Prompting Gemini

Gemini is Google's AI assistant and the family of models behind it. You may meet it as a standalone app, as a helper built into Google's productivity tools, or through the developer API. The surface changes what it can see, such as an open document or files you attach, but the way to ask for good work stays much the same.

Google's prompt design documentation treats prompting as an iterative process. You are not expected to get it right on the first attempt. Start with a clear instruction, look at what comes back, and adjust: rephrase, add an example, change the order of the parts. That framing is worth adopting, because it turns a disappointing answer into information about what the prompt was missing.

A Gemini prompt generally has up to four ingredients: the task, any constraints on how it should be done, the context or source material, and the format of the response. Leaving one out is the usual cause of generic output. If you do not say how long the answer should be or who it is for, the model has to guess.

Standing guidance has its own place. Developers set system instructions that apply to a whole session; in the app, saved instructions and reusable custom assistants play a similar role. Use these for a persona, a house style or rules that should hold across many requests, and keep one-off details in the prompt.

Gemini accepts more than text. Images, documents and other files can be part of a prompt, and the same principles apply: say what the file is and what you want done with it.

Version names, limits and pricing are omitted here because they change. Which features you have depends on your account and region.

How to get better results

Give clear, specific instructions and name the constraints

Google's documentation starts with the basics: say exactly what you want done, and state any limits on the response, such as length, scope or things to exclude. A prompt that says 'summarize this' leaves the model to decide how short and for whom. One that asks for three sentences for a non-technical reader removes the guesswork and gives you something to check the answer against.

Include a few examples, and keep their format consistent

The prompt design guide recommends few-shot examples as a strong way to control format, phrasing and scope, and suggests including them wherever practical. Keep the structure of every example identical, including labels and spacing, because inconsistencies can be picked up as part of the pattern. Showing what to do generally works better than showing examples of what to avoid.

Supply the context the model needs instead of assuming it has it

Google advises adding the information required to solve the problem directly to the prompt: the document, the data, the background on your situation. Instructions can then tell the model to rely on that material. This is particularly useful for anything specific to your organization, where a general-purpose model would otherwise fall back on generic knowledge that may not apply.

Put long context first and your question at the end

When a prompt contains a large document or several files, the documentation suggests placing the material first and the specific instruction or question after it. A short bridging line, for instance one that refers back to the information above, helps anchor the request to the supplied content. The same ordering is used in most prompts on this site that take pasted source text.

Use prefixes and partial outputs to steer the response shape

The guide describes labeling parts of a prompt with prefixes, such as a marker before the input and another before the expected output, so the model can tell them apart. You can also start the response yourself, for example by writing the first row of a table or the opening key of a JSON object, and let the model continue in that pattern.

Split complicated requests and set standing rules separately

For tasks with several distinct stages, Google recommends breaking the work into simpler prompts, either as a sequence where each output feeds the next or as parallel pieces combined afterward. Rules that should apply throughout, like a role or a tone, belong in system instructions or their app equivalent, so they do not have to be repeated at each step.

Where it fits

Well suited to

  • Tasks that combine text with images, documents or other files
  • Summarizing and questioning long source material placed ahead of the request
  • Drafting within Google's own productivity tools, where the open file provides context
  • Structured output such as tables or JSON, especially when an example is supplied
  • Iterative work where you refine a prompt over several attempts

Watch out for

  • Responses can contain errors presented confidently; verify facts, figures and references
  • Asking for the same thing twice can produce different answers, so rerun before concluding a prompt is at fault
  • What Gemini can access varies by surface; the app, the workspace integrations and the API do not see the same things
  • Inconsistent examples can teach an unintended pattern
  • Review your organization's data policy before sharing confidential content

Prompts that work with Gemini

These prompts are expected to work with Gemini based on their structure. Check each prompt page for its testing status; see how compatibility is labelled.

Web Design

Web Development

Content Writing

SEO

Marketing

Business

Research

Coding

Graphic Design

Productivity

Education

E-commerce

Official documentation