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Best Prompt libraries in 2026: Top 4 Picks, Ranked

Curated, tested prompts and style references for writing, image and video models. Below are the 4 prompt libraries we recommend in 2026, ranked by our editor score, GitHub stars, reader upvotes and how often readers click through.

Last updated September 2026 · 4 listings reviewed

The ranking

1

Fabric Open source

Open-source CLI and library of reusable AI prompt patterns for summarising and writing

★ 44k · MIT · updated 2026-09-24

8.0/10

What it is Fabric by Daniel Miessler (MIT) is a command-line framework built around "patterns": carefully written, crowdsourced system prompts for specific jobs such as extracting wisdom from a video transcript, summarising articles, writing essays, creating social posts, improving writing or analysing claims. You pipe text into a pattern and get structured output, which makes it handy for turning long… Read more →

Pros

  • Readable, editable prompt patterns
  • Works with many model providers and local models
  • MIT, very active

Cons

  • Terminal-first; not for non-technical users
  • Output quality depends on the model you connect

Pricing: Open source  ·  prompts cli summarization patterns

2

prompts.chat (Awesome ChatGPT Prompts) Open source

Large open prompt library, formerly Awesome ChatGPT Prompts, with web app and CLI

★ 171k · CC0-1.0 (prompts); MIT (code) · updated 2026-09-09

7.8/10

What it is prompts.chat, started by Fatih Kadir Akın as Awesome ChatGPT Prompts, is one of the most-starred repositories on GitHub. It collects community "act as" role prompts and task prompts for writing, marketing, education, coding and more, and has grown into a web app at prompts.chat, a CLI, a Claude Code plugin and a self-hostable prompt library you can… Read more →

Pros

  • CC0 prompts, free for any use
  • Web, CLI and self-host options
  • Very active community

Cons

  • Uneven, often generic prompts
  • Many written for older models
  • Content-specific prompts are a minority

Pricing: Open source  ·  prompts chatgpt prompt-library cc0

3

Awesome Nano Banana Pro Prompts Open source

Curated image prompts for Google's Nano Banana Pro, by use case and style

★ 13k · CC-BY-4.0 · updated 2026-09-25

7.2/10

What it is Awesome Nano Banana Pro Prompts from YouMind OpenLab collects community prompts and example outputs for Google's Nano Banana Pro image model (Gemini's image generation and editing model). Prompts are grouped by use case, including profile avatars, social media posts, infographics, YouTube thumbnails, comics and storyboards, product marketing, e-commerce main images, posters and app designs, and by visual… Read more →

Pros

  • Organised by real creator use cases
  • Example outputs for every prompt
  • Updated daily

Cons

  • Prompt provenance unclear
  • Promotes the maintainer's commercial gallery
  • No install; copy-paste only

Pricing: Open source  ·  prompts nano-banana image-prompts gemini

4

Awesome GPT Image 2 Prompts Open source

Curated prompt collection with examples for OpenAI's GPT Image 2 model

★ 9.9k · CC-BY-4.0 · updated 2026-09-25

6.9/10

What it is Awesome GPT Image 2 is YouMind OpenLab's companion collection to its Nano Banana list, gathering prompts and example outputs for OpenAI's GPT Image 2 model, which powers image generation in ChatGPT and the OpenAI API. Prompts cover posters, product shots, infographics, avatars, thumbnails, UI mockups and stylised illustration, with text-heavy designs where GPT Image models are strong.… Read more →

Pros

  • Current prompts for a new model
  • Examples show expected output
  • Strong on text-in-image designs

Cons

  • Prompt provenance unclear
  • Promotes the maintainer's gallery
  • Copy-paste only

Pricing: Open source  ·  prompts gpt-image image-prompts chatgpt

Prompt libraries compared at a glance

#NamePricingStarsScore
1FabricOpen source★ 44k8.0
2prompts.chat (Awesome ChatGPT Prompts)Open source★ 171k7.8
3Awesome Nano Banana Pro PromptsOpen source★ 13k7.2
4Awesome GPT Image 2 PromptsOpen source★ 9.9k6.9

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How we rank prompt libraries

Every workflow gets an editor score from 0 to 10 based on usefulness, quality of the instructions or code, maintenance (recent commits, open issues) and adoption (GitHub stars), and we check which apps it really works with. Reader upvotes and click-throughs nudge the order over time, and we remove listings that shut down, go unmaintained or change pricing dramatically. Read our full methodology.

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