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Prompt engineering for GitHub Copilot
Prompt engineering
Follow these strategies to improve your {% data variables.product.prodname_copilot_short %} results.
feature
copilot
Copilot

A prompt is a request that you make to {% data variables.product.prodname_copilot %}. For example, a question that you ask {% data variables.product.prodname_copilot_chat_short %}, or a code snippet that you ask {% data variables.product.prodname_copilot_short %} to complete. In addition to your prompt, {% data variables.product.prodname_copilot_short %} uses additional context, like the code in your current file and the chat history, to generate a response.

Follow the tips in this article to write prompts that generate better responses from {% data variables.product.prodname_copilot_short %}.

Start general, then get specific

When writing a prompt for {% data variables.product.prodname_copilot_short %}, first give {% data variables.product.prodname_copilot_short %} a broad description of the goal or scenario. Then list any specific requirements.

For example:

Write a function that tells me if a number is prime

The function should take an integer and return true if the integer is prime

The function should error if the input is not a positive integer

Give examples

Use examples to help {% data variables.product.prodname_copilot_short %} understand what you want. You can provide example input data, example outputs, and example implementations.

For example:

Write a function that finds all dates in a string and returns them in an array. Dates can be formatted like:

  • 05/02/24
  • 05/02/2024
  • 5/2/24
  • 5/2/2024
  • 05-02-24
  • 05-02-2024
  • 5-2-24
  • 5-2-2024

Example:

findDates("I have a dentist appointment on 11/14/2023 and book club on 12-1-23")

Returns: ["11/14/2023", "12-1-23"]

Unit tests can also serve as examples. Before writing your function, you can use {% data variables.product.prodname_copilot_short %} to write unit tests for the function. Then, you can ask {% data variables.product.prodname_copilot_short %} to write a function described by those unit tests.

Break complex tasks into simpler tasks

If you want {% data variables.product.prodname_copilot_short %} to complete a complex or large task, break the task into multiple simple, small tasks.

For example, instead of asking {% data variables.product.prodname_copilot_short %} to generate a word search puzzle, break the process down into smaller tasks, and ask {% data variables.product.prodname_copilot_short %} to accomplish them one by one:

  • Write a function to generate a 10 by 10 grid of letters.
  • Write a function to find all words in a grid of letters, given a list of valid words.
  • Write a function that uses the previous functions to generate a 10 by 10 grid of letters that contains at least 10 words.
  • Update the previous function to print the grid of letters and 10 random words from the grid.

Avoid ambiguity

Avoid ambiguous terms. For example, don’t ask "what does this do" if "this" could be the current file, the last {% data variables.product.prodname_copilot_short %} response, or a specific code block. Instead, be specific:

  • What does the createUser function do?
  • What does the code in your last response do?

Ambiguity can also apply to libraries:

  • If you are using an uncommon library, describe what the library does.
  • If you want to use a specific library, set the import statements at the top of the file or specify what library you want to use.

Indicate relevant code

If you are using {% data variables.product.prodname_copilot_short %} in your IDE to get suggestions as you code, open any relevant files and close irrelevant files. {% data variables.product.prodname_copilot_short %} will use the open files to understand your request.

If you are using {% data variables.product.prodname_copilot_chat_short %} in your IDE, open the file or highlight the code that you want {% data variables.product.prodname_copilot_short %} to reference. You can also specify which files {% data variables.product.prodname_copilot_chat_short %} should reference. For example, in {% data variables.product.prodname_vscode_shortname %}, use the #file variable or the @workspace participant. For instructions on how to reference files in your IDE, see "AUTOTITLE."

Experiment and iterate

If you don’t get the result that you want, iterate on your prompt and try again.

If you are using {% data variables.product.prodname_copilot_short %} to get suggestions as you code, you can delete the suggestion entirely and start over. Or you can keep the suggestion and request modifications.

If you are using {% data variables.product.prodname_copilot_chat_short %}, you can reference the previous response in your next request. Or, you can delete the previous response and start over.

Keep history relevant

{% data variables.product.prodname_copilot_chat_short %} uses the chat history to get context about your request. To give {% data variables.product.prodname_copilot_short %} only the relevant history:

  • Use threads to start a new conversation for a new task
  • Delete requests that are no longer relevant or that didn’t give you the desired result

Follow good coding practices

If you aren't getting the responses you want when you ask {% data variables.product.prodname_copilot_short %} for suggestions or explanations in your codebase, make sure that your existing code follows best practices and is easy to read. For example:

  • Use a consistent code style and patterns
  • Use descriptive names for variables and functions
  • Comment your code
  • Structure your code into modular, scoped components
  • Include unit tests

Tip

Use {% data variables.product.prodname_copilot_short %} to help your code follow best practices. For example, ask {% data variables.product.prodname_copilot_short %} to add comments or to break a large function into smaller functions.

{% ifversion ghec %}

Similarly, if you aren't getting the responses you want when you use {% data variables.product.prodname_copilot_short %} with knowledge bases, apply these best practices to your knowledge base files:

  • Organize the files into a logical hierarchy
  • Use clear and concise language
  • Include examples and use cases, if relevant
  • Cross reference between related files

{% endif %}

Further reading