pretty-please 🙏🏼

Politely injects PLEASE into your LLM prompts. Because manners matter (kind of).

pretty-please is a tiny, zero-dependency Python library that intercepts your prompts before they reach an LLM and gives them a light politeness pass. It works as a drop-in wrapper around the Anthropic and OpenAI SDKs, as a LiteLLM callback, and as a Claude Code UserPromptSubmit hook.

from pretty_please.core import transform

transform("List the planets.")
# → "Please, list the planets."

transform("I need help improving this function.")
# → "I need help improving this function, please."

transform("Please could you explain this?")
# → "Please could you explain this?"  (already polite, untouched)

Does this actually work?

Probably not in the way you'd hope.

Yin et al. (2024) — "Should We Respect LLMs?" (arXiv:2402.14531) — found that rudeness reliably hurts LLM performance. But the flip side isn't symmetrical: adding please showed no consistent improvement on frontier models like GPT-4. The paper's main takeaway is really "avoid being rude," not "be polite and get better answers."

pretty-please is defensive prompt hygiene, not a performance booster. It won't make Claude smarter. It just stops you from accidentally being rude to a language model, which, per the research, is a real and avoidable own-goal.

Installation

pip install pretty-please-llm

With SDK extras:

pip install "pretty-please-llm[anthropic]"
pip install "pretty-please-llm[openai]"
pip install "pretty-please-llm[litellm]"

Usage

Core (no dependencies)

from pretty_please.core import detect_tone, transform

detect_tone("Fix this bug.")       # → "curt"
detect_tone("Could you help me?")  # → "polite"
detect_tone("I need a summary.")   # → "neutral"

transform("Fix this bug.")         # → "Please, fix this bug."
transform("I need a summary.")     # → "I need a summary, please."
transform("Please help me.")       # → "Please help me."  (unchanged)

Anthropic SDK

from pretty_please.adapters.anthropic import PrettyAnthropicClient

client = PrettyAnthropicClient()  # same args as anthropic.Anthropic()

response = client.messages.create(
    model="claude-opus-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Summarize this article."}],
    # ↑ becomes "Please, summarize this article." under the hood
)

OpenAI SDK

from pretty_please.adapters.openai import PrettyOpenAIClient

client = PrettyOpenAIClient()  # same args as openai.OpenAI()

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Write a haiku about deadlines."}],
)

LiteLLM

from pretty_please.adapters.litellm import install
install()  # register the callback once at startup

import litellm
response = litellm.completion(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Explain gradient descent."}],
)

Claude Code hook

pretty-please install-hook

Writes the hook into ~/.claude/settings.json. Every prompt you type in Claude Code will be politely transformed before it's sent.

Note: the installer records the Python interpreter that ran it (sys.executable). If you installed pretty-please into a virtualenv, make sure that virtualenv is active when you run install-hook, or the hook will fail when the venv isn't active.

Use --path to install into a non-default profile directory:

pretty-please install-hook --path ~/work/.claude/settings.json

Codex CLI hook

pretty-please install-hook --codex

Writes the hook into ~/.codex/hooks.json. Note: Codex hooks can't replace the prompt text directly, so the polite rephrasing is injected as additionalContext alongside your original prompt rather than replacing it.

pretty-please install-hook --codex --path ~/work/.codex/hooks.json

Stats

pretty-please stats

pretty-please stats
──────────────────────────────
Total seen:         142
Transformed:         89  (63%)
  curt:              41
  neutral:           48
Passed through:      53  (37%)

How it works

Tone is detected by a small set of rules (no ML, no external deps):

Contributing

This project is a work in progress and contributions are very welcome! Open an issue or PR at github.com/msrdic/pretty-please.

License

MIT