repo layout
├── prompt.md          ← the system prompt (main artifact)
├── CHANGELOG.md       ← rule history
├── CONTRIBUTING.md    ← how to add rules
└── TEST_RESULTS.md    ← before/after comparisons

git clone https://github.com/hexiecs/talk-normal.git
cd talk-normal

cat prompt.md

import os
from pathlib import Path
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])

system_prompt = Path("prompt.md").read_text()

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": system_prompt},
        {"role": "user",   "content": "What is Python?"},
    ],
)
print(response.choices[0].message.content)

SYSTEM=$(cat prompt.md | jq -Rs .)

curl https://api.openai.com/v1/chat/completions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"model\": \"gpt-4o-mini\",
    \"messages\": [
      {\"role\": \"system\", \"content\": $SYSTEM},
      {\"role\": \"user\",   \"content\": \"What is Python?\"}
    ]
  }"

import os
from pathlib import Path
import anthropic

client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])

system_prompt = Path("prompt.md").read_text()

message = client.messages.create(
    model="claude-opus-4-5",
    max_tokens=1024,
    system=system_prompt,
    messages=[{"role": "user", "content": "Explain Docker in one paragraph."}],
)
print(message.content[0].text)

import os
from pathlib import Path
import google.generativeai as genai

genai.configure(api_key=os.environ["GEMINI_API_KEY"])

system_prompt = Path("prompt.md").read_text()

model = genai.GenerativeModel(
    model_name="gemini-1.5-flash",
    system_instruction=system_prompt,
)

response = model.generate_content("What is a neural network?")
print(response.text)

SYSTEM=$(cat prompt.md)

ollama run llama3 \
  --system "$SYSTEM" \
  "What is a REST API?"

import subprocess, json
from pathlib import Path

system_prompt = Path("prompt.md").read_text()

result = subprocess.run(
    ["ollama", "run", "llama3"],
    input=f"SYSTEM: {system_prompt}\nUSER: What is a REST API?",
    capture_output=True, text=True,
)
print(result.stdout)

# Add to ~/.bashrc or ~/.zshrc
export TALK_NORMAL_PROMPT="$HOME/talk-normal/prompt.md"

asknormal() {
  local question="$*"
  local system
  system=$(cat "$TALK_NORMAL_PROMPT")

  curl -s https://api.openai.com/v1/chat/completions \
    -H "Authorization: Bearer $OPENAI_API_KEY" \
    -H "Content-Type: application/json" \
    -d "$(jq -n \
      --arg sys "$system" \
      --arg q   "$question" \
      '{model:"gpt-4o-mini",messages:[{role:"system",content:$sys},{role:"user",content:$q}]}'
    )" | jq -r '.choices[0].message.content'
}

source ~/.bashrc
asknormal "What is the CAP theorem?"

# Prepend talk-normal to your existing rules
cat talk-normal/prompt.md > .cursorrules
echo "" >> .cursorrules
echo "# Project-specific rules below" >> .cursorrules
cat your-existing-rules.md >> .cursorrules

import os
from pathlib import Path
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
system_prompt = Path("talk-normal/prompt.md").read_text()

assistant = client.beta.assistants.create(
    name="Normal Assistant",
    instructions=system_prompt,
    model="gpt-4o-mini",
)
print(f"Assistant ID: {assistant.id}")

from pathlib import Path

talk_normal = Path("talk-normal/prompt.md").read_text()

your_rules = """
You are a senior backend engineer. Answer questions about Python, Go, and distributed systems.
"""

combined_system = f"{talk_normal}\n\n---\n\n{your_rules}"

def verbosity_ratio(before: str, after: str) -> float:
    """Returns fraction of original length kept (lower = more concise)."""
    return len(after) / len(before)

before = "Python is a high-level, interpreted programming language known for its readability..."  # 1583 chars
after  = "Python is a high-level, interpreted language known for readability..."                  #  513 chars
print(f"{verbosity_ratio(before, after):.0%} of original length")  # → 32%

import os
from pathlib import Path
from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
system_prompt = Path("talk-normal/prompt.md").read_text()

question = "What is Kubernetes?"

def ask(system: str | None, user: str) -> str:
    messages = []
    if system:
        messages.append({"role": "system", "content": system})
    messages.append({"role": "user", "content": user})
    resp = client.chat.completions.create(model="gpt-4o-mini", messages=messages)
    return resp.choices[0].message.content

without = ask(None, question)
with_prompt = ask(system_prompt, question)

print(f"Without: {len(without)} chars")
print(f"With:    {len(with_prompt)} chars")
print(f"Reduction: {(1 - len(with_prompt)/len(without)):.0%}")

# Pull latest rules from upstream
cd talk-normal
git pull origin main

# Check what changed
git log --oneline -10
cat CHANGELOG.md | head -50

# Quick before/after test for your new rule
SYSTEM=$(cat prompt.md)
echo "Test question" | asknormal   # uses your modified prompt