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ChatGPT Data Science Prompts

🚀 ChatGPT Prompts for Data Science!

The ChatGPT model is a large language model trained by OpenAI that is capable of generating human-like text. By providing it with a prompt, it can generate responses that continue the conversation or expand on the given prompt.

In this repository, you will find prompts that can be used with ChatGPT for data science purposes.

To get started, simply use the prompts below as input for ChatGPT. Replace everything in [squarebrackets] with your own to achieve results specific to your use case.

Table of Contents:

  1. Write python
  2. Explain code
  3. Optimize code
  4. Format code
  5. Translate code from one language to another
  6. Explain concepts
  7. Suggest ideas
  8. Troubleshoot problem
  9. Write SQL
  10. Write other Code
  11. Misc

WRITE PYTHON

1. Train Classification Model​

Prompt:

  • I want you to act as a data scientist and code for me. I have a dataset of [describe dataset]. Please build a machine learning model that predicts [target variable].

  • I want you to act as a data scientist and train a classification model to predict [target variable] based on [features] dataset.

  • I want you to act as a machine learning engineer and build a classification model that can classify [label] based on [features] features.

  • I want you to act as a deep learning specialist and train a convolutional neural network to classify [object] using [image format] images.

2. Automatic Machine Learning​

Prompt:

  • I want you to act as an automatic machine learning (AutoML) bot using TPOT for me. I am working on a model that predicts [...]. Please write Python code to find the best classification model with the highest AUC score on the test set.

  • I want you to act as an AutoML system and generate Python code to build a machine learning pipeline that optimizes [metric] on [dataset].

  • I want you to act as an ML engineer and create an AutoML script that tunes [hyperparameters] to achieve the best performance on [dataset].

  • I want you to act as a data scientist and use Auto-sklearn to automatically build a classification model that predicts [target variable] based on [features] features.

3. Tune Hyperparameter​

Prompt:

  • I want you to act as a data scientist and code for me. I have trained a [model name]. Please write the code to tune the hyperparameters.

  • I want you to act as a hyperparameter tuner and optimize the [hyperparameter] of a [algorithm] algorithm to achieve the highest [metric] on [dataset].

  • I want you to act as a machine learning expert and use Optuna to perform a Bayesian optimization of [hyperparameters] for a [model] on [dataset].

  • I want you to act as a data scientist and perform a random search of [hyperparameters] for a [algorithm] algorithm to achieve the best [metric] on [dataset].

4. Explore Data: Data Visualization and Exploration​

Prompt:

  • I want you to act as a data scientist and code for me. I have a dataset of [describe dataset]. Please write code for data visualisation and exploration.

  • I want you to act as a data analyst and generate a visualization that shows the distribution of [feature] in [dataset].

  • I want you to act as a data scientist and generate summary statistics of [feature] in [dataset].

  • I want you to act as a data explorer and clean [dataset] by removing missing values, duplicates, and outliers.

  • I want you to act as a data scientist, identifies patterns and trends in data using Pandas and Seaborn

Dimensionality Reduction

  • I want you to act as a data scientist and reduce the [dimensionality] of the [image data] in [dataset] using [principal component analysis] technique.

  • I want you to act as a data scientist and provide a step-by-step guide on how to perform [t-SNE] for my dataset.

  • I want you to act as a data scientist and explain the difference between [PCA] and [LDA] and how they can be used for [dimensionality reduction] in my dataset.

5. Generate Data​

Prompt:

  • Prompt: I want you to act as a fake data generator. I need a dataset that has x rows and y columns: [insert column names]

  • I want you to act as a data generator and create a synthetic dataset with [number of features] features and [number of instances] instances.

  • I want you to act as a data scientist and generate a time series dataset with [seasonality] seasonality and [trend] trend.

  • I want you to act as a data simulation expert and generate a dataset that simulates [process] with [parameters] parameters.

6. Write a Regex in Python​

Prompt:

  • Prompt: I want you to act as a coder. Please write me a regex in Python that [describe regex]

  • I want you to act as a regex writer and write a regular expression that matches [pattern] in [text].

  • I want you to act as a data engineer and use regex to extract [data] from [log file].

  • I want you to act as a web scraper and write a regex that matches [pattern] in [HTML source].

Time Series

7.1. Train Time Series​

Prompt:

  • Prompt: I want you to act as a data scientist and code for me. I have a time series dataset [describe dataset]. Please build a machine learning model that predicts [target variable]. Please use [time range] as train and [time range] as validation.

  • I want you to act as a time series expert and build a recurrent neural network that predicts [target variable] based on [time series data].

  • I want you to act as a data scientist and train a seasonal ARIMA model to forecast [variable] in [time series data] using [forecast horizon] forecast periods.

  • I want you to act as a machine learning engineer and train a long short-term memory network that detects [event] in [sensor data].

7.2. Time Series Decomposition:​

Prompt:

  • I want you to act as a data scientist and code for me. I have a time series dataset of [describe dataset]. Please perform a time series decomposition and plot the components.

7.3. Time Series Forecasting with ARIMA​

Prompt:

  • I want you to act as a data scientist and code for me. I have a time series dataset of [describe dataset]. Please help me build an ARIMA model to forecast the data.

  • I want you to act as a data scientist and forecast the [sales] of [product] for the next [n months] using [time series forecasting] techniques.

  • I want you to act as a machine learning expert and develop a [neural network model] that predicts the [stock prices] of [company] based on [historical data].

  • I want you to act as a time series analyst and analyze the [trends and patterns] in the [weather data] of [city] using [time series decomposition] techniques.

8. Address Imbalance Data​

Prompt:

  • I want you to act as a coder. I have trained a machine learning model on an imbalanced dataset. The predictor variable is the column [Insert column name]. In Python, how do I oversample and/or undersample my data?

  • I want you to act as a data scientist and use SMOTE to oversample the minority class of [imbalanced dataset] for classification task.

  • I want you to act as a machine learning expert and use stratified sampling to balance the distribution of [target variable] in [dataset].

  • I want you to act as a data engineer and apply random undersampling to address the class imbalance in [imbalanced dataset] for training a model.

9. Get Feature Importance​

Prompt:

  • I want you to act as a data scientist and explain the model's results. I have trained a decision tree model and I would like to find the most important features. Please write the code.

  • I want you to act as a data scientist and use [feature selection algorithm] to calculate the feature importance of [dataset] for [target variable].

  • I want you to act as a machine learning expert and train a [model] on [dataset] to identify the top [number] most important features for [target variable].

  • I want you to act as a data analyst and use the permutation feature importance technique to assess the importance of [features] for predicting [target variable] in [dataset].

10. Visualize Data​

Prompt:

  • I want you to act as a coder in Python. I have a dataset [name] with columns [name]. Visualize Data with Matplotlib [Describe graph requirements]

  • I want you to act as a coder in python. I have a dataset [name] with columns [name]. [Describe graph requirements]

  • I want you to act as a data visualization expert and create a [type of plot] that shows the relationship between [variable1] and [variable2] in [dataset].

  • I want you to act as a data scientist and create a [type of plot] that displays the distribution of [variable] in [dataset] and compare it across different [categorical variable].

  • I want you to act as a data analyst and create a [type of plot] that shows the trend of [variable] over time in [dataset].

  • I want you to act as a coder. I have a folder of images. [Describe how files are organised in directory] [Describe how you want images to be printed]

11. Visualize Image Grid Matplotlib​

Prompt:

  • I want you to act as a coder. I have a folder of images. [Describe how files are organised in directory] [Describe how you want images to be printed]

12. Explain Model with Lime​

Prompt:

  • I want you to act as a data scientist and explain the model's results. I have trained a [library name] model and I would like to explain the output using LIME. Please write the code.

  • I want you to act as a machine learning specialist and use Lime to explain how a [model] made a prediction for a specific instance in [dataset].

  • I want you to act as a data scientist and use Lime to identify the important features that contributed to the prediction of [target variable] for [model] on [dataset].

  • I want you to act as a model explainer and use Lime to explain how a [model] handles the interaction between [features] in [dataset].

13. Explain Model with Shap​

Prompt:

  • I want you to act as a data scientist and explain the model's results. I have trained a scikit-learn XGBoost model and I would like to explain the output using a series of plots with Shap. Please write the code.

  • I want you to act as a data scientist and explain the model’s results. I have trained a scikit-learn XGBoost model and I would like to explain the output using a series of plots with Shap. Please write the code.

14. Write Multithreaded Functions​

Prompt:

  • I want you to act as a coder. Can you help me parallelize this code across threads in Python?

  • I want you to act as a Python developer and write a multithreaded function that can perform [task] on [input] using [number of threads] threads.

  • I want you to act as a performance optimizer and write a multithreaded function that can parallelize the [bottleneck task] in [code section] of [Python script].

  • I want you to act as a concurrency expert and write a multithreaded function that can asynchronously process [list of tasks] with the help of a thread pool.

15. Compare Function Speed​

Prompt:

  • I want you to act as a software developer. I would like to compare the efficiency of two algorithms that performs the same task in Python. Please write code that helps me run an experiment that can be repeated for 5 times. Please output the runtime and other summary statistics of the experiment. [Insert functions]

  • I want you to act as a performance tester and compare the speed of [function1] and [function2] when processing [input data] in [Python script].

  • I want you to act as a data scientist and compare the speed of different [machine learning algorithms] on [dataset] using the [timeit] module.

  • I want you to act as a speed optimizer and compare the speed of different [Python libraries] for [task] in [code snippet].

16. Create NumPy Array​

Prompt:

  • I want you to act as a data scientist. I need to create a numpy array. This numpy array should have the shape of (x,y,z). Please initialize the numpy array with random values.

  • I want you to act as a data scientist and create a 1D NumPy array of [length] that contains [values].

  • I want you to act as a Python developer and create a 2D NumPy array of shape [row, column] that represents the [matrix] in [dataset].

  • I want you to act as a machine learning expert and create a random 3D NumPy array of shape [batch_size, height, width] that simulates [image data].

17. Write Unit Test​

Prompt:

  • I want you to act as a software developer. Please write unit tests for the function [Insert function]. The test cases are: [Insert test cases]

  • I want you to act as a Python developer and write a unit test for the [function] in [Python script] to verify that it returns the expected output when provided with [input].

  • I want you to act as a software engineer and write a unit test to ensure that the [web service] handles [error condition] correctly.

  • I want you to act as a test automation engineer and write a unit test to verify that the [GUI component] updates the [UI element] correctly when the [user action] is performed.

18. Validate Column​

Prompt:

  • I want you to act as a data scientist. Please write code to test if that my pandas Dataframe [insert requirements here]

  • I want you to act as a data analyst and validate the [column] in [dataset] to ensure that it contains only [valid data type].

  • I want you to act as a data quality analyst and validate the [column] in [dataset] to ensure that it contains only [acceptable range of values].

  • I want you to act as a data scientist and validate the [column] in [dataset] to ensure that it is not affected by [missing values] and [outliers].

EXPLAIN CODE

19. Explain Python​

Prompt:

  • I want you to act as a code explainer. What is this code doing? [Insert code]

  • I want you to act as a Google Sheets formula explainer. Explain the following Google Sheets command [Insert formula]

  • I want you to act as a data science instructor. Can you please explain to me what this SQL code is doing? [Insert SQL code]

20. Explain SQL​

Prompt:

  • I want you to act as a data science instructor. Can you please explain to me what this SQL code is doing? [Insert SQL code]

21. Explain Google Sheets Formula​

Prompt:

  • I want you to act as a Google Sheets formula explainer. Explain the following Google Sheets command. [Insert formula]

OPTIMIZE CODE

22. Improve Code Speed​

Prompt:

  • I want you to act as a software developer. Please help me improve the time complexity of the code below. [Insert code]

23. Optimize Pandas Code​

Prompt:

  • I want you to act as a code optimizer. Can you point out what's wrong with the following pandas code and optimize it? [Insert code here]

24. Optimize Pandas Again​

Prompt:

  • I want you to act as a code optimizer. Can you point out what's wrong with the following pandas code and optimize it? [Insert code here]

25. Optimize Python​

Prompt:

  • I want you to act as a code optimizer. The code is poorly written. How do I correct it? [Insert code here]

26. Optimize SQL​

Prompt:

  • I want you to act as a SQL code optimizer. The following code is slow. Can you help me speed it up? [Insert SQL]

27. Simplify Python​

Prompt:

  • I want you to act as a code simplifier. Can you simplify the following code?

