Gemini Prompt Generator (2026): Copy-Paste Templates for Better Text + JSON

Name: PromptBuilder
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Author: PromptBuilder

If you’ve searched for a Gemini prompt generator, you’re probably trying to solve the same thing everyone hits with modern AI: you know what you want, but you don’t know how to ask for it in a way that produces clean, usable output on the first try.

This post gives you a simple formula and ready-to-use templates for Gemini prompt generator text prompts and Gemini JSON prompt generator workflows.

If you prefer a UI over writing prompts manually, think of this as a lightweight Gemini prompt builder you can copy and adapt.

Want the fast path? Use our free tool: Gemini Prompt Generator

What a “Gemini prompt generator” should do (in 2026)

A good Gemini prompt generator should:

Turn vague goals into clear instructions (so Gemini doesn’t guess your intent)
Add the missing constraints that prevent “helpful but wrong” outputs
Lock the output format (so results are easy to paste into docs/tools)

If you’re using Gemini 3, you can often get excellent results with shorter prompts. If you want the model-specific playbook, see: Gemini 3 Prompting Playbook

The 3-part prompt formula that fixes most Gemini outputs

Use this structure for almost everything:

TASK: one sentence describing what you want
CONTEXT: the minimum background/data Gemini needs
OUTPUT: exact format + constraints (length, tone, fields, etc.)

Copy-paste base template

TASK: {{one sentence goal}}
CONTEXT: {{inputs, audience, constraints, source text, or data}}
OUTPUT: {{format + length + any must-include / must-avoid rules}}

If your task has multiple phases, chain it (extract → draft → edit → verify). Template here: Prompt Chaining in 2026

Gemini prompt generator text: 6 templates you can use today

1) Clean rewrite (same meaning, better clarity)

TASK: Rewrite the text to be clearer and more direct without changing meaning.
CONTEXT: Audience = {{who}}. Tone = {{tone}}. Reading level = {{level}}.
OUTPUT: Return 1 revised version + 5 bullet changes you made.

TEXT:
{{paste text}}

2) High-converting landing page section (problem → solution)

TASK: Write a landing page section for this offer.
CONTEXT: Offer = {{offer}}. Target customer = {{persona}}. Objections = {{list}}.
OUTPUT: Headline (<=12 words), subhead (<=20 words), 5 bullets, CTA button text (<=4 words).

3) Blog outline that actually stays on-topic

TASK: Create an outline for a blog post that targets the keyword: "{{primary keyword}}".
CONTEXT: Secondary keywords = {{list}}. Reader intent = {{informational/transactional}}.
OUTPUT: H1 + 8-12 H2s (with 2-4 bullets each) + FAQ (5 questions).

4) Meeting notes → action plan

TASK: Turn these meeting notes into an action plan.
CONTEXT: Team = {{roles}}. Deadline = {{date}}. Risks = {{known risks}}.
OUTPUT: 10 bullet action items with owner + due date + dependency (if any).

NOTES:
{{paste notes}}

5) Research summary (with uncertainty)

TASK: Summarize the topic and separate facts from assumptions.
CONTEXT: Topic = {{topic}}. If you cite numbers, say “approx” unless a source is provided.
OUTPUT: 5 key points, 3 uncertainties, and 5 follow-up questions to verify.

6) Content repurposing (one source → many formats)

TASK: Repurpose the source into multiple assets.
CONTEXT: Audience = {{who}}. Platform = {{LinkedIn / X / newsletter}}. Brand voice = {{voice}}.
OUTPUT:
- 1 LinkedIn post (120-180 words)
- 1 X thread (6 tweets, <=260 chars each)
- 1 newsletter intro (80-120 words)

SOURCE:
{{paste source}}

Gemini JSON prompt generator: 4 templates for structured output

1) Extract entities from text → JSON

TASK: Extract entities from the text.
CONTEXT: Entities = people, orgs, products, dates, money.
OUTPUT: Return valid JSON only with this schema:
{
  "people": [{"name": "", "role": ""}],
  "organizations": [{"name": "", "type": ""}],
  "products": [{"name": "", "category": ""}],
  "dates": [{"raw": "", "iso": ""}],
  "money": [{"raw": "", "amount": null, "currency": ""}]
}

TEXT:
{{paste text}}

2) Convert messy bullets → normalized JSON array

TASK: Normalize the items into a JSON array.
CONTEXT: Each item describes a feature request.
OUTPUT: JSON only. Schema:
[
  {
    "title": "",
    "problem": "",
    "proposed_solution": "",
    "priority": "low|medium|high",
    "notes": ""
  }
]

INPUT:
{{paste bullets}}

3) Build a simple content brief → JSON

TASK: Create a content brief.
CONTEXT: Keyword = "{{keyword}}". Audience = {{audience}}. Goal = {{goal}}.
OUTPUT: JSON only:
{
  "search_intent": "",
  "angle": "",
  "outline": [{"h2": "", "bullets": [""]}],
  "do_not_include": [""],
  "cta": ""
}

4) Add a self-check (evaluator) before final JSON

TASK: Produce the JSON output, then verify it.
CONTEXT: If the JSON is invalid or missing fields, fix it and output the corrected JSON.
OUTPUT: Return only valid JSON.

For reliability, this “evaluator” pattern is a lightweight version of prompt chaining: Prompt Chaining in 2026

Troubleshooting: when Gemini output is “almost right”

If Gemini gives you content that’s close but not usable, don’t rewrite the prompt from scratch. Fix the specific failure mode:

Too generic → add a concrete example output (1 is usually enough)
Wrong audience → define the reader persona and their job-to-be-done
Format drift → restate the schema and require “JSON only” or a strict heading layout
Hallucinated details → require a section called “Unknowns” and force questions

More tactics here: How to Make AI Prompts Better

Quick note: “Grok prompt generator” and “Claude prompt generator” prompts

Most of these templates transfer cleanly to other models. If you’re testing a Grok prompt generator prompt or a Claude prompt generator prompt, keep the same structure (TASK / CONTEXT / OUTPUT) and only tweak the constraints (tone, length, and how strict the schema needs to be).

Extra resource

If you’re collecting prompt engineering resources beyond PromptBuilder, bookmark: techdxon.com

FAQ

Is there a Gemini prompt generator free tool?

Yes — start here: Gemini Prompt Generator

What’s the best prompt format for Gemini in 2026?

Use a short, structured prompt with a clear TASK, minimal CONTEXT, and a strict OUTPUT format. For multi-step work, use chaining.

How do I make Gemini return valid JSON?

Provide an explicit schema and require “JSON only”. If you still get invalid JSON, add a verification instruction (see the evaluator template above).

Published: January 3, 2026.