system_prompts_leaks vs prompt-in-context-learning

Common questions

What is the difference between system_prompts_leaks and prompt-in-context-learning?

system_prompts_leaks: Leaked system prompts from various AI agents. prompt-in-context-learning: Resources for in-context learning and prompt engineering with LLMs like ChatGPT and GPT-3. See the comparison table for live GitHub stats and shared categories.

When should I choose system_prompts_leaks over prompt-in-context-learning?

Choose system_prompts_leaks over prompt-in-context-learning when system_prompts_leaks is primarily JavaScript; prompt-in-context-learning is Jupyter Notebook; License: system_prompts_leaks is CC0-1.0, prompt-in-context-learning is MIT; Pricing: The repository is available under the CC0-1.0 license, which means it is free to use and distribute without any restrictions. However, users should be cautious about the reliability and legality of; Requirements: Min 1 GB RAM; Users should have a basic understanding of AI agents and system prompts to effectively utilize the information provided in the repository.; It is recommended to cross-reference the information with official sources where possible to ensure accuracy and reliability.; Tags unique to system_prompts_leaks: ai-agents, ai-prompts, anthropic, chatgpt; Use system_prompts_leaks when you need to understand the underlying instructions and rules that different AI agents follow. This can be particularly useful for researchers, developers, and prompt工程师.

When should I choose prompt-in-context-learning over system_prompts_leaks?

Choose prompt-in-context-learning over system_prompts_leaks when prompt-in-context-learning is primarily Jupyter Notebook; system_prompts_leaks is JavaScript; License: prompt-in-context-learning is MIT, system_prompts_leaks is CC0-1.0; Requirements: Operates in Jupyter Notebook environments.; Tags unique to prompt-in-context-learning: ai-agent, chain-of-thought, in-context-learning, large-language-model; Use when seeking to enhance the capabilities of AI agents specifically using cutting-edge prompt engineering techniques such as those used with ChatGPT, GPT-3, or FlanT5.

When should I avoid system_prompts_leaks?

Do not use system_prompts_leaks if you are looking for official documentation or support from the AI agent providers, as the content here is based on leaked information and may not be up-to-date or Avoid relying on this repository if you need legally compliant or secure system prompts, as the repository's content is unverified and may contain inaccuracies or outdated information. Do not use this repository if you are in a regulated industry where the use of unofficial or leaked system prompts could lead to compliance issues or security vulnerabilities.

When should I avoid prompt-in-context-learning?

Not recommended if you require functionalities specific to other AI frameworks that do not align with the prompt engineering techniques focused on here. Avoid this resource if your project strictly focuses on areas outside of in-context learning and advanced LLMs like ChatGPT or GPT-3.

Is system_prompts_leaks or prompt-in-context-learning more popular on GitHub?

system_prompts_leaks has more GitHub stars (67,400 vs 2,246). Stars measure visibility, not whether either tool fits your constraints.

Are system_prompts_leaks and prompt-in-context-learning open source?

Yes - both are open-source projects on GitHub (system_prompts_leaks: CC0-1.0, prompt-in-context-learning: MIT).

Where can I find alternatives to system_prompts_leaks or prompt-in-context-learning?

GraphCanon lists graph-backed alternatives at system_prompts_leaks alternatives and prompt-in-context-learning alternatives (system_prompts_leaks markdown twin, prompt-in-context-learning markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, system_prompts_leaks or prompt-in-context-learning?

system_prompts_leaks: Very active. prompt-in-context-learning: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for system_prompts_leaks and prompt-in-context-learning?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: system_prompts_leaks trust report; prompt-in-context-learning trust report.