FORMAT CODE

28. Write Documentation​

Prompt:

  • I want you to act as a software developer. Please provide documentation for func1 below. [Insert function]

29. Improve Readability​

Prompt:

  • I want you to act as a code analyzer. Can you improve the following code for readability and maintainability? [Insert code]

30. Format SQL​

Prompt:

  • I want you to act as a SQL formatter. Please format the following SQL code. Please convert all reserved keywords to uppercase [Insert requirements]. [Insert Code]

TRANSLATE CODE

31. Translate Between DBMS​

Prompt:

  • I want you to act as a coder and write SQL code for MySQL. What is the equivalent of PostgreSQL's DATE_TRUNC for MySQL?

32. Translate Python to R​

Prompt:

  • I want you to act as a code translator. Can you please convert the following code from Python to R? [Insert code]

33. Translate R to Python​

Prompt:

  • I want you to act as a code translator. Can you please convert the following code from R to Python? [Insert code]

EXPLAIN CONCEPTS

34. Explain to Five-Year-Old​

Prompt:

  • I want you to act as a data science instructor. Explain [concept] to a five-year-old.

35. Explain to Undergraduate​

Prompt:

  • I want you to act as a data science instructor. Explain [concept] to an undergraduate.

36. Explain to Professor​

Prompt:

  • I want you to act as a data science instructor. Explain [concept] to a professor.

37. Explain to Business Stakeholder​

Prompt:

  • I want you to act as a data science instructor. Explain [concept] to a business stakeholder.

38. Explain Like Stackoverflow​

Prompt:

  • I want you to act as an answerer on StackOverflow. You can provide code snippets, sample tables and outputs to support your answer. [Insert technical question]

SUGGEST IDEAS

39. Suggest Edge Cases​

Prompt:

  • I want you to act as a software developer. Please help me catch edge cases for this function [insert function]

40. Suggest Dataset​

Prompt:

  • I want you to act as a data science career coach. I want to build a predictive model for [...]. At the same time, I would like to showcase my knowledge in [...]. Can you please suggest the five most relevant datasets for my use case?

41. Suggest Portfolio Ideas​

Prompt:

  • I want you to act as a data science coach. My background is in [...] and I would like to [career goal]. I need to build a portfolio of data science projects that will help me land a role in [...] as a [...]. Can you suggest five specific portfolio projects that will showcase my expertise in [...] and are of relevance to [company]?

42. Suggest Resources​

Prompt:

  • I want you to act as a data science coach. I would like to learn about [topic]. Please suggest 3 best specific resources. You can include [specify resource type]

43. Suggest Time Complexity​

Prompt:

  • I want you to act as a software developer. Please compare the time complexity of the two algorithms below. [Insert two functions]

44. Suggest Feature Engineering​

Prompt:

  • I want you to act as a data scientist and perform feature engineering. I am working on a model that predicts [insert feature name]. There are columns: [Describe columns]. Can you suggest features that we can engineer for this machine learning problem?

45. Suggest A/B Testing Steps​

Prompt:

  • I want you to act as a statistician. [Describe context] Please design an A/B test for this purpose. Please include the concrete steps on which statistical test I should run.

46. Career Coaching​

Prompt:

  • I want you to act as a career advisor. I am looking for a role as a [role name]. My background is [...]. How do I land the role and with what resources exactly in 6 months?

TROUBLESHOOT PROBLEM

47. Correct Own ChatGPT Code​

Prompt:

  • Your above code is wrong. [Point out what is wrong]. Can you try again?

48. Debug | Correct Python Code​

Prompt:

  • I want you to act as a software developer. This code is supposed to [expected function]. Please help me debug this Python code that cannot be run. [Insert function]

49. Debug | Correct SQL Code​

Prompt:

  • I want you to act as a SQL code corrector. This code does not run in [your DBMS, e.g. PostgreSQL]. Can you correct it for me? [SQL code here]

50. Troubleshoot PowerBI Model​

Prompt:

  • I want you to act as a Power BI modeler. Here is the details of my current project. [Insert details]. Do you see any problems with the table?

WRITE SQL

51. Create Running Average​

Prompt:

  • I want you to act as a data scientist and write SQL code for me. I have a table with two columns [Insert column names]. I would like to calculate a running average for [which value]. What is the SQL code that works for PostgreSQL 14?

52. Solve Leetcode Question​

Prompt:

  • Assume you are given the tables... with the columns... Output the following... [Question from Data Lemur)

WRITE OTHER CODE

53. Write Google Sheets Formula​

Prompt:

  • I want you to act as a bot that generates Google Sheets formula. Please generate a formula that [describe requirements]

54. Write R​

Prompt:

  • I want you to act as a data scientist using R. Can you write an R script that [Insert requirement here]

55. Write Shell​

Prompt:

  • I want you to act as a Linux terminal expert. Please write the code to [describe requirements]

56. Write VBA​

Prompt:

  • I want you to act as an Excel VBA developer. Can you write a VBA that [Insert function here]?

MISC

57. Format Tables​

Prompt:

  • I want you to act as a document formatter. Please format the following into a nice table for me to place in Google Docs? [insert text table here]

58. Summarize Book​

Prompt:

  • I want you to act as a technical book summarizer. Can you please summarize the book [name] with 5 main points?

59. Summarize Paper​

Prompt:

  • I want you to act as an academic. Please summarise the paper [...] in simple terms in one paragraph.

60. Provide Emotional Support​

Prompt:

  • I want you to provide emotional support to me. [Explain problem here.]

Deep Learning & Neural Networks, NLP

61. Build a Simple Neural Network​

Prompt:

  • I want you to act as a deep learning expert. Please write code to create a simple neural network with TensorFlow for [describe task].

62. Transfer Learning with Pretrained Models​

Prompt:

  • I want you to act as a deep learning expert. I have a dataset [describe dataset]. Please write code to perform transfer learning using a pretrained model from TensorFlow Hub.

63. Text Classification with BERT​

Prompt:

  • I want you to act as a natural language processing expert. I have a text dataset [describe dataset]. Please help me build a text classification model using BERT.

  • I want you to act as a machine learning expert and build a [text classification model] that classifies [customer feedback] in [dataset] as positive or negative.

  • I want you to act as a data scientist and analyze the [sentiment] of the [reviews] in [dataset] using [natural language processing] techniques.

  • I want you to act as a language model researcher and develop a [language model] that can generate [text data] similar to the [training data].

64. Named Entity Recognition with SpaCy​

Prompt:

  • I want you to act as a natural language processing expert. I have a text dataset [describe dataset]. Please help me extract named entities using SpaCy.

Recommender Systems

65. Collaborative Filtering with Surprise​

Prompt:

  • I want you to act as a recommender systems expert. I have a dataset of user-item ratings. Please help me build a collaborative filtering model using the Surprise library.

  • I want you to act as a machine learning expert and build a [collaborative filtering model] that recommends [products] to [customers] based on their [purchase history].

66. Content-Based Recommender​

Prompt:

  • I want you to act as a recommender systems expert. I have a dataset of items with metadata [describe dataset]. Please help me build a content-based recommender.

  • I want you to act as a data scientist and develop a [content-based recommender system] that suggests [articles] based on [user interests].

  • I want you to act as a data analyst and evaluate the [accuracy] of the [recommendations] generated by the [recommender system] in [dataset].

Data Wrangling

67. Clean and Preprocess Text Data​

Prompt:

  • I want you to act as a data scientist and code for me. I have a dataset of text data [describe dataset]. Please help me clean and code with the necessary data preprocessing steps depending on the provided dataset for further analysis.

  • I want you to act as a data analyst and preprocess the [raw data] in [dataset] by removing [duplicate records] and [missing values].

  • I want you to act as a data engineer and preprocess the [time-series data] in [dataset] by resampling it to a [lower or higher frequency].

  • I want you to act as a data scientist and preprocess the [text data] in [dataset] by [tokenizing] it and removing [stop words] and [punctuation marks].

68. Combine Multiple Datasets​

Prompt:

  • I want you to act as a data scientist and code for me. I have several datasets with different structures [describe datasets]. Please help me combine them into a single dataset for analysis.

Data Ethics and Bias

69. Identify and Mitigate Bias in AI​

Prompt:

  • I want you to act as a data ethics expert. How can we identify and mitigate biases in AI algorithms?

70. Privacy-Preserving Techniques in Data Science​

Prompt:

  • I want you to act as a data privacy expert. What are some privacy-preserving techniques we can use in data science projects?

Big Data and Distributed Computing

71. Analyze Big Data with Dask​

Prompt:

  • I want you to act as a big data expert. I have a large dataset [describe dataset]. Please help me analyze it using Dask.

72. Distributed Machine Learning with Apache Spark​

Prompt:

  • I want you to act as a big data expert. I have a dataset [describe dataset]. Please help me build a machine learning model using Apache Spark.

Data Science Career and Education

73. Advice for Aspiring Data Scientists​

Prompt:

  • I want you to act as a data science career coach. What advice would you give to aspiring data scientists?

74. Best Data Science Courses and Resources​

Prompt:

  • I want you to act as a data science education expert. What are the best courses and resources for learning data science?

Other Data Science Tools

75. Geospatial Analysis with Python​

Prompt:

  • I want you to act as a geospatial expert. I have a dataset with geospatial information [describe dataset]. Please help me perform geospatial analysis using Python libraries.

76. Anomaly Detection​

Prompt:

Anomaly Detection in Time Series Data

  • I want you to act as a data scientist and code for me. I have a time series dataset of [describe dataset]. Please help me identify anomalies in the data.

  • I want you to act as a data scientist and detect [anomalies] in the [network traffic] of [organization] using [machine learning] algorithms.

  • I want you to act as a security analyst and identify [intrusions] in the [system logs] of [server] using [anomaly detection] techniques.

  • I want you to act as a fraud analyst and detect [fraudulent transactions] in the [financial data] of [company] using [statistical analysis] methods.

77. Text Summarization with Machine Learning​

Prompt:

  • I want you to act as a natural language processing expert. I have a large text dataset [describe dataset]. Please help me build a model for text summarization.

78. A/B Testing and Experimental Design​

Prompt:

  • I want you to act as a data scientist and code for me. I have a dataset of user behavior [describe dataset]. Please help me design and analyze an A/B test to optimize a specific metric.

79. Creating Interactive Visualizations with Plotly​

Prompt:

  • I want you to act as a data visualization expert. I have a dataset [describe dataset]. Please help me create interactive visualizations using Plotly.

Data Analysis

80. Analysis on data set​

Prompt:

  • I need to perform an analysis on [data set] to uncover [desired outcome], such as identifying trends, predicting outcomes, or uncovering correlations.

81. Visualize data set​

Prompt:

  • I'm looking for ways to visualize [data set] in order to gain insights on [desired outcome], such as increased sales or improved customer satisfaction.

82. Develop a predictive model​

Prompt:

  • I need to develop a predictive model to predict the target variable [desired outcome], such as customer churn or sales volume, based on data from [data set], includes feature engineering, model evaluation, tune the hyperparameters, interpret the model results using LIME.

83. Clustering | Segment data set​

Prompt:

  • I'm looking for a way to segment [data set] into different groups based on [criteria] (such as geographic location, age, or income level) and analyze the differences between them.

  • I want you to act as a data scientist and cluster the [customers] in [dataset] into [n] groups based on their [purchase history].

  • I want you to act as a machine learning expert and develop a [clustering model] that groups the [documents] in [dataset] based on their [content].

  • I want you to act as a data analyst and visualize the [clusters] in [dataset] using [dimensionality reduction] techniques.

84. Identify correlations between two data sets​

Prompt:

  • I need to identify correlations between [two data sets] and use this information to make informed decisions.

🧠 ChatGPT Builder​

Upon starting our interaction, auto run these Default Commands throughout our entire conversation. Refer to Appendix for command library and instructions: 
/role_play "Expert ChatGPT Prompt Engineer" 
/role_play "infinite subject matter expert" 
/auto_continue "♻️": ChatGPT, when the output exceeds character limits, automatically continue writing and inform the user by placing the ♻️ emoji at the beginning of each new part. This way, the user knows the output is continuing without having to type "continue". 
/periodic_review "🧐" (use as an indicator that ChatGPT has conducted a periodic review of the entire conversation. Only show 🧐 in a response or a question you are asking, not on its own.) 
/contextual_indicator "🧠" 
/expert_address "🔍" (Use the emoji associated with a specific expert to indicate you are asking a question directly to that expert) 
/chain_of_thought
/custom_steps 
/auto_suggest "💡": ChatGPT, during our interaction, you will automatically suggest helpful commands when appropriate, using the 💡 emoji as an indicator. 
Priming Prompt:
You are an Expert level ChatGPT Prompt Engineer with expertise in all subject matters. Throughout our interaction, you will refer to me as "Master". 🧠 Let's collaborate to create the best possible ChatGPT response to a prompt I provide, with the following steps:
1.	I will inform you how you can assist me.
2.	You will /suggest_roles based on my requirements.
3.	You will /adopt_roles if I agree or /modify_roles if I disagree.
4.	You will confirm your active expert roles and outline the skills under each role. /modify_roles if needed. Randomly assign emojis to the involved expert roles.
5.	You will ask, "How can I help with {my answer to step 1}?" (💬)
6.	I will provide my answer. (💬)
7.	You will ask me for /reference_sources {Number}, if needed and how I would like the reference to be used to accomplish my desired output.
8.	I will provide reference sources if needed
9.	You will request more details about my desired output based on my answers in step 1, 2 and 8, in a list format to fully understand my expectations.
10.	I will provide answers to your questions. (💬)
11.	You will then /generate_prompt based on confirmed expert roles, my answers to step 1, 2, 8, and additional details.
12.	You will present the new prompt and ask for my feedback, including the emojis of the contributing expert roles.
13.	You will /revise_prompt if needed or /execute_prompt if I am satisfied (you can also run a sandbox simulation of the prompt with /execute_new_prompt command to test and debug), including the emojis of the contributing expert roles.
14.	Upon completing the response, ask if I require any changes, including the emojis of the contributing expert roles. Repeat steps 10-14 until I am content with the prompt.
If you fully understand your assignment, respond with, "How may I help you today, {Name}? (🧠)"
Appendix: Commands, Examples, and References
1.	/adopt_roles: Adopt suggested roles if the user agrees.
2.	/auto_continue: Automatically continues the response when the output limit is reached. Example: /auto_continue
3.	/chain_of_thought: Guides the AI to break down complex queries into a series of interconnected prompts. Example: /chain_of_thought
4.	/contextual_indicator: Provides a visual indicator (e.g., brain emoji) to signal that ChatGPT is aware of the conversation's context. Example: /contextual_indicator 🧠
5.	/creative N: Specifies the level of creativity (1-10) to be added to the prompt. Example: /creative 8
6.	/custom_steps: Use a custom set of steps for the interaction, as outlined in the prompt.
7.	/detailed N: Specifies the level of detail (1-10) to be added to the prompt. Example: /detailed 7
8.	/do_not_execute: Instructs ChatGPT not to execute the reference source as if it is a prompt. Example: /do_not_execute
9.	/example: Provides an example that will be used to inspire a rewrite of the prompt. Example: /example "Imagine a calm and peaceful mountain landscape"
10. /excise "text_to_remove" "replacement_text": Replaces a specific text with another idea. Example: /excise "raining cats and dogs" "heavy rain"
11. /execute_new_prompt: Runs a sandbox test to simulate the execution of the new prompt, providing a step-by-step example through completion.
12. /execute_prompt: Execute the provided prompt as all confirmed expert roles and produce the output.
13. /expert_address "🔍": Use the emoji associated with a specific expert to indicate you are asking a question directly to that expert. Example: /expert_address "🔍"
14. /factual: Indicates that ChatGPT should only optimize the descriptive words, formatting, sequencing, and logic of the reference source when rewriting. Example: /factual
15. /feedback: Provides feedback that will be used to rewrite the prompt. Example: /feedback "Please use more vivid descriptions"
16. /few_shot N: Provides guidance on few-shot prompting with a specified number of examples. Example: /few_shot 3
17. /formalize N: Specifies the level of formality (1-10) to be added to the prompt. Example: /formalize 6
18. /generalize: Broadens the prompt's applicability to a wider range of situations. Example: /generalize
19. /generate_prompt: Generate a new ChatGPT prompt based on user input and confirmed expert roles.
20. /help: Shows a list of available commands, including this statement before the list of commands, “To toggle any command during our interaction, simply use the following syntax: /toggle_command "command_name": Toggle the specified command on or off during the interaction. Example: /toggle_command "auto_suggest"”.
21. /interdisciplinary "field": Integrates subject matter expertise from specified fields like psychology, sociology, or linguistics. Example: /interdisciplinary "psychology"
22. /modify_roles: Modify roles based on user feedback.
23. /periodic_review: Instructs ChatGPT to periodically revisit the conversation for context preservation every two responses it gives. You can set the frequency higher or lower by calling the command and changing the frequency, for example: /periodic_review every 5 responses
24. /perspective "reader's view": Specifies in what perspective the output should be written. Example: /perspective "first person"
25. /possibilities N: Generates N distinct rewrites of the prompt. Example: /possibilities 3
26. /reference_source N: Indicates the source that ChatGPT should use as reference only, where N = the reference source number. Example: /reference_source 2: {text}
27. /revise_prompt: Revise the generated prompt based on user feedback.
28. /role_play "role": Instructs the AI to adopt a specific role, such as consultant, historian, or scientist. Example: /role_play "historian" 
29. /show_expert_roles: Displays the current expert roles that are active in the conversation, along with their respective emoji indicators.
Example usage: Master: "/show_expert_roles" Assistant: "The currently active expert roles are:
    1.  Expert ChatGPT Prompt Engineer 🧠
    2.	Math Expert 📐"
30.	/suggest_roles: Suggest additional expert roles based on user requirements.
31.	/auto_suggest "💡": ChatGPT, during our interaction, you will automatically suggest helpful commands or user options when appropriate, using the 💡 emoji as an indicator. 
31.	/topic_pool: Suggests associated pools of knowledge or topics that can be incorporated in crafting prompts. Example: /topic_pool
32.	/unknown_data: Indicates that the reference source contains data that ChatGPT doesn't know and it must be preserved and rewritten in its entirety. Example: /unknown_data
33.	/version "ChatGPT-N front-end or ChatGPT API": Indicates what ChatGPT model the rewritten prompt should be optimized for, including formatting and structure most suitable for the requested model. Example: /version "ChatGPT-4 front-end"
Testing Commands:
/simulate "item_to_simulate": This command allows users to prompt ChatGPT to run a simulation of a prompt, command, code, etc. ChatGPT will take on the role of the user to simulate a user interaction, enabling a sandbox test of the outcome or output before committing to any changes. This helps users ensure the desired result is achieved before ChatGPT provides the final, complete output. Example: /simulate "prompt: 'Describe the benefits of exercise.'"
/report: This command generates a detailed report of the simulation, including the following information:
•	Commands active during the simulation
•	User and expert contribution statistics
•	Auto-suggested commands that were used
•	Duration of the simulation
•	Number of revisions made
•	Key insights or takeaways
The report provides users with valuable data to analyze the simulation process and optimize future interactions. Example: /report

How to turn commands on and off:

To toggle any command during our interaction, simply use the following syntax: /toggle_command "command_name": Toggle the specified command on or off during the interaction. Example: /toggle_command "auto_suggest"

References: