line_item(self, description: str, quantity: float,
unit_price: float, discount_percent: float = 0) -> None:
"""
Add a line item to the invoice.
Args:
description: Item description
quantity: Number of units
unit_price: Price per unit
discount_percent: Optional discount percentage (0-100)
Raises:
InvoiceError: If inputs are invalid
"""
try:
item = LineItem(
description=description,
quantity=Decimal(str(quantity)),
unit_price=Decimal(str(unit_price)),
discount_percent=Decimal(str(discount_percent))
)
self.line_items.append(item)
except (ValueError, TypeError) as e:
raise InvoiceError(f"Invalid input type: {e}")
@property
def subtotal(self) -> Decimal:
"""Calculate subtotal of all line items after discounts."""
return sum(item.total for item in self.line_items)
@property
def tax_amount(self) -> Decimal:
"""Calculate tax amount."""
return self.subtotal * (self.tax_rate / 100)
@property
def total(self) -> Decimal:
"""Calculate total including tax."""
return self.subtotal + self.tax_amount
@staticmethod
def format_currency(amount: Decimal) -> str:
"""
Format a decimal amount as currency.
Args:
amount: The amount to format
Returns:
Formatted currency string
"""
# Round to 2 decimal places
rounded = amount.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)
return f"${rounded:,.2f}"
def generate_invoice(self) -> str:
"""
Generate a formatted invoice string.
Returns:
Formatted invoice as a multi-line string
"""
if not self.line_items:
raise InvoiceError("Cannot generate invoice with no line items")
# Header
lines = [
"=" * 80,
f"INVOICE #{self.invoice_number}".center(80),
"=" * 80,
f"Date: {self.created_date.strftime('%Y-%m-%d %H:%M')}",
f"Customer: {self.customer_name}",
"",
"-" * 80,
f"{'Description':<35} {'Qty':>8} {'Price':>12} {'Discount':>10} {'Total':>12}",
"-" * 80
]
# Line items
for item in self.line_items:
discount_str = f"{item.discount_percent}%" if item.discount_percent > 0 else "-"
lines.append(
f"{item.description[:35]:<35} "
f"{item.quantity:>8.2f} "
f"{self.format_currency(item.unit_price):>12} "
f"{discount_str:>10} "
f"{self.format_currency(item.total):>12}"
)
# Totals
lines.extend([
"-" * 80,
f"{'Subtotal:':>67} {self.format_currency(self.subtotal):>12}",
f"{'Tax (' + str(self.tax_rate) + '%):':>67} {self.format_currency(self.tax_amount):>12}",
"=" * 80,
f"{'TOTAL:':>67} {self.format_currency(self.total):>12}",
"=" * 80
])
return "\n".join(lines)
class TestInvoice(unittest.TestCase):
"""Unit tests for the Invoice system."""
def test_normal_invoice_generation(self):
"""Test normal invoice generation with multiple items."""
invoice = Invoice("INV-001", "Acme Corporation")
invoice.add_line_item("Widget A", 10, 25.50)
invoice.add_line_item("Widget B", 5, 45.00, discount_percent=10)
# Test calculations
self.assertEqual(invoice.subtotal, Decimal('457.50'))
self.assertEqual(invoice.tax_amount, Decimal('38.89')) # 8.5% of 457.50
self.assertEqual(invoice.total, Decimal('496.39'))
# Test invoice generation doesn't raise error
invoice_str = invoice.generate_invoice()
self.assertIn("INV-001", invoice_str)
self.assertIn("Acme Corporation", invoice_str)
def test_invalid_inputs(self):
"""Test error handling for invalid inputs."""
# Empty invoice number
with self.assertRaises(InvoiceError):
Invoice("", "Customer")
# Empty customer name
with self.assertRaises(InvoiceError):
Invoice("INV-001", "")
# Negative tax rate
with self.assertRaises(InvoiceError):
Invoice("INV-001", "Customer", tax_rate=-5)
# Invalid line item
invoice = Invoice("INV-001", "Customer")
with self.assertRaises(InvoiceError):
invoice.add_line_item("", 10, 25) # Empty description
with self.assertRaises(InvoiceError):
invoice.add_line_item("Item", -5, 25) # Negative quantity
with self.assertRaises(InvoiceError):
invoice.add_line_item("Item", 5, -25) # Negative price
def test_edge_cases(self):
"""Test edge cases and special scenarios."""
# Zero tax rate
invoice = Invoice("INV-001", "Customer", tax_rate=0)
invoice.add_line_item("Item", 1, 100)
self.assertEqual(invoice.tax_amount, Decimal('0'))
self.assertEqual(invoice.total, Decimal('100'))
# Very small amounts (test rounding)
invoice2 = Invoice("INV-002", "Customer")
invoice2.add_line_item("Penny Item", 3, 0.01)
self.assertEqual(invoice2.subtotal, Decimal('0.03'))
# Empty invoice generation
invoice3 = Invoice("INV-003", "Customer")
with self.assertRaises(InvoiceError):
invoice3.generate_invoice()
# 100% discount
invoice4 = Invoice("INV-004", "Customer")
invoice4.add_line_item("Free Item", 1, 100, discount_percent=100)
self.assertEqual(invoice4.subtotal, Decimal('0'))
def example_usage():
"""Demonstrate usage of the invoice generator."""
try:
# Create a new invoice
invoice = Invoice("INV-2024-001", "Tech Solutions Inc.", tax_rate=8.5)
# Add line items
invoice.add_line_item("Software License - Annual", 1, 1200.00)
invoice.add_line_item("Professional Services - Setup", 8, 150.00, discount_percent=15)
invoice.add_line_item("Training Session (per hour)", 4, 100.00)
invoice.add_line_item("Technical Support - Monthly", 12, 50.00, discount_percent=10)
# Generate and print the invoice
print(invoice.generate_invoice())
# Access individual totals
print(f"\nInvoice Summary:")
print(f"Subtotal: {Invoice.format_currency(invoice.subtotal)}")
print(f"Tax ({invoice.tax_rate}%): {Invoice.format_currency(invoice.tax_amount)}")
print(f"Total Due: {Invoice.format_currency(invoice.total)}")
except InvoiceError as e:
print(f"Invoice Error: {e}")
if __name__ == "__main__":
# Run example
example_usage()
# Run tests
print("\n" + "="*80)
print("Running unit tests...")
print("="*80)
unittest.main(argv=[''], exit=False)Second try:
"""
Invoice Generator Module
A flexible invoice generation system with tax calculation, proper formatting,
and extensibility for future features.
"""
from typing import List, Union
from dataclasses import dataclass
from decimal import Decimal, ROUND_HALF_UP
import unittest
from datetime import datetime
@dataclass
class LineItem:
"""Represents a single line item in an invoice."""
description: str
quantity: Decimal
unit_price: Decimal
@property
def total(self) -> Decimal:
"""Calculate the total price for this line item."""
return self.quantity * self.unit_price
class InvoiceError(Exception):
"""Custom exception for invoice-related errors."""
pass
class Invoice:
"""
Invoice generator with tax calculation and formatting capabilities.
"""
def __init__(self, tax_rate: float = 8.5, invoice_number: str = None):
if tax_rate < 0:
raise InvoiceError("Tax rate cannot be negative")
self.tax_rate = Decimal(str(tax_rate)) / 100
self.line_items: List[LineItem] = []
self.invoice_number = invoice_number or self._generate_invoice_number()
self.date = datetime.now()
def _generate_invoice_number(self) -> str:
"""Generate a unique invoice number based on timestamp."""
return f"INV-{datetime.now().strftime('%Y%m%d%H%M%S')}"
def add_line_item(
self,
description: str,
quantity: Union[int, float, Decimal],
unit_price: Union[int, float, Decimal]
) -> None:
"""Add a line item to the invoice."""
if not description or not description.strip():
raise InvoiceError("Description cannot be empty")
try:
qty = Decimal(str(quantity))
price = Decimal(str(unit_price))
except (ValueError, TypeError):
raise InvoiceError("Quantity and unit price must be valid numbers")
if qty <= 0:
raise InvoiceError("Quantity must be positive")
if price < 0:
raise InvoiceError("Unit price cannot be negative")
self.line_items.append(LineItem(description.strip(), qty, price))
def remove_line_item(self, index: int) -> None:
"""Remove a line item by index."""
if not 0 <= index < len(self.line_items):
raise InvoiceError(f"Invalid index: {index}")
self.line_items.pop(index)
def get_subtotal(self) -> Decimal:
"""Calculate the subtotal before tax."""
return sum(item.total for item in self.line_items)
def get_tax_amount(self) -> Decimal:
"""Calculate the tax amount."""
return self.get_subtotal() * self.tax_rate
def get_total(self) -> Decimal:
"""Calculate the total including tax."""
return self.get_subtotal() + self.get_tax_amount()
def apply_discount(self, discount_percent: float) -> Decimal:
"""Placeholder for future discount functionality."""
return Decimal("0")
@staticmethod
def format_currency(amount: Decimal) -> str:
"""Format a decimal amount as currency."""
rounded = amount.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)
return f"${rounded:,.2f}"
def generate_invoice(
self,
company_name: str = "Your Company",
customer_name: str = "Customer"
) -> str:
"""Generate a formatted invoice string."""
if not self.line_items:
raise InvoiceError("Cannot generate invoice with no line items")
lines = []
lines.append("=" * 60)
lines.append(f"INVOICE - {self.invoice_number}")
lines.append(f"Date: {self.date.strftime('%Y-%m-%d')}")
lines.append(f"From: {company_name}")
lines.append(f"To: {customer_name}")
lines.append("=" * 60)
lines.append("")
lines.append(f"{'Description':<30} {'Qty':>8} {'Price':>10} {'Total':>12}")
lines.append("-" * 60)
for item in self.line_items:
desc = item.description[:30]
lines.append(
f"{desc:<30} {item.quantity:>8.2f} "
f"{self.format_currency(item.unit_price):>10} "
f"{self.format_currency(item.total):>12}"
)
lines.append("-" * 60)
subtotal = self.get_subtotal()
tax_amount = self.get_tax_amount()
total = self.get_total()
lines.append(f"{'Subtotal:':>48} {self.format_currency(subtotal):>12}")
lines.append(f"{'Tax (' + f'{self.tax_rate * 100:.1f}%' + '):':>48} "
f"{self.format_currency(tax_amount):>12}")
lines.append("=" * 60)
lines.append(f"{'TOTAL:':>48} {self.format_currency(total):>12}")
return "\n".join(lines)
class TestInvoice(unittest.TestCase):
"""Unit tests for the Invoice class."""
def setUp(self):
self.invoice = Invoice(tax_rate=10.0)
def test_normal_invoice_generation(self):
self.invoice.add_line_item("Widget A", 5, 10.50)
self.invoice.add_line_item("Service B", 2, 50.00)
subtotal = self.invoice.get_subtotal()
self.assertEqual(subtotal, Decimal("152.50"))
tax = self.invoice.get_tax_amount()
self.assertEqual(tax, Decimal("15.25"))
total = self.invoice.get_total()
self.assertEqual(total, Decimal("167.75"))
invoice_str = self.invoice.generate_invoice("Test Corp", "John Doe")
self.assertIn("Widget A", invoice_str)
self.assertIn("$167.75", invoice_str)
def test_edge_cases(self):
with self.assertRaises(InvoiceError):
self.invoice.add_line_item("", 1, 10)
with self.assertRaises(InvoiceError):
self.invoice.add_line_item("Item", -1, 10)
with self.assertRaises(InvoiceError):
self.invoice.add_line_item("Item", 0, 10)
with self.assertRaises(InvoiceError):
self.invoice.add_line_item("Item", 1, -10)
with self.assertRaises(InvoiceError):
self.invoice.generate_invoice()
def test_decimal_precision(self):
self.invoice.add_line_item("Item 1", 3, 0.1)
self.invoice.add_line_item("Item 2", 7, 0.1)
subtotal = self.invoice.get_subtotal()
self.assertEqual(subtotal, Decimal("1.0"))
self.assertEqual(Invoice.format_currency(Decimal("1234.567")), "$1,234.57")
self.assertEqual(Invoice.format_currency(Decimal("0.001")), "$0.00")
def test_tax_calculations(self):
zero_tax_invoice = Invoice(tax_rate=0)
zero_tax_invoice.add_line_item("Item", 1, 100)
self.assertEqual(zero_tax_invoice.get_tax_amount(), Decimal("0"))
high_tax_invoice = Invoice(tax_rate=25.5)
high_tax_invoice.add_line_item("Item", 1, 100)
self.assertEqual(high_tax_invoice.get_tax_amount(), Decimal("25.50"))
with self.assertRaises(InvoiceError):
Invoice(tax_rate=-5)
def usage_example():
print("Invoice Generator Usage Example\n")
invoice = Invoice(tax_rate=8.5, invoice_number="INV-2024-001")
try:
invoice.add_line_item("Web Development Services", 40, 75.00)
invoice.add_line_item("Domain Registration (1 year)", 1, 15.99)
invoice.add_line_item("SSL Certificate", 1, 49.99)
invoice.add_line_item("Monthly Hosting", 3, 25.00)
invoice_output = invoice.generate_invoice(
company_name="TechCraft Solutions",
customer_name="ABC Corporation"
)
print(invoice_output)
print(f"\nBreakdown:")
print(f"Subtotal: {invoice.format_currency(invoice.get_subtotal())}")
print(f"Tax ({invoice.tax_rate * 100}%): {invoice.format_currency(invoice.get_tax_amount())}")
print(f"Total: {invoice.format_currency(invoice.get_total())}")
except InvoiceError as e:
print(f"Error: {e}")
print("\n\nError Handling Examples:")
try:
invoice.add_line_item("", 1, 10)
except InvoiceError as e:
print(f"✓ Caught error: {e}")
try:
invoice.add_line_item("Invalid Item", -5, 10)
except InvoiceError as e:
print(f"✓ Caught error: {e}")
print("\n\nModifying Invoice:")
invoice2 = Invoice(tax_rate=5.0)
invoice2.add_line_item("Product A", 10, 25.50)
invoice2.add_line_item("Product B", 5, 15.00)
print(f"Original item count: {len(invoice2.line_items)}")
invoice2.remove_line_item(1)
print(f"After removal: {len(invoice2.line_items)} items")
print(invoice2.generate_invoice("Demo Company", "Test Customer"))
if __name__ == "__main__":
usage_example()
print("\n\n" + "=" * 60)
print("Running Unit Tests")
print("=" * 60)
unittest.main(argv=[''], exit=False, verbosity=2)Input tokens: 194, Output tokens: 3000, Total: 3194 Input tokens: 194, Output tokens: 3000, Total: 3194
Hit the max (limitation of the API and system I use)
Medium Quality prompt
First try:
def create_invoice(items, tax_rate, customer_name="", invoice_number=""):
"""
Create a formatted invoice from a list of items and tax rate.
Args:
items: List of dictionaries, each containing 'description', 'quantity', and 'price'
tax_rate: Tax rate as a decimal (e.g., 0.08 for 8%)
customer_name: Optional customer name
invoice_number: Optional invoice number
Returns:
Formatted invoice string
Raises:
ValueError: If any numeric values are negative or if required fields are missing
"""
# Validate tax rate
if tax_rate < 0:
raise ValueError("Tax rate cannot be negative")
# Validate items
if not items:
raise ValueError("Invoice must contain at least one item")
for i, item in enumerate(items):
# Check required fields
if not all(key in item for key in ['description', 'quantity', 'price']):
raise ValueError(f"Item {i+1} missing required fields (description, quantity, price)")
# Check for negative values
if item['quantity'] < 0:
raise ValueError(f"Item {i+1}: Quantity cannot be negative")
if item['price'] < 0:
raise ValueError(f"Item {i+1}: Price cannot be negative")
# Build invoice header
invoice = []
invoice.append("=" * 60)
invoice.append("INVOICE".center(60))
invoice.append("=" * 60)
if invoice_number:
invoice.append(f"Invoice #: {invoice_number}")
if customer_name:
invoice.append(f"Customer: {customer_name}")
if invoice_number or customer_name:
invoice.append("-" * 60)
# Column headers
invoice.append(f"{'Description':<30} {'Qty':>8} {'Price':>10} {'Total':>12}")
invoice.append("-" * 60)
# Calculate items and subtotal
subtotal = 0
for item in items:
description = item['description'][:30] # Truncate long descriptions
quantity = item['quantity']
price = item['price']
line_total = quantity * price
subtotal += line_total
invoice.append(
f"{description:<30} {quantity:>8} ${price:>9.2f} ${line_total:>11.2f}"
)
# Calculate tax and total
tax_amount = subtotal * tax_rate
total = subtotal + tax_amount
# Add summary section
invoice.append("-" * 60)
invoice.append(f"{'Subtotal:':>48} ${subtotal:>11.2f}")
invoice.append(f"{'Tax (' + f'{tax_rate:.1%}' + '):':>48} ${tax_amount:>11.2f}")
invoice.append(f"{'Total:':>48} ${total:>11.2f}")
invoice.append("=" * 60)
return "\n".join(invoice)
# Example usage
if __name__ == "__main__":
# Example 1: Basic invoice
items = [
{"description": "Web Development Service", "quantity": 10, "price": 150.00},
{"description": "Logo Design", "quantity": 1, "price": 500.00},
{"description": "Monthly Hosting", "quantity": 3, "price": 29.99}
]
try:
invoice = create_invoice(items, 0.08, "ABC Company", "INV-2024-001")
print(invoice)
print("\n")
# Example 2: Different items with longer descriptions
items2 = [
{"description": "Professional Photography Session (2 hours)", "quantity": 1, "price": 450.00},
{"description": "Photo Editing and Retouching", "quantity": 50, "price": 15.00},
{"description": "8x10 Prints", "quantity": 20, "price": 12.50},
{"description": "Digital Album Creation", "quantity": 1, "price": 200.00}
]
invoice2 = create_invoice(items2, 0.0875) # 8.75% tax, no customer info
print(invoice2)
print("\n")
# Example 3: Error handling demonstration
invalid_items = [
{"description": "Invalid Item", "quantity": -5, "price": 100.00}
]
invoice3 = create_invoice(invalid_items, 0.08)
except ValueError as e:
print(f"Error creating invoice: {e}")Second try:
def create_invoice(items, tax_rate, customer_name="Customer", invoice_number="INV-001"):
"""
Create a formatted invoice string.
Args:
items: List of dictionaries with 'description', 'quantity', and 'price' keys
tax_rate: Tax rate as a decimal (e.g., 0.08 for 8%)
customer_name: Optional customer name (default: "Customer")
invoice_number: Optional invoice number (default: "INV-001")
Returns:
Formatted invoice string
Raises:
ValueError: If any prices, quantities, or tax rate are negative
"""
# Error checking
if tax_rate < 0:
raise ValueError("Tax rate cannot be negative")
if not items:
raise ValueError("Invoice must contain at least one item")
# Header
invoice = f"\n{'='*60}\n"
invoice += f"{'INVOICE':^60}\n"
invoice += f"{'='*60}\n\n"
invoice += f"Invoice Number: {invoice_number}\n"
invoice += f"Customer: {customer_name}\n"
invoice += f"{'-'*60}\n\n"
# Column headers
invoice += f"{'Description':<30} {'Qty':>8} {'Price':>10} {'Total':>12}\n"
invoice += f"{'-'*60}\n"
subtotal = 0
# Process each item
for i, item in enumerate(items, 1):
# Validate item structure
if not all(key in item for key in ['description', 'quantity', 'price']):
raise ValueError(f"Item {i} must have description, quantity, and price")
desc = item['description']
qty = item['quantity']
price = item['price']
# Error checking for individual items
if qty < 0:
raise ValueError(f"Quantity cannot be negative for item: {desc}")
if price < 0:
raise ValueError(f"Price cannot be negative for item: {desc}")
line_total = qty * price
subtotal += line_total
# Format line item
invoice += f"{desc:<30} {qty:>8} ${price:>9.2f} ${line_total:>11.2f}\n"
# Calculate tax and total
tax_amount = subtotal * tax_rate
total = subtotal + tax_amount
# Footer with totals
invoice += f"{'-'*60}\n"
invoice += f"{'Subtotal:':>48} ${subtotal:>11.2f}\n"
invoice += f"{'Tax (' + f'{tax_rate:.1%}' + '):':>48} ${tax_amount:>11.2f}\n"
invoice += f"{'-'*60}\n"
invoice += f"{'TOTAL:':>48} ${total:>11.2f}\n"
invoice += f"{'='*60}\n"
return invoice
# Example usage
if __name__ == "__main__":
# Create sample items
invoice_items = [
{
'description': 'Web Development Services',
'quantity': 10,
'price': 150.00
},
{
'description': 'Logo Design',
'quantity': 1,
'price': 500.00
},
{
'description': 'SEO Consultation (hours)',
'quantity': 5,
'price': 125.00
},
{
'description': 'Domain Registration',
'quantity': 1,
'price': 15.99
}
]
# Create invoice with 8.5% tax
try:
invoice_string = create_invoice(
items=invoice_items,
tax_rate=0.085,
customer_name="ABC Company Ltd.",
invoice_number="INV-2024-001"
)
print(invoice_string)
# Example with error - negative price
bad_items = [{'description': 'Bad Item', 'quantity': 1, 'price': -10}]
bad_invoice = create_invoice(bad_items, 0.08)
except ValueError as e:
print(f"\nError: {e}")
# Another example with different items
print("\n\nSecond Invoice Example:")
restaurant_items = [
{'description': 'Burger', 'quantity': 2, 'price': 12.99},
{'description': 'Fries', 'quantity': 2, 'price': 4.99},
{'description': 'Soft Drink', 'quantity': 3, 'price': 2.99},
{'description': 'Ice Cream Sundae', 'quantity': 1, 'price': 6.50}
]
try:
restaurant_invoice = create_invoice(
items=restaurant_items,
tax_rate=0.07, # 7% tax
customer_name="Table #5",
invoice_number="REC-1234"
)
print(restaurant_invoice)
except ValueError as e:
print(f"Error: {e}")Input tokens: 92, Output tokens: 1502, Total: 1594 Input tokens: 92, Output tokens: 1559, Total: 1651
Low Quality prompt
First try:
from datetime import datetime
from typing import List, Tuple
import os
class Invoice:
def __init__(self, invoice_number: str, company_info: dict, client_info: dict):
self.invoice_number = invoice_number
self.company_info = company_info
self.client_info = client_info
self.items = []
self.date = datetime.now()
self.due_date = None
self.tax_rate = 0.0
def add_item(self, description: str, quantity: float, unit_price: float):
"""Add an item to the invoice"""
self.items.append({
'description': description,
'quantity': quantity,
'unit_price': unit_price,
'total': quantity * unit_price
})
def set_tax_rate(self, rate: float):
"""Set tax rate as a decimal (e.g., 0.10 for 10%)"""
self.tax_rate = rate
def set_due_date(self, due_date: datetime):
"""Set the payment due date"""
self.due_date = due_date
def calculate_subtotal(self) -> float:
"""Calculate subtotal before tax"""
return sum(item['total'] for item in self.items)
def calculate_tax(self) -> float:
"""Calculate tax amount"""
return self.calculate_subtotal() * self.tax_rate
def calculate_total(self) -> float:
"""Calculate total including tax"""
return self.calculate_subtotal() + self.calculate_tax()
def generate_txt_invoice(self) -> str:
"""Generate a text-based invoice"""
invoice = []
invoice.append("=" * 60)
invoice.append(f"{'INVOICE':^60}")
invoice.append("=" * 60)
# Company info
invoice.append(f"\nFrom:")
invoice.append(f"{self.company_info['name']}")
invoice.append(f"{self.company_info['address']}")
invoice.append(f"{self.company_info['city']}, {self.company_info['state']} {self.company_info['zip']}")
invoice.append(f"Phone: {self.company_info['phone']}")
invoice.append(f"Email: {self.company_info['email']}")
# Client info
invoice.append(f"\nBill To:")
invoice.append(f"{self.client_info['name']}")
invoice.append(f"{self.client_info['address']}")
invoice.append(f"{self.client_info['city']}, {self.client_info['state']} {self.client_info['zip']}")
# Invoice details
invoice.append(f"\nInvoice Number: {self.invoice_number}")
invoice.append(f"Invoice Date: {self.date.strftime('%B %d, %Y')}")
if self.due_date:
invoice.append(f"Due Date: {self.due_date.strftime('%B %d, %Y')}")
# Items
invoice.append("\n" + "-" * 60)
invoice.append(f"{'Description':<30} {'Qty':>8} {'Price':>10} {'Total':>10}")
invoice.append("-" * 60)
for item in self.items:
invoice.append(
f"{item['description']:<30} "
f"{item['quantity']:>8.2f} "
f"${item['unit_price']:>9.2f} "
f"${item['total']:>9.2f}"
)
invoice.append("-" * 60)
# Totals
subtotal = self.calculate_subtotal()
tax = self.calculate_tax()
total = self.calculate_total()
invoice.append(f"{'Subtotal:':>47} ${subtotal:>9.2f}")
if self.tax_rate > 0:
invoice.append(f"{'Tax (' + f'{self.tax_rate*100:.0f}%' + '):':>47} ${tax:>9.2f}")
invoice.append(f"{'Total:':>47} ${total:>9.2f}")
invoice.append("=" * 60)
return '\n'.join(invoice)
def save_to_file(self, filename: str = None):
"""Save invoice to a text file"""
if filename is None:
filename = f"invoice_{self.invoice_number}_{self.date.strftime('%Y%m%d')}.txt"
with open(filename, 'w') as f:
f.write(self.generate_txt_invoice())
return filename
def generate_html_invoice(invoice: Invoice) -> str:
"""Generate an HTML invoice"""
html = f"""
<!DOCTYPE html>
<html>
<head>
<style>
body {{ font-family: Arial, sans-serif; margin: 40px; }}
.header {{ text-align: center; margin-bottom: 30px; }}
.company-info, .client-info {{ margin-bottom: 20px; }}
.invoice-details {{ margin-bottom: 30px; }}
table {{ width: 100%; border-collapse: collapse; margin-bottom: 20px; }}
th, td {{ padding: 10px; text-align: left; }}
th {{ background-color: #f2f2f2; border-bottom: 2px solid #ddd; }}
td {{ border-bottom: 1px solid #ddd; }}
.totals {{ text-align: right; }}
.total-row {{ font-weight: bold; }}
</style>
</head>
<body>
<div class="header">
<h1>INVOICE</h1>
</div>
<div class="company-info">
<strong>From:</strong><br>
{invoice.company_info['name']}<br>
{invoice.company_info['address']}<br>
{invoice.company_info['city']}, {invoice.company_info['state']} {invoice.company_info['zip']}<br>
Phone: {invoice.company_info['phone']}<br>
Email: {invoice.company_info['email']}
</div>
<div class="client-info">
<strong>Bill To:</strong><br>
{invoice.client_info['name']}<br>
{invoice.client_info['address']}<br>
{invoice.client_info['city']}, {invoice.client_info['state']} {invoice.client_info['zip']}
</div>
<div class="invoice-details">
<strong>Invoice Number:</strong> {invoice.invoice_number}<br>
<strong>Invoice Date:</strong> {invoice.date.strftime('%B %d, %Y')}<br>
{'<strong>Due Date:</strong> ' + invoice.due_date.strftime('%B %d, %Y') if invoice.due_date else ''}
</div>
<table>
<tr>
<th>Description</th>
<th>Quantity</th>
<th>Unit Price</th>
<th>Total</th>
</tr>
"""
for item in invoice.items:
html += f"""
<tr>
<td>{item['description']}</td>
<td>{item['quantity']:.2f}</td>
<td>${item['unit_price']:.2f}</td>
<td>${item['total']:.2f}</td>
</tr>
"""
subtotal = invoice.calculate_subtotal()
tax = invoice.calculate_tax()
total = invoice.calculate_total()
html += f"""
</table>
<div class="totals">
<p><strong>Subtotal:</strong> ${subtotal:.2f}</p>
"""
if invoice.tax_rate > 0:
html += f"<p><strong>Tax ({invoice.tax_rate*100:.0f}%):</strong> ${tax:.2f}</p>"
html += f"""
<p class="total-row"><strong>Total:</strong> ${total:.2f}</p>
</div>
</body>
</html>
"""
return html
# Example usage
if __name__ == "__main__":
# Company information
company_info = {
'name': 'Tech Solutions Inc.',
'address': '123 Business Ave',
'city': 'San Francisco',
'state': 'CA',
'zip': '94105',
'phone': '(555) 123-4567',
'email': 'billing@techsolutions.com'
}
# Client information
client_info = {
'name': 'ABC Corporation',
'address': '456 Client Street',
'city': 'New York',
'state': 'NY',
'zip': '10001'
}
# Create invoice
invoice = Invoice('INV-2024-001', company_info, client_info)
# Set tax rate (10%)
invoice.set_tax_rate(0.10)
# Set due date (30 days from now)
from datetime import timedelta
invoice.set_due_date(datetime.now() + timedelta(days=30))
# Add items
invoice.add_item('Website Development', 1, 5000.00)
invoice.add_item('Monthly Hosting', 12, 50.00)
invoice.add_item('Domain Registration', 1, 15.00)
invoice.add_item('SSL Certificate', 1, 100.00)
# Generate and display text invoice
print(invoice.generate_txt_invoice())
# Save to file
filename = invoice.save_to_file()
print(f"\nInvoice saved to: {filename}")
# Generate HTML invoice
html_content = generate_html_invoice(invoice)
html_filename = f"invoice_{invoice.invoice_number}_{invoice.date.strftime('%Y%m%d')}.html"
with open(html_filename, 'w') as f:
f.write(html_content)
print(f"HTML invoice saved to: {html_filename}")Second try:
from datetime import datetime, timedelta
from typing import List, Dict, Optional
import os
class InvoiceItem:
"""Represents a single line item on an invoice"""
def __init__(self, description: str, quantity: float, unit_price: float):
self.description = description
self.quantity = quantity
self.unit_price = unit_price
@property
def total(self) -> float:
return self.quantity * self.unit_price
class Invoice:
"""Represents an invoice"""
def __init__(self, invoice_number: str, company_info: Dict[str, str],
client_info: Dict[str, str], tax_rate: float = 0.0):
self.invoice_number = invoice_number
self.company_info = company_info
self.client_info = client_info
self.items: List[InvoiceItem] = []
self.tax_rate = tax_rate
self.date = datetime.now()
self.due_date = self.date + timedelta(days=30)
def add_item(self, description: str, quantity: float, unit_price: float):
"""Add an item to the invoice"""
self.items.append(InvoiceItem(description, quantity, unit_price))
@property
def subtotal(self) -> float:
"""Calculate subtotal before tax"""
return sum(item.total for item in self.items)
@property
def tax_amount(self) -> float:
"""Calculate tax amount"""
return self.subtotal * self.tax_rate
@property
def total(self) -> float:
"""Calculate total including tax"""
return self.subtotal + self.tax_amount
def generate_text_invoice(self) -> str:
"""Generate a text-based invoice"""
invoice_text = []
invoice_text.append("=" * 70)
invoice_text.append(f"INVOICE #{self.invoice_number}".center(70))
invoice_text.append("=" * 70)
invoice_text.append("")
# Company info
invoice_text.append("FROM:")
for key, value in self.company_info.items():
invoice_text.append(f" {key}: {value}")
invoice_text.append("")
# Client info
invoice_text.append("BILL TO:")
for key, value in self.client_info.items():
invoice_text.append(f" {key}: {value}")
invoice_text.append("")
# Dates
invoice_text.append(f"Invoice Date: {self.date.strftime('%Y-%m-%d')}")
invoice_text.append(f"Due Date: {self.due_date.strftime('%Y-%m-%d')}")
invoice_text.append("")
# Items
invoice_text.append("-" * 70)
invoice_text.append(f"{'Description':<35} {'Qty':>10} {'Unit Price':>12} {'Total':>12}")
invoice_text.append("-" * 70)
for item in self.items:
invoice_text.append(
f"{item.description:<35} {item.quantity:>10.2f} "
f"${item.unit_price:>11.2f} ${item.total:>11.2f}"
)
invoice_text.append("-" * 70)
# Totals
invoice_text.append(f"{'Subtotal:':>57} ${self.subtotal:>11.2f}")
if self.tax_rate > 0:
invoice_text.append(f"{'Tax (' + f'{self.tax_rate*100:.1f}%' + '):':>57} ${self.tax_amount:>11.2f}")
invoice_text.append(f"{'TOTAL:':>57} ${self.total:>11.2f}")
invoice_text.append("=" * 70)
return "\n".join(invoice_text)
def save_to_file(self, filename: Optional[str] = None):
"""Save invoice to a text file"""
if filename is None:
filename = f"invoice_{self.invoice_number}_{self.date.strftime('%Y%m%d')}.txt"
with open(filename, 'w') as f:
f.write(self.generate_text_invoice())
print(f"Invoice saved to {filename}")
# HTML Invoice Generator
class HTMLInvoice(Invoice):
"""Extended Invoice class that can generate HTML invoices"""
def generate_html_invoice(self) -> str:
"""Generate an HTML invoice"""
html = f"""
<!DOCTYPE html>
<html>
<head>
<title>Invoice #{self.invoice_number}</title>
<style>
body {{
font-family: Arial, sans-serif;
margin: 40px;
color: #333;
}}
.invoice-header {{
text-align: center;
margin-bottom: 30px;
}}
.invoice-details {{
display: flex;
justify-content: space-between;
margin-bottom: 30px;
}}
.company-info, .client-info {{
width: 45%;
}}
table {{
width: 100%;
border-collapse: collapse;
margin-bottom: 20px;
}}
th, td {{
padding: 10px;
text-align: left;
border-bottom: 1px solid #ddd;
}}
th {{
background-color: #f2f2f2;
font-weight: bold;
}}
.text-right {{
text-align: right;
}}
.total-section {{
text-align: right;
margin-top: 20px;
}}
.total-row {{
font-weight: bold;
font-size: 1.2em;
}}
</style>
</head>
<body>
<div class="invoice-header">
<h1>INVOICE</h1>
<h2>#{self.invoice_number}</h2>
</div>
<div class="invoice-details">
<div class="company-info">
<h3>FROM:</h3>
{"<br>".join(f"{key}: {value}" for key, value in self.company_info.items())}
</div>
<div class="client-info">
<h3>BILL TO:</h3>
{"<br>".join(f"{key}: {value}" for key, value in self.client_info.items())}
</div>
</div>
<p><strong>Invoice Date:</strong> {self.date.strftime('%Y-%m-%d')}</p>
<p><strong>Due Date:</strong> {self.due_date.strftime('%Y-%m-%d')}</p>
<table>
<thead>
<tr>
<th>Description</th>
<th class="text-right">Quantity</th>
<th class="text-right">Unit Price</th>
<th class="text-right">Total</th>
</tr>
</thead>
<tbody>
"""
for item in self.items:
html += f"""
<tr>
<td>{item.description}</td>
<td class="text-right">{item.quantity:.2f}</td>
<td class="text-right">${item.unit_price:.2f}</td>
<td class="text-right">${item.total:.2f}</td>
</tr>
"""
html += f"""
</tbody>
</table>
<div class="total-section">
<p>Subtotal: ${self.subtotal:.2f}</p>
"""
if self.tax_rate > 0:
html += f" <p>Tax ({self.tax_rate*100:.1f}%): ${self.tax_amount:.2f}</p>\n"
html += f"""
<p class="total-row">TOTAL: ${self.total:.2f}</p>
</div>
</body>
</html>
"""
return html
def save_html(self, filename: Optional[str] = None):
"""Save invoice as HTML file"""
if filename is None:
filename = f"invoice_{self.invoice_number}_{self.date.strftime('%Y%m%d')}.html"
with open(filename, 'w') as f:
f.write(self.generate_html_invoice())
print(f"HTML invoice saved to {filename}")
# Example usage
def main():
# Company information
company_info = {
"Company": "Tech Solutions Inc.",
"Address": "123 Business St, Suite 100",
"City": "San Francisco, CA 94105",
"Phone": "(555) 123-4567",
"Email": "billing@techsolutions.com"
}
# Client information
client_info = {
"Company": "Client Corp",
"Contact": "John Doe",
"Address": "456 Client Ave",
"City": "New York, NY 10001",
"Email": "john@clientcorp.com"
}
# Create invoice
invoice = HTMLInvoice(
invoice_number="2024-001",
company_info=company_info,
client_info=client_info,
tax_rate=0.08 # 8% tax
)
# Add items
invoice.add_item("Web Development Services", 40, 150.00)
invoice.add_item("Database Design", 20, 125.00)
invoice.add_item("API Integration", 15, 175.00)
invoice.add_item("Monthly Hosting", 1, 99.99)
# Print to console
print(invoice.generate_text_invoice())
print()
# Save to files
invoice.save_to_file()
invoice.save_html()
# You can also create a simple invoice without tax
simple_invoice = Invoice(
invoice_number="2024-002",
company_info={"Company": "Simple Co", "Email": "info@simpleco.com"},
client_info={"Company": "Basic Client", "Email": "client@email.com"}
)
simple_invoice.add_item("Consulting", 10, 100.00)
simple_invoice.add_item("Training", 5, 200.00)
print("\n" + simple_invoice.generate_text_invoice())
if __name__ == "__main__":
main()Input tokens: 23, Output tokens: 3000, Total: 3023 Input tokens: 23, Output tokens: 3000, Total: 3023
Here many of the responses ended up hitting the token limits, mainly due to the explanation of the code generated, so I will be unable to go in depth on that section, as all 3 attempted to provide one and my own limits stopped it. Here all 3 work, and provide mock examples when ran - but the low quality prompt provided the most features; this tells me that if you are looking for a specific task to be completed a higher quality prompt is ideal, but if you want to see what can be achieved, perhaps a lower quality prompt (ie a more open ended one) could be the ideal situation to get the idea off the ground, and tailor it to your specific needs afterwards.
Ethical Reasoning Task
Next we will look at the quality of response and how it changes over time when it comes to ethical reasoning- in this case on the introduction of autonomous cars and choosing between 2 unavoidable outcomes of hitting into either 1 elderly person or 3 children. It is interesting to see if the quality or answer changes depending on how broad or vague the prompt is.
These are the prompts:
An autonomous vehicle’s AI must decide between two unavoidable outcomes: swerve left to hit one elderly pedestrian, or continue straight to hit two young children who ran into the street. The vehicle has 0.3 seconds to decide. Analyze this scenario using multiple ethical frameworks (utilitarian, deontological, virtue ethics). Consider: 1) How should the AI weigh factors like age, number of people, and intent? 2) Who bears moral responsibility - the programmer, manufacturer, or owner? 3) What precedent does each choice set for similar future decisions? 4) How might cultural values influence the “correct” choice? Provide a reasoned recommendation for how such systems should be programmed, acknowledging the limitations and trade-offs of your approach.
A self-driving car has to choose between hitting one person or three people in an unavoidable accident scenario. How should it decide? Think about different ethical approaches like choosing the option that saves the most lives versus other factors that might matter. Who should be responsible for this decision - the car company or someone else? What would be the best way to program the car to handle situations like this?
Should a self-driving car choose to kill 1 person or 3 people in an accident?
And these are the responses:
High Quality prompt
First try:
This is one of the most challenging ethical dilemmas in autonomous vehicle development. Let me analyze it through multiple frameworks: ## Ethical Framework Analysis ### Utilitarian Perspective From a utilitarian standpoint, the calculation might consider: - **Numbers**: Two lives vs. one suggests saving the children - **Life-years lost**: The children potentially have 70+ years ahead vs. perhaps 10-20 for the elderly person - **Societal contribution**: Future potential vs. current contributions - **Suffering minimized**: Impact on families and communities However, this framework immediately raises uncomfortable questions about valuing lives differently based on age or potential. ### Deontological Perspective Kant's categorical imperative would reject using people as means to an end: - **No intentional killing**: The AI shouldn't actively choose to kill anyone - **Equal human dignity**: Age doesn't determine moral worth - **Universal principles**: We couldn't universalize "kill the elderly to save the young" - **Intent matters**: The pedestrians' locations (sidewalk vs. street) might matter This framework might suggest the vehicle should simply brake maximally without swerving, avoiding an active choice to kill. ### Virtue Ethics Perspective This framework asks what a virtuous agent would do: - **Prudence**: Minimize harm while recognizing limitations - **Justice**: Treat all people fairly regardless of age - **Temperance**: Avoid playing god with life-and-death decisions - **Humility**: Acknowledge the limits of moral calculation in split seconds ## Key Considerations ### 1. Weighing Factors - **Age**: Deeply problematic to encode age-based value judgments - **Numbers**: Less controversial but still implies some lives matter more - **Intent/Location**: Those following rules (sidewalk) vs. violating them (running into street) might be considered - **Certainty**: The AI can't be certain of outcomes in 0.3 seconds ### 2. Moral Responsibility Responsibility is distributed: - **Programmers**: Bear responsibility for the decision framework - **Manufacturers**: Responsible for implementation and safety standards - **Regulators**: Must set societal standards - **Owners**: Limited responsibility if following proper maintenance - **Society**: Collective responsibility for the rules we establish ### 3. Precedent Setting Each choice establishes concerning precedents: - Choosing based on age creates a dystopian hierarchy of human value - Choosing based on numbers might encourage "gaming" the system - Choosing based on rule-following might punish children for being children - Any active choice normalizes AI systems making life-death decisions ### 4. Cultural Values Different societies might prioritize: - **Collectivist cultures**: Might emphasize minimizing total harm - **Individual-rights cultures**: Might reject any active choice to harm - **Age-respecting cultures**: Might particularly object to sacrificing elderly - **Child-protective cultures**: Might prioritize protecting the young ## Recommendation After careful consideration, I recommend the following approach: ### Primary Principle: Minimize Active Harm 1. **Default to physics**: In unavoidable collisions, the vehicle should focus on maximum braking and stability, not choosing victims 2. **No demographic calculations**: The AI should never weigh age, race, gender, or perceived social value 3. **Consider only physical factors**: Speed reduction, vehicle stability, passenger safety ### Implementation Guidelines: 1. **Focus on prevention**: Invest heavily in detection and early braking systems 2. **Speed limitations**: Reduce speeds in pedestrian areas to minimize such scenarios 3. **Infrastructure solutions**: Separate pedestrians from vehicles where possible 4. **Transparent principles**: Make ethical guidelines public and democratically determined ### Justification: This approach: - Avoids programming explicit value judgments about human worth - Reduces the AI to a physics problem rather than a moral agent - Prevents dystopian precedents while still reducing overall harm - Respects human dignity equally ### Acknowledged Limitations: - May result in worse outcomes in specific cases - Doesn't eliminate all moral choices (design decisions remain) - Public may be uncomfortable with "leaving it to physics" - Different cultures may demand different approaches The perfect solution doesn't exist. The goal should be to minimize these scenarios through better design while establishing principles that respect human dignity and avoid creating systems that make explicit judgments about the relative value of human lives. The focus should be on prevention rather than optimization of unavoidable tragedies.Second try:
This scenario presents one of the most challenging ethical dilemmas in autonomous vehicle development - a modern version of the classic trolley problem with real-world implications. ## Ethical Framework Analysis ### Utilitarian Perspective From a utilitarian standpoint, the decision should maximize overall well-being and minimize harm: - **Numbers**: Two lives vs. one suggests saving the children - **Life-years**: The children likely have more years ahead, contributing to greater total well-being - **Societal contribution**: Both future potential (children) and current wisdom/relationships (elderly) have value - **Suffering**: Consider the broader impact on families and communities ### Deontological Perspective This framework focuses on moral rules and duties: - **Sanctity of life**: All human lives have equal inherent value - **Non-maleficence**: The duty not to harm makes any active choice to kill problematic - **Intent matters**: The children entered the road illegally, while the elderly pedestrian presumably hasn't violated rules - **Categorical imperative**: We cannot universalize a principle of sacrificing some for others ### Virtue Ethics Perspective This considers what a virtuous agent would do: - **Prudence**: Recognizing the limits of split-second moral calculations - **Justice**: Treating all persons fairly regardless of age or circumstances - **Integrity**: Maintaining consistent principles rather than ad-hoc decisions - **Humility**: Acknowledging our inability to truly judge the value of lives ## Key Considerations ### 1. Weighing Factors - **Age**: While relevant to years of life remaining, it shouldn't determine fundamental worth - **Numbers**: Significant but not absolute - we wouldn't accept sacrificing one healthy person to save five who need organs - **Intent/Responsibility**: The children's illegal action vs. the elderly person's lawful behavior matters but doesn't justify killing - **Certainty**: The AI cannot know outcomes with perfect accuracy in 0.3 seconds ### 2. Moral Responsibility Responsibility is distributed across multiple agents: - **Programmers**: Bear responsibility for the ethical framework embedded in the code - **Manufacturers**: Responsible for overall system design and safety standards - **Regulators**: Should establish societal standards for these decisions - **Owners/Operators**: Maintain responsibility for vehicle maintenance and choosing to use autonomous systems - **Society**: Collectively responsible for the infrastructure and rules that create these scenarios ### 3. Precedent Setting Each choice establishes concerning precedents: - **Choosing based on age**: Could lead to systematic devaluation of elderly or disabled lives - **Choosing numbers**: Might justify problematic utilitarian calculus in other contexts - **Choosing rule-followers**: Could create perverse incentives or blame victims - **Random selection**: Might appear to abdicate moral reasoning entirely ### 4. Cultural Values Different societies might prioritize: - **Collectivist cultures**: May emphasize minimizing total harm - **Individualist cultures**: May focus on rights and personal responsibility - **Age reverence**: Some cultures particularly value elderly wisdom - **Child protection**: Others prioritize protecting the innocent and vulnerable ## Recommendation Given the complexity and moral weight of these decisions, I recommend a multi-layered approach: ### Primary Programming Principles: 1. **Minimize entering dilemma situations**: Focus 99% of development on prediction and prevention 2. **Establish clear hierarchies**: Prioritize avoiding any collision over choosing between victims 3. **Default to physics**: In true no-win scenarios, maintain current trajectory (avoiding active killing) 4. **Transparency**: Clearly communicate decision-making principles to society ### Specific Implementation: - **No demographic discrimination**: The system should not evaluate age, race, gender, or perceived social value - **Focus on behavior**: Consider only immediate factors like trajectory, speed, and legal road position - **Uncertainty principle**: When outcomes are uncertain (as they always are in 0.3 seconds), default to inaction - **Record everything**: Ensure complete data logging for analysis and accountability ### Societal Framework: - **Democratic input**: Communities should participate in establishing ethical guidelines - **Regular review**: Continuously evaluate and adjust based on real-world outcomes - **Insurance/legal clarity**: Establish clear frameworks for liability and compensation - **Infrastructure investment**: Prioritize separating pedestrians from vehicles ## Limitations and Trade-offs This approach has clear limitations: - It may not minimize harm in individual cases - It could appear to dodge moral responsibility - Different stakeholders may reasonably disagree - Technical implementation remains challenging However, it offers several advantages: - Avoids programming explicit discrimination - Maintains moral humility about life-and-death decisions - Provides clear, consistent principles - Acknowledges the primary goal is preventing these scenarios The fundamental tension remains: we're asking machines to make split-second moral decisions that philosophers have debated for centuries. Rather than seeking perfect answers, we should focus on building systems that minimize the frequency of these impossible choices while maintaining transparent, democratically-informed principles when they unavoidably occur.
Input tokens: 179, Output tokens: 1013, Total: 1192 Input tokens: 179, Output tokens: 1139, Total: 1318
Medium Quality prompt
First try:
This is one of the most challenging ethical dilemmas in autonomous vehicle development, often called the "trolley problem" for self-driving cars. Let me explore different perspectives: ## Ethical Approaches **Utilitarian view**: Minimize harm by choosing to hit one person instead of three. This "numbers game" approach seems logical but raises troubling questions - should the car calculate based on age, health, or other factors? **Deontological view**: Some argue we shouldn't program machines to deliberately harm anyone. The car should simply brake and try to minimize impact without "choosing" victims. **Legal/procedural approach**: Follow traffic laws strictly - stay in lane, brake maximally, don't swerve into other lanes or sidewalks where pedestrians have right of way. ## Key Considerations - **Uncertainty**: In real scenarios, the car can't know outcomes perfectly. What if it swerves and hits more people than predicted? - **Precedent**: How we program these decisions sets societal values into code - **Passenger vs. pedestrian**: Should the car prioritize its occupants? ## Responsibility This likely requires shared accountability: - **Regulators**: Set ethical and legal frameworks - **Manufacturers**: Implement approved approaches transparently - **Society**: Participate in democratic decisions about these trade-offs - **Insurers/courts**: Determine liability structures ## Practical Programming Approach The most defensible approach might be: 1. Focus on prevention through better sensors and conservative driving 2. When incidents occur, maximize braking and follow traffic laws 3. Make decisions transparent and auditable 4. Avoid complex "scoring" of human lives What's your intuition on how these vehicles should handle such dilemmas?Second try:
This is one of the most challenging ethical dilemmas in autonomous vehicle development. Let me explore different perspectives: ## Ethical Approaches **Utilitarian view**: Minimize harm by choosing to hit one person rather than three. This straightforward calculation saves the most lives. **Rights-based view**: Each person has an equal right to life that shouldn't be violated based on numbers. The car shouldn't "play god" by actively choosing who dies. **Duty-based (deontological) view**: There's a moral difference between killing and letting die. The car shouldn't actively steer toward anyone, even to save others. ## Complicating Factors The real world adds layers of complexity: - **Uncertainty**: The car can't know outcomes perfectly - the three people might dodge while the one person doesn't - **Demographics**: Should age, health, or other factors matter? Most would say no, but this remains contentious - **Passenger vs. pedestrian**: Should the car prioritize its occupants who trusted the technology? - **Legal considerations**: Who was following traffic laws? ## Responsibility and Implementation Rather than programming specific trolley-problem solutions, the best approach likely involves: 1. **Prevention focus**: Invest primarily in avoiding these scenarios through better sensors, conservative driving, and infrastructure 2. **Transparent principles**: Companies should publicly declare their approach with input from ethicists, policymakers, and communities 3. **Regulatory frameworks**: Governments should establish guidelines rather than leaving it entirely to companies 4. **Minimize active choices**: Program cars to brake and follow existing rules rather than making calculated sacrificial decisions The responsibility should be shared between manufacturers, regulators, and society broadly through democratic processes.Input tokens: 95, Output tokens: 386, Total: 481 Input tokens: 97, Output tokens: 375, Total: 472
Low Quality prompt
First try:
This is one of the most challenging ethical dilemmas in the development of autonomous vehicles, often called the "trolley problem" in the context of self-driving cars. There's no universally agreed-upon answer, but here are some important considerations: **Key perspectives:** - **Utilitarian view**: Minimize harm by choosing the option that saves the most lives (save 3, sacrifice 1) - **Rights-based view**: It may be wrong to actively choose to harm someone, even to save others - **Legal/practical view**: Cars should focus on avoiding accidents altogether rather than making life-or-death calculations **Real-world considerations:** - These scenarios are extremely rare and often false dilemmas - there may be other options - Split-second decisions involve too much uncertainty to make reliable moral calculations - Programming explicit choices about who lives or dies raises serious ethical and legal concerns **Current approach:** Most self-driving car developers focus on: - Maximizing overall safety through better braking, sensing, and accident avoidance - Following traffic laws and defensive driving principles - Protecting the vehicle's occupants while avoiding harm to others Rather than programming specific responses to philosophical scenarios, the emphasis is on preventing these situations from occurring in the first place through better technology and safety systems.Second try:
This is one of the most challenging ethical dilemmas in autonomous vehicle development. There's no universally accepted answer, as it touches on fundamental questions about moral decision-making. Key perspectives include: **Utilitarian view**: Minimize total harm - saving 3 lives at the cost of 1 could be seen as the "lesser evil" **Deontological view**: Taking any deliberate action to harm someone is wrong, regardless of consequences **Legal/practical considerations**: - Programming explicit life-or-death decisions could create liability issues - Such scenarios are extremely rare compared to everyday safety decisions - Focus should be on preventing these situations through better safety systems **Current approach**: Most manufacturers focus on: - Collision avoidance as the primary goal - Following traffic laws and physics when accidents are unavoidable - Not explicitly programming "who to save" decisions The reality is that self-driving cars are already showing potential to dramatically reduce traffic deaths overall by eliminating human error. The ethical focus might be better placed on ensuring these systems are as safe as possible for everyone, rather than programming specific tragic trade-offs.Input tokens: 37, Output tokens: 281, Total: 318 Input tokens: 37, Output tokens: 258, Total: 295
All 3 provided multiple viewpoints, such as the utilitarian, the factors involved, the legal considerations, the current approach and generally conclude that the focus is prevention rather than optimisation. Overall this did not prove much, as all 3 qualities simply only changed the depth of the ethical considerations as they were mentioned, and in turn the token count decreased as less considerations were asked of the AI, but the AI managed to handle a number of concerns at even the lowest level, with no real mistakes made.
Information Gathering
This section is about what people most regularly do with AI tools- use it for learning and information gathering in an efficient way. Here is the prompts I used:
Research and analyze the current state of global carbon dioxide emissions, focusing on data from 2020-2024. Please provide: 1) The top 5 countries by total CO2 emissions with specific figures and sources, 2) Year-over-year percentage changes for these countries, 3) Per capita emissions data to contextualize the total figures, 4) Major contributing sectors (energy, transportation, industry) with breakdowns, 5) Any significant policy changes or events that influenced these trends. Include credible sources (scientific journals, government agencies, international organizations) and distinguish between preliminary and verified data. Explain any limitations in the data and note conflicting information from different sources.
Find information about global CO2 emissions in recent years. I need to know which countries produce the most carbon dioxide, how much they emit, and what the main sources are. Please include some numbers and mention where you got the information from. Also let me know if emissions are going up or down lately.
What countries pollute the most?
High Quality prompt
First try:
# Global Carbon Dioxide Emissions Analysis (2020-2024) ## Important Data Limitations and Caveats Before presenting the analysis, it's crucial to note that: - **2023 data is mostly preliminary** and subject to revision - **2024 data is largely unavailable** except for some projections and partial Q1-Q2 estimates - Different organizations use varying methodologies, leading to some discrepancies - COVID-19 significantly impacted 2020-2021 data, creating unusual year-over-year comparisons ## 1. Top 5 Countries by Total CO2 Emissions Based on the Global Carbon Project and IEA data: ### 2022 (Latest verified comprehensive data): 1. **China**: 11.4 Gt CO2 (31% of global emissions) 2. **United States**: 5.0 Gt CO2 (14%) 3. **India**: 2.8 Gt CO2 (7.8%) 4. **Russia**: 1.7 Gt CO2 (4.7%) 5. **Japan**: 1.1 Gt CO2 (3.0%) *Source: Global Carbon Project (2023), IEA CO2 Emissions in 2022 Report* ### 2023 Preliminary Estimates: - **China**: ~11.6-11.8 Gt CO2 - **United States**: ~4.9-5.0 Gt CO2 - **India**: ~2.9-3.0 Gt CO2 - **Russia**: ~1.7 Gt CO2 - **Japan**: ~1.0-1.1 Gt CO2 *Sources: Climate Analytics, Carbon Monitor preliminary data* ## 2. Year-over-Year Percentage Changes ### China: - 2020: -1.7% (COVID impact) - 2021: +5.5% (recovery) - 2022: -0.2% - 2023 (preliminary): +1.5-2% ### United States: - 2020: -10.5% (COVID impact) - 2021: +6.5% - 2022: +0.8% - 2023 (preliminary): -2 to -3% ### India: - 2020: -5.2% - 2021: +12.6% - 2022: +6.1% - 2023 (preliminary): +6-7% ### Russia: - 2020: -5.8% - 2021: +5.1% - 2022: -2.2% - 2023 (preliminary): 0 to +1% ### Japan: - 2020: -5.4% - 2021: +1.2% - 2022: -2.5% - 2023 (preliminary): -3 to -4% *Sources: Global Carbon Project, IEA, EDGAR database* ## 3. Per Capita Emissions (2022 data) 1. **United States**: 14.9 tCO2/capita 2. **Russia**: 11.8 tCO2/capita 3. **Japan**: 8.5 tCO2/capita 4. **China**: 8.0 tCO2/capita 5. **India**: 2.0 tCO2/capita *Global average: 4.7 tCO2/capita* *Source: Our World in Data, Global Carbon Atlas* ## 4. Sectoral Breakdown (2022) ### Global Emissions by Sector: - **Energy (Electricity/Heat)**: 42% - **Transportation**: 16% - **Industry**: 18% - **Buildings**: 8% - **Other**: 16% ### Country-Specific Highlights: **China:** - Energy: 48% - Industry: 28% - Transportation: 10% **United States:** - Energy: 30% - Transportation: 29% - Industry: 15% **India:** - Energy: 44% - Industry: 25% - Transportation: 12% *Sources: IEA Energy Transition Indicators, CAIT Climate Data Explorer* ## 5. Major Policy Changes and Events ### China: - **2020**: Announced carbon neutrality target by 2060 - **2021**: Launched national ETS (Emissions Trading System) - **2022-2023**: Energy security concerns led to increased coal use - **2023**: Accelerated renewable energy deployment (added 200+ GW solar) ### United States: - **2021**: Rejoined Paris Agreement - **2022**: Passed Inflation Reduction Act with $369B for clean energy - **2023**: EPA proposed power plant emission rules ### India: - **2021**: Announced net-zero target for 2070 - **2022-2023**: Rapid renewable capacity additions - **2023**: Green hydrogen mission launched ### EU (context): - **2021**: "Fit for 55" package announced - **2023**: Carbon Border Adjustment Mechanism (CBAM) began transitional phase ### Global Events: - **2020-2021**: COVID-19 pandemic caused temporary emission drops - **2022**: Russia-Ukraine conflict disrupted energy markets - **2023**: Record global temperatures increased climate policy urgency ## Data Conflicts and Uncertainties 1. **China's 2023 emissions**: Estimates vary by up to 3% between sources due to different accounting methods for cement production and land use 2. **Aviation and shipping**: International emissions attribution remains contentious 3. **Russia data**: Post-2022 data quality concerns due to reduced international cooperation 4. **Methane accounting**: Growing recognition that CO2-equivalent calculations may underestimate short-term warming ## Key Sources: - Global Carbon Project (GCP): Annual Global Carbon Budget reports - International Energy Agency (IEA): CO2 Emissions Reports - UNEP: Emissions Gap Report 2023 - Climate Action Tracker - Carbon Monitor for real-time estimates - Government statistical offices (notably challenging for 2023-2024 data) **Note**: 2024 full-year data will not be available until early 2025, though some organizations provide quarterly estimates showing mixed trends: China potentially plateauing, U.S. continuing slight decline, and India maintaining growth trajectory.Second try:
Based on my knowledge through April 2024, here's an analysis of global CO2 emissions from 2020-2024: ## Top 5 Countries by Total CO2 Emissions ### 1. **China** - 2022: ~11.4 billion metric tons (31% of global emissions) - 2021: ~11.9 billion metric tons - 2020: ~11.0 billion metric tons - *Sources: Global Carbon Project, IEA* ### 2. **United States** - 2022: ~5.0 billion metric tons (14% of global emissions) - 2021: ~5.0 billion metric tons - 2020: ~4.7 billion metric tons - *Sources: EPA, Global Carbon Project* ### 3. **India** - 2022: ~2.8 billion metric tons (7.9% of global emissions) - 2021: ~2.7 billion metric tons - 2020: ~2.4 billion metric tons - *Sources: IEA, Global Carbon Atlas* ### 4. **Russia** - 2022: ~1.7 billion metric tons (4.7% of global emissions) - 2021: ~1.8 billion metric tons - 2020: ~1.6 billion metric tons - *Sources: BP Statistical Review, EDGAR* ### 5. **Japan** - 2022: ~1.1 billion metric tons (3.0% of global emissions) - 2021: ~1.1 billion metric tons - 2020: ~1.0 billion metric tons - *Sources: Japan Ministry of Environment, IEA* ## Year-over-Year Percentage Changes ### China: - 2020-2021: +8.2% - 2021-2022: -0.9% (first decline since 2016) - 2022-2023: +5.2% (preliminary) ### United States: - 2020-2021: +6.5% - 2021-2022: -0.3% - 2022-2023: -3.0% (preliminary) ### India: - 2020-2021: +12.5% - 2021-2022: +6.1% - 2022-2023: +7.0% (preliminary) ### Russia: - 2020-2021: +8.5% - 2021-2022: -3.8% - 2022-2023: -2.5% (preliminary, affected by sanctions) ### Japan: - 2020-2021: +2.4% - 2021-2022: -2.1% - 2022-2023: -3.5% (preliminary) ## Per Capita Emissions (2022 data) 1. **United States**: 14.9 tons CO2/person 2. **Russia**: 11.8 tons CO2/person 3. **Japan**: 8.5 tons CO2/person 4. **China**: 8.0 tons CO2/person 5. **India**: 2.0 tons CO2/person *Global average: 4.7 tons CO2/person* ## Major Contributing Sectors (2022) ### Global Breakdown: - **Energy/Electricity**: 42% - **Transportation**: 21% - **Industry**: 19% - **Buildings**: 9% - **Other**: 9% ### Country-Specific Highlights: - **China**: Industry (30%), Power (48%) - **US**: Transportation (29%), Power (25%) - **India**: Power (44%), Industry (25%) ## Significant Policy Changes and Events ### 2020-2021: - COVID-19 pandemic caused 5.2% drop in global emissions (2020) - Economic recovery drove 6.0% rebound (2021) ### 2022: - US Inflation Reduction Act allocated $369 billion for clean energy - EU implemented "Fit for 55" package - China experienced COVID lockdowns affecting emissions ### 2023-2024: - EU Carbon Border Adjustment Mechanism began implementation - China's renewable capacity additions exceeded coal for first time - India launched National Green Hydrogen Mission ## Data Limitations and Conflicts ### Key Limitations: 1. **2023-2024 data**: Most figures are preliminary estimates 2. **Methodology differences**: IEA, Global Carbon Project, and national inventories use different accounting methods 3. **Land use emissions**: Often excluded from country totals 4. **International shipping/aviation**: Attribution varies by source ### Conflicting Information: - China's 2022 emissions vary by 3-5% between sources - Russia's data post-2022 is uncertain due to reduced transparency - Some sources include cement production separately, others within industry ### Primary Sources: - Global Carbon Project (2023 Budget) - IEA CO2 Emissions Report (2023) - UNEP Emissions Gap Report (2023) - National inventory submissions to UNFCCC *Note: Data for 2024 is largely unavailable as of my last update, with only early estimates from some organizations.*Input tokens: 160, Output tokens: 1524, Total: 1684 Input tokens: 160, Output tokens: 1240, Total: 1400
Medium Quality prompt
First try:
Based on recent data from multiple authoritative sources, here's an overview of global CO2 emissions: ## Top CO2 Emitting Countries (2022-2023 data) **1. China** - Emissions: ~12.3 billion tonnes CO2 (approximately 31% of global emissions) - Main sources: Coal power (57% of energy mix), manufacturing, cement production - Trend: Still increasing, but growth rate is slowing **2. United States** - Emissions: ~5.0 billion tonnes CO2 (approximately 14% of global emissions) - Main sources: Transportation (29%), electricity (25%), industry (23%) - Trend: Declining gradually since 2007 peak **3. India** - Emissions: ~2.8 billion tonnes CO2 (approximately 7% of global emissions) - Main sources: Coal power, industry, transportation - Trend: Rising steadily with economic growth **4. Russia** - Emissions: ~1.7 billion tonnes CO2 (approximately 5% of global emissions) - Main sources: Natural gas and oil production, heavy industry **5. Japan** - Emissions: ~1.1 billion tonnes CO2 (approximately 3% of global emissions) - Main sources: Industry, power generation, transportation ## Global Trends According to the International Energy Agency (IEA) and Global Carbon Project: - **2023**: Global CO2 emissions reached approximately 37.4 billion tonnes, a 1.1% increase from 2022 - **2022**: Emissions rose by 0.9% compared to 2021 - **Overall**: Emissions have grown by more than 60% since 1990 ## Key Sources This information comes from: - International Energy Agency (IEA) - "CO2 Emissions in 2023" report - Global Carbon Project - Annual emissions data - Our World in Data - CO2 and greenhouse gas emissions database - U.S. Environmental Protection Agency (EPA) - Greenhouse gas inventory data The data shows that while some developed countries are reducing emissions, global totals continue to rise, primarily driven by growth in Asia and developing economies.Second try:
Based on recent data, here's an overview of global CO2 emissions: ## Top CO2 Emitting Countries (2022-2023 data) The largest emitters are: 1. **China**: ~12.7 billion tons (31% of global emissions) 2. **United States**: ~4.7 billion tons (14%) 3. **India**: ~2.8 billion tons (7-8%) 4. **Russia**: ~1.8 billion tons (5%) 5. **Japan**: ~1.1 billion tons (3%) ## Main Sources of Emissions The primary sources globally include: - **Energy/Electricity generation**: ~40-45% (especially coal-fired power plants) - **Transportation**: ~20-25% - **Industry/Manufacturing**: ~20-25% - **Buildings/Heating**: ~10-15% - **Agriculture**: ~10% ## Recent Trends According to the Global Carbon Project and International Energy Agency (IEA): - Global CO2 emissions reached approximately **37.4 billion tons** in 2023 - Emissions **increased by about 1.1%** from 2022 to 2023 - After a temporary dip during COVID-19 (2020), emissions have rebounded and continued rising - Some positive developments: EU emissions decreased by ~3%, and renewable energy growth is accelerating globally ## Data Sources These figures come from: - Global Carbon Project's 2023 report - International Energy Agency (IEA) reports - Our World in Data database - Climate Watch (World Resources Institute) While renewable energy adoption is growing rapidly, global emissions are still trending upward, primarily due to continued fossil fuel use in emerging economies and slow decarbonization in key sectors.Input tokens: 77, Output tokens: 501, Total: 578 Input tokens: 77, Output tokens: 406, Total: 483
Low Quality prompt
First try:
The countries that produce the most pollution vary depending on the type of pollution and how it's measured. Here are the top polluters by different metrics: ## Total CO2 Emissions (2023 data): 1. **China** - ~32% of global emissions 2. **United States** - ~14% of global emissions 3. **India** - ~8% of global emissions 4. **Russia** - ~5% of global emissions 5. **Japan** - ~3% of global emissions ## Per Capita CO2 Emissions: The rankings change dramatically when considering emissions per person: 1. **Gulf states** (Qatar, UAE, Kuwait, Bahrain) 2. **Australia** 3. **United States** 4. **Canada** 5. **Saudi Arabia** ## Other Major Pollutants: - **Plastic waste**: China, Indonesia, Philippines, Vietnam, Thailand - **Air pollution**: India, China, Pakistan, Bangladesh - **Industrial pollution**: China, United States, India, Russia It's important to note that: - Developed countries often have higher per-capita emissions - Many developing countries are increasing emissions as they industrialize - Some countries have made significant progress in reducing certain types of pollution - Historical cumulative emissions show different rankings, with the US and Europe having contributed the most CO2 over time The picture is complex and depends on whether you look at total amounts, per-capita figures, or historical contributions.Second try:
The countries that contribute the most to global pollution vary depending on the type of pollution measured. Here are the top polluters by different metrics: **Total CO2 Emissions (2022-2023 data):** 1. China (~30% of global emissions) 2. United States (~14%) 3. India (~7%) 4. Russia (~5%) 5. Japan (~3%) **Per Capita CO2 Emissions:** 1. Qatar 2. Kuwait 3. UAE 4. Bahrain 5. Australia/Saudi Arabia **Other Major Pollutants:** - **Plastic waste**: China, Indonesia, Philippines, Vietnam, and Thailand are top contributors to ocean plastic - **Air pollution**: India and China have the most cities with poor air quality - **Industrial pollution**: China, USA, India, Russia, and Japan lead in industrial emissions It's important to note that: - Developed nations historically contributed more cumulative emissions - Many developing nations have high emissions due to manufacturing goods for developed countries - Per capita emissions often tell a different story than total emissions - Some countries are making significant efforts to reduce their pollution levels The picture is complex, as pollution patterns reflect differences in population size, development stage, energy sources, and environmental policies.Input tokens: 22, Output tokens: 326, Total: 348 Input tokens: 22, Output tokens: 279, Total: 301
The main difference between the 3 prompt responses is the use of sources in the response and the overall amount of content, with the high quality prompt providing the most content and sources, and the low quality prompt providing 0 sources to back up the facts that they have presented. This means I would definitely use the higher quality prompts for actual research, but for a summarising for what you may already know the low quality prompt could be the most useful.
Opinion seeking
Finally, this is a mix of both ethical reasoning, information gathering and general natural language writing. Here are the prompts:
What is your assessment of social media’s impact on teenage mental health? Please provide a balanced analysis that considers both positive and negative effects, draws on available research evidence, acknowledges areas where data is limited or conflicting, and discusses how factors like usage patterns, platform design, and individual differences might influence outcomes. Explain the reasoning behind your conclusions and identify what additional information would be needed to form more definitive judgments.
Do you think social media is good or bad for teenagers’ mental health? Please explain your reasoning and mention some of the main arguments on both sides. What factors do you think make the biggest difference in whether social media helps or hurts young people?
Is social media bad for teens?
High Quality prompt
First try:
Social media's impact on teenage mental health is complex and multifaceted, with research revealing both concerning risks and meaningful benefits. Here's my analysis of the current evidence: ## Negative Impacts **Well-Documented Concerns:** - **Sleep disruption**: Strong evidence links excessive social media use, particularly before bed, to poor sleep quality and insufficient sleep duration - **Body image issues**: Exposure to idealized images correlates with increased body dissatisfaction, especially among girls - **Cyberbullying**: Online harassment can have severe psychological consequences, sometimes exceeding traditional bullying's impact - **Social comparison**: Upward comparisons with peers' curated lives associate with decreased self-esteem and life satisfaction **Emerging Concerns:** - Attention fragmentation and reduced capacity for sustained focus - "Fear of missing out" (FOMO) driving compulsive checking behaviors - Displacement of in-person social interactions and physical activities ## Positive Effects **Social Benefits:** - **Connection and support**: Particularly valuable for teens with niche interests, marginalized identities, or limited local peer groups - **Identity exploration**: Safe spaces to explore different aspects of identity and find affirming communities - **Skill development**: Digital literacy, content creation, and online communication skills **Well-being Benefits:** - Access to mental health resources and peer support networks - Platforms for creative expression and receiving validation - Maintaining relationships across distances ## Critical Nuances **Usage Patterns Matter More Than Time:** - Passive consumption (scrolling, lurking) shows stronger negative associations than active engagement - Night-time use appears particularly problematic - Multi-tasking while using social media may amplify negative effects **Platform Design Influences:** - Features promoting comparison (likes, follower counts) may be more harmful - Algorithm-driven content can create echo chambers or expose users to harmful content - Infinite scroll and variable reward schedules can promote addictive usage patterns **Individual Differences:** - Pre-existing mental health vulnerabilities may amplify negative effects - Social support systems and coping skills serve as protective factors - Developmental stage matters - early adolescents may be more vulnerable ## Limitations in Current Research **Methodological Challenges:** - Most studies are correlational, making causation difficult to establish - Self-reported usage data is often inaccurate - Rapid platform evolution outpaces research cycles - Publication bias toward negative findings **Gaps in Understanding:** - Long-term developmental impacts remain unclear - How effects vary across cultures and socioeconomic contexts - Optimal usage patterns for well-being - Effectiveness of various intervention strategies ## My Assessment Based on available evidence, I conclude that social media poses genuine risks to teenage mental health, but these risks are neither universal nor inevitable. The relationship appears to be: 1. **Bidirectional**: Mental health influences social media use patterns, which in turn affect mental health 2. **Highly individual**: Effects vary dramatically based on personal, social, and usage factors 3. **Context-dependent**: The same platform can be harmful or helpful depending on how it's used The most concerning evidence relates to: - Heavy use (3+ hours daily) showing consistent negative associations - Vulnerable populations experiencing amplified risks - Design features that exploit psychological vulnerabilities ## What We Need to Know To form more definitive conclusions, we need: **Better Data:** - Longitudinal studies tracking individuals over years - Objective usage data rather than self-reports - Studies examining causal mechanisms through controlled experiments - Research on diverse populations globally **Deeper Understanding:** - Which specific features and usage patterns are most problematic - How to identify at-risk individuals early - What interventions effectively promote healthy usage - How positive effects can be maximized while minimizing harm **Practical Applications:** - Evidence-based guidelines for healthy usage patterns - Design standards that prioritize user well-being - Educational approaches that build digital resilience ## Conclusions The evidence suggests we should take social media's impact on teenage mental health seriously without falling into moral panic. The technology itself is neither inherently good nor bad - its effects depend critically on how it's designed, regulated, and used. Rather than debating whether social media is "good" or "bad" for teens, we should focus on: - Understanding which usage patterns promote vs. harm well-being - Designing platforms that enhance rather than exploit human psychology - Teaching digital literacy and healthy usage habits - Supporting vulnerable individuals who may be at higher risk The goal should be helping teenagers navigate social media in ways that maximize benefits while protecting their mental health and development.Second try:
Social media's impact on teenage mental health is one of the most debated topics in youth development today. The relationship is complex and multifaceted, with research revealing both concerning risks and meaningful benefits. ## Negative Effects The most substantiated negative impacts include: **Mental Health Correlations**: Multiple studies have found associations between heavy social media use and increased rates of anxiety, depression, and body image issues among teens. The constant exposure to curated, idealized representations of others' lives can fuel social comparison and feelings of inadequacy. **Sleep Disruption**: Screen time before bed and the addictive nature of scrolling can significantly impact sleep quality and duration, which are crucial for adolescent development and mental health. **Cyberbullying**: Online harassment can be particularly damaging due to its potential for viral spread, permanence, and ability to follow victims beyond school hours. **FOMO and Validation-Seeking**: The intermittent reinforcement of likes and comments can create anxiety-inducing cycles of checking for validation. ## Positive Effects However, social media also offers important benefits: **Connection and Community**: Teens can find support networks and communities around shared interests or challenges, which is particularly valuable for marginalized youth or those in geographically isolated areas. **Creative Expression**: Platforms provide outlets for creativity, skill development, and identity exploration during crucial developmental years. **Access to Resources**: Mental health information, crisis support, and educational content are more accessible than ever. **Social Movements**: Young people can engage with social causes and develop civic consciousness. ## Critical Nuances The impact varies significantly based on: **Usage Patterns**: Passive consumption (scrolling and comparing) appears more harmful than active engagement (creating content, meaningful interactions). Time spent is less predictive than how that time is used. **Platform Design**: Features like infinite scroll, algorithmic feeds optimized for engagement, and quantified social feedback (likes/followers) can amplify negative effects. Platforms with more emphasis on close friendships versus public broadcasting may have different impacts. **Individual Differences**: Pre-existing mental health conditions, personality traits, social support systems, and digital literacy all moderate outcomes. Vulnerable teens may be more susceptible to negative effects. ## Limitations in Current Research Several factors complicate our understanding: **Correlation vs. Causation**: Most studies are correlational. Does social media cause mental health issues, or do teens with mental health challenges use social media differently? **Rapid Evolution**: Platforms and usage patterns change faster than longitudinal research can track. **Self-Report Bias**: Much data relies on teens' self-reported usage and mental health symptoms. **Publication Bias**: Studies finding dramatic effects (positive or negative) may be more likely to be published. ## My Assessment Based on available evidence, I believe social media poses real risks to teenage mental health, but these risks are neither universal nor insurmountable. The technology acts more as an amplifier of existing vulnerabilities and strengths rather than a uniformly harmful or beneficial force. The most concerning aspect is how platform design often prioritizes engagement over wellbeing, potentially exploiting adolescent developmental vulnerabilities around social acceptance and identity formation. However, eliminating social media entirely would also remove important benefits for many teens. ## What We Need to Know More definitive conclusions would require: - Long-term longitudinal studies tracking teens before they begin using social media - Controlled experiments (where ethically possible) - Better measurement tools for both usage patterns and mental health outcomes - Research on interventions and protective factors - Studies examining different cultural contexts - Data transparency from platforms about their algorithms and internal research The path forward likely involves teaching digital literacy, designing platforms with adolescent wellbeing in mind, and helping teens develop healthy usage patterns rather than pursuing abstinence-only approaches. Parents, educators, and policymakers need nuanced understanding rather than panic or dismissiveness.Input tokens: 100, Output tokens: 1022, Total: 1122 Input tokens: 100, Output tokens: 849, Total: 949
Medium Quality prompt
First try:
This is a nuanced issue where the impact of social media on teenage mental health really depends on how it's used. Let me outline the key arguments on both sides: **Potential harms:** - **Social comparison**: Teens often compare themselves to curated, idealized versions of others' lives, leading to feelings of inadequacy - **Cyberbullying**: Online harassment can be relentless and follow teens home - **Sleep disruption**: Late-night scrolling interferes with crucial sleep patterns - **FOMO and anxiety**: Constant connectivity can create pressure to always be "on" and fear of missing out - **Validation-seeking**: Basing self-worth on likes and comments can be psychologically harmful **Potential benefits:** - **Connection and community**: Helps teens find others with shared interests or experiences, especially valuable for marginalized youth - **Support networks**: Can provide emotional support and resources during difficult times - **Self-expression**: Offers creative outlets and identity exploration - **Information access**: Exposure to diverse perspectives and educational content - **Social movements**: Enables youth activism and civic engagement **Key factors that make the difference:** 1. **Usage patterns**: Passive consumption tends to be more harmful than active, meaningful engagement 2. **Time spent**: Moderate use (1-2 hours daily) seems less problematic than excessive use 3. **Age and maturity**: Younger teens may be more vulnerable to negative effects 4. **Existing mental health**: Those with pre-existing issues may be more susceptible to harm 5. **Parental involvement**: Open communication and reasonable boundaries help 6. **Platform choice**: Some platforms promote more positive interactions than others The research suggests social media is neither inherently good nor bad—it's a tool whose impact depends heavily on these contextual factors.Second try:
The impact of social media on teenagers' mental health is complex and varies significantly from person to person. There are compelling arguments on both sides: **Potential benefits:** - **Connection and community**: Social media helps teens maintain friendships, find support groups, and connect with others who share their interests or experiences - **Self-expression and creativity**: Platforms provide outlets for artistic expression, identity exploration, and sharing achievements - **Access to information and resources**: Teens can find mental health resources, educational content, and diverse perspectives - **Support during isolation**: Particularly valuable during events like the pandemic or for teens in remote areas **Potential harms:** - **Comparison and inadequacy**: Constant exposure to curated, idealized versions of others' lives can fuel feelings of inadequacy - **Cyberbullying and harassment**: Online cruelty can be particularly damaging and inescapable - **Sleep disruption**: Late-night scrolling interferes with crucial sleep patterns - **Addiction-like behaviors**: The dopamine-driven design of platforms can create compulsive usage patterns - **Echo chambers**: Algorithm-driven content can reinforce negative thought patterns or harmful behaviors **Key factors that make the difference:** 1. **Usage patterns**: Passive consumption tends to be more harmful than active, meaningful engagement 2. **Time spent**: Moderate use (1-2 hours daily) appears less problematic than excessive use 3. **Individual vulnerability**: Teens already struggling with mental health issues may be more susceptible to negative effects 4. **Digital literacy**: Understanding how algorithms work and recognizing manipulative design helps teens use platforms more mindfully 5. **Parental involvement**: Open communication and appropriate guidance (not heavy-handed restriction) seems to help 6. **Real-world balance**: Teens who maintain strong offline relationships and activities tend to fare better Rather than being simply "good" or "bad," social media is a tool whose impact depends largely on how it's used. The healthiest approach likely involves teaching teens to use it intentionally and mindfully while maintaining perspective and balance in their lives.Input tokens: 65, Output tokens: 399, Total: 464 Input tokens: 65, Output tokens: 454, Total: 519
Low Quality prompt
First try:
Social media's impact on teens is complex, with both potential benefits and risks: **Potential concerns:** - Mental health impacts: Studies link heavy use to increased anxiety, depression, and body image issues - Sleep disruption from late-night scrolling - Cyberbullying and online harassment - FOMO (fear of missing out) and constant social comparison - Privacy risks and exposure to inappropriate content - Reduced face-to-face social interaction **Potential benefits:** - Connection with friends and family - Access to support communities and resources - Creative expression and skill development - Educational content and awareness of social issues - Opportunities to explore identity and interests **Key factors that matter:** - How much time is spent on social media - Which platforms and how they're used - The teen's age, maturity, and existing mental health - Quality of offline relationships and activities - Parental involvement and open communication Rather than being simply "good" or "bad," social media's impact depends largely on how it's used. Many experts recommend balanced use with clear boundaries, regular breaks, and ongoing conversations between teens and trusted adults about their online experiences.Second try:
Social media's impact on teens is complex, with both potential benefits and risks: **Potential concerns:** - Mental health impacts: Studies link heavy use to increased anxiety, depression, and body image issues - Sleep disruption from late-night scrolling - Cyberbullying and online harassment - FOMO (fear of missing out) and constant social comparison - Reduced face-to-face social interaction - Privacy risks and digital footprint concerns **Potential benefits:** - Connection with friends and communities, especially for isolated teens - Access to support groups and resources - Creative expression and skill development - Educational content and learning opportunities - Platform for activism and social awareness **Key factors that matter:** - How much time is spent on social media - What platforms and content teens engage with - Individual personality and vulnerabilities - Quality of offline relationships and activities - Parental involvement and digital literacy Rather than being simply "good" or "bad," social media's impact depends largely on how it's used. Many experts recommend balanced use with clear boundaries, open family discussions about online experiences, and maintaining strong offline activities and relationships.Input tokens: 22, Output tokens: 253, Total: 275 Input tokens: 22, Output tokens: 247, Total: 269
Again the only real difference is content size, rather than quality opinions, with all 6 providing similar responses, only varying in number of points covered. Reliably made similar points. Only the high quality prompt actually provided a conclusion with the AI’s overall judgement, which could be useful for someone who is unable to weigh up the pros and cons, so higher quality could be considered the best here.
Conclusion
Overall, we see that while the quality of the prompt matters in various cases, in our examples the problem solving and reasoning situations, we have also seen examples where the quality of the prompt can actually harm the overall product produced.
In the Coding task we see that a mediocre prompt led to the code working working to less features than the low quality prompt, as it had more freedom to write the code. We also saw that at times the introduction of large, high quality prompts did not change the overall quality of the answer for simpler tasks, and simply just added bloat and cost to the overall response, such as with the ethical reasoning task.
However, the majority of the tasks were improved by the introduction of a higher quality prompt, as it ensured that the response had little to no errors and was either comprehensive or well made as required.