HubLensLLMelder-plinius/CL4R1T4S
// archived 2026-04-23
elder-plinius

CL4R1T4S

AI#LLM#Prompt Engineering#Observability#Transparency
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266

// summary

CL4R1T4S is a comprehensive repository dedicated to exposing the hidden system prompts, guidelines, and tools used by major AI models and agents. By documenting these unseen instructions, the project aims to provide users with a clearer understanding of the underlying frameworks that shape AI behavior and decision-making. The platform encourages community contributions to maintain an up-to-date collection of extracted system prompts from various industry-leading AI providers.

// technical analysis

CL4R1T4S is an open-source transparency initiative designed to expose the hidden system prompts and behavioral guidelines that govern major AI models and agents. By aggregating these extracted instructions, the project aims to demystify the 'shadow-puppet' nature of AI, allowing users to understand the ethical, political, and functional constraints imposed by developers. The project operates on the philosophy that trust in AI output requires full visibility into the input scaffolds, prioritizing public awareness over the proprietary secrecy maintained by AI labs.

// key highlights

01
Provides a comprehensive repository of extracted system prompts from industry-leading models like OpenAI, Anthropic, and Google.
02
Exposes the underlying guidelines that dictate how AI models handle refusals, redirections, and persona adoption.
03
Reveals the hidden ethical and political framing baked into AI systems to help users identify potential biases.
04
Facilitates community-driven transparency by encouraging users to contribute their own reverse-engineered prompt extractions.
05
Serves as an educational resource for understanding how AI labs manipulate model behavior through unseen instruction sets.

// use cases

01
Accessing extracted system prompts from major AI models like OpenAI, Anthropic, and Google
02
Analyzing the ethical and political frames embedded within AI system instructions
03
Contributing reverse-engineered prompt data to increase transparency in AI systems

// getting started

To begin using CL4R1T4S, explore the repository to browse the collection of extracted system prompts and guidelines for various AI models. If you have successfully extracted or reverse-engineered a system prompt, you can contribute to the project by submitting a pull request that includes the model name, the date of extraction, and any relevant context.