Open Source GitHub Repository Compiles Extracted System Prompts Across Major Models from Anthropic, OpenAI, and Google

Key Takeaways

• Comprehensive Prompt Collection: The open-source GitHub repository system_prompts_leaks by author asgeirtj serves as a dedicated archive for extracted system prompts across top-tier artificial intelligence services.
• Multi-Lab Coverage: The repository compiles system instructions from premier AI developers and platforms, explicitly featuring Anthropic, OpenAI, Google, xAI, Cursor, and Kimi.
• Specific Model Lineups Included: Documented systems include Anthropic's Claude Fable 5.1, Opus 5, Claude Design, and Claude Code; OpenAI's ChatGPT GPT-6-Astra and Codex; Google's Gemini 3.8 Flash, 3.1 Pro, and Antigravity; and xAI's Grok and Grok Bot.
• Commitment to Regular Maintenance: The project maintainer actively maintains the collection, pledging regular updates as new extractions and revisions emerge across these platforms.

In-Depth Analysis

Scope and Structure of the Extracted System Prompts Repository

The repository system_prompts_leaks, curated by asgeirtj, represents an organized initiative to catalog the baseline behavioral instructions that govern leading conversational, coding, and design artificial intelligence models. System prompts act as the foundational steering layer for large language models, providing operational parameters, formatting guidelines, tone instructions, safety guardrails, and role-specific capabilities prior to processing user inputs.

The repository covers an extensive spectrum of commercial models, indicating a wide comparative scope across distinct engineering philosophies:

1. Anthropic Implementations: The repository documents extracted instructions from Anthropic's ecosystem, encompassing conversational and reasoning engines such as Claude Fable 5.1 and Claude Opus 5, alongside specialized task workflows like Claude Design and the command-line developer environment Claude Code. These prompts reflect how constitutional rules, tone settings, and tool integration instructions are structured for Anthropic's varying interfaces.
2. OpenAI Architectures: Included within the archive are system instructions extracted from OpenAI's deployments, specifically detailing ChatGPT GPT-6-Astra and Codex environments. These prompts capture the instruction-following framework, coding behavior guidance, and session management protocols applied by OpenAI.
3. Google Ecosystem: The compilation features Google systems spanning multiple tiers and operational contexts, specifically Gemini 3.8 Flash, Gemini 3.1 Pro, and Antigravity. This highlights the differing operational directives utilized across Google's latency-optimized and high-capability production configurations.
4. xAI, Cursor, and Kimi: Beyond the foundational model providers, the archive incorporates system prompts from xAI's Grok and Grok Bot interfaces, developer-focused IDE platform Cursor, and Moonshot AI's Kimi service, covering developer-centric and multi-regional implementations.

The Role of Regular Updates in Prompt Tracking

A critical aspect highlighted in the repository description is its commitment to regular updates. Production system prompts in enterprise AI environments are not static; developers frequently tweak safety rules, adjust tool definitions, refine persona attributes, and adapt to edge-case vulnerabilities over time. By maintaining an updated ledger of these instructions, the repository functions as a comparative benchmark, recording changes in how foundational developers steer their models in production environments.

Industry Impact

Transparency in Production AI Guardrails

The public aggregation of proprietary system prompts provides researchers and developers with unvarnished visibility into how leading model providers control model behaviors. While model weights and post-training datasets are frequently kept private, the extracted system prompts expose the direct linguistic rules, constraint mechanisms, and operational personas enforced by Anthropic, OpenAI, Google, xAI, and other major platforms.

Implications for Prompt Engineering and Security

For prompt engineers and security researchers, repositories like system_prompts_leaks offer concrete case studies in production-grade prompt architecture. They demonstrate how frontier organizations structure complex tool-use schemas, mitigate jailbreak attempts, and define interaction boundaries. Conversely, the continuous extraction of these prompts highlights the persistent challenge developers face in safeguarding system-level instructions against prompt extraction and indirect injection techniques.

Frequently Asked Questions

What is the purpose of the system_prompts_leaks GitHub repository?

The repository, maintained by asgeirtj, is designed to archive and systematically update extracted system prompts from leading commercial AI platforms, including Anthropic, OpenAI, Google, xAI, Cursor, and Kimi.

Which specific models are documented in the repository?

The repository specifies extracted prompts from Anthropic (Claude Fable 5.1, Opus 5, Claude Design, Claude Code), OpenAI (ChatGPT GPT-6-Astra, Codex), Google (Gemini 3.8 Flash, 3.1 Pro, Antigravity), xAI (Grok, Grok Bot), Cursor, and Kimi.

How frequently is the repository updated?

According to the original repository documentation provided by the author, the collection is subject to regular updates as new system prompts and model versions are extracted.