# promptslab/Awesome-Prompt-Engineering

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

Repository: https://github.com/promptslab/Awesome-Prompt-Engineering
Canonical: https://ross.abutalabs.com/products/awesome-prompt-engineering
Homepage: https://discord.gg/m88xfYMbK6
Language: TypeScript
License: Apache-2.0
License Family: permissive
Topics: chatgpt, chatgpt-api, few-shot-learning, gpt, gpt-3, openai, prompt, promptengineering, text-to-image, text-to-speech, text-to-video, prompt-engineering, prompt-generator, prