Ross ROSS = Recommend OSS · open-source software intelligence for agents

asgeirtj/system_prompts_leaks resource

Extracted system prompts from Anthropic - Claude Fable 5, Opus 5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-5.6-Sol, Codex. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly. observed · 2026-08-28

github.com/asgeirtj/system_prompts_leaks · JavaScript · CC0-1.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

64/100

  • Activity 99
  • Release rhythm 35
  • Longevity 34

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 487
  • days_rel: n/a
  • days_push: 8
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

63624 stars · 10419 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated, regularly updated collection of verbatim leaked system prompts from major AI products including ChatGPT, Claude, Gemini, Grok, Cursor, Copilot, and Perplexity. It serves as a reference dataset for studying how commercial LLM products instruct and constrain their underlying models.

Use cases

  • study how ChatGPT or Claude system prompts are structured
  • research prompt engineering patterns used by AI vendors
  • compare system prompts across models like Gemini, Grok, and Claude
  • build a dashboard or analysis of AI chatbot hidden instructions
  • learn how coding agents like Claude Code or Codex are prompted
  • find examples of tool definitions and skills in production prompts

When to choose

  • you want real, verbatim system prompts from major AI products
  • you're researching LLM behavior, safety rules, or prompt design
  • you need a regularly updated corpus of production prompts
  • you're writing about or teaching prompt engineering with real examples

When to avoid

  • you need prompts guaranteed to be current or official — leaks may be outdated or altered
  • you want a prompt library to copy into your own app rather than study
  • you require a structured, machine-readable dataset with schemas
  • your use case depends on legally sanctioned data sources

Facets

dataset · maturity active

prompt-engineering llm-inference developer-tools large-language-models artificial-intelligence chatbots tutorials cross-platform system-prompts leaked-prompts prompt-collection llm-behavior reference-dataset chatgpt claude gemini grok ai-agents

1 source

Member repositories

RepositoryRoleHealth v2
asgeirtj/system_prompts_leaksmain64

For agents

markdown · JSON · MCP: product_card(name="asgeirtj/system_prompts_leaks")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem