This repository contains a curated subset of system prompt configurations designed to function as research assistants or research agents. These prompts are extracted from my main system prompt library.
The system prompts in this repository are specifically tailored to elicit consistent and informative analytical outputs. To achieve their full potential, they often require integration with external data sources such as real-time APIs (e.g., Tavily, Perplexity) or web scraping models. Careful prompt engineering and templating are key to their effective utilization.
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Clone the repository:
git clone <repository_url> cd <repository_directory>
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Examine the Prompts: Review the individual prompt files to understand their intended function and any specific requirements.
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Integrate with External Sources: Modify the prompts to incorporate data from your chosen real-time API or scraping model. Pay close attention to the prompt's input variables and ensure they align with the data format provided by your external source.
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Execute the Prompts: Use the prompts with your preferred LLM (e.g., OpenAI, Gemini) and observe the output. Iterate on the prompt design and data integration to optimize the quality of the results.
Daniel Rosehill
(public at danielrosehill dot com)
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