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jujumilk3/leaked-system-prompts

Analysis updated 2026-06-24

14,567Audience · researcherComplexity · 1/5Setup · easy

TLDR

Curated archive of leaked or reproduced system prompts from popular LLM-based products, kept honest with required sources and verification steps.

Mindmap

mindmap
  root((leaked-system-prompts))
    Inputs
      Reproducible prompt extractions
      Verified source links
      Pull requests
    Outputs
      Markdown prompt archive
      Citation friendly history
    Use Cases
      Study assistant design
      Benchmark prompt patterns
      Academic citation
    Tech Stack
      Markdown
      Git
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Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Study real production system prompts to learn how teams steer LLM assistants

USE CASE 2

Cite specific assistant configurations in academic papers about LLM behavior

USE CASE 3

Compare safety and persona patterns across ChatGPT, Claude, Gemini, and other vendors

USE CASE 4

Reproduce a prompt extraction to verify a claim against the archived version

What is it built with?

MarkdownGit

How does it compare?

jujumilk3/leaked-system-promptsmusescore/musescoregraphql/graphql-spec
Stars14,56714,56814,571
LanguageC++JavaScript
Setup difficultyeasyhardeasy
Complexity1/54/54/5
Audienceresearchergeneraldeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Pure Markdown archive, so reading it just needs git clone or a browser.

In plain English

This repository is a public archive of leaked system prompts from popular services that are built on top of large language models. A system prompt is the hidden instruction that a company gives to a chatbot or AI assistant before any user message arrives. It sets the assistant's persona, rules, and limits. Companies usually keep these prompts private, but users sometimes get the model to reveal them through clever questioning, and this repo collects those revealed prompts in one place. The README itself is short and to the point. It describes the project in two sentences and then lays out the contribution rules. The maintainer asks contributors to follow the same document format as existing entries and to include sources that can be verified, or prompts that can be reproduced by anyone else. This is the project's way of keeping the collection honest, since a prompt with no source is just a claim. For people who do not want to open a full pull request, there is a lighter option. You can post a link in the Issues section instead. If the maintainer can verify the source or reproduce the prompt, they will merge it into the main collection themselves. This lowers the barrier for casual contributors while keeping a verification step in place. The README closes with a legal note. The repository is cited in academic papers, so the maintainer wants to keep it online and avoid DMCA takedown requests from companies. Contributors are asked not to include sensitive commercial source code, only the prompt text itself. That is the entire scope of the project: a curated, source-checked, citation-friendly archive of system prompts that have escaped into public view.

Copy-paste prompts

Prompt 1
Compare the system prompts in this repo for ChatGPT and Claude and list the safety patterns each one uses
Prompt 2
Pick three assistants from this archive and summarize how each one frames its persona in under 100 words
Prompt 3
Help me design a system prompt for a coding assistant by borrowing structure from the examples in this repo
Prompt 4
Find every prompt in the repo that mentions tool use and tell me what they have in common

Frequently asked questions

What is leaked-system-prompts?

Curated archive of leaked or reproduced system prompts from popular LLM-based products, kept honest with required sources and verification steps.

How hard is leaked-system-prompts to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is leaked-system-prompts for?

Mainly researcher.

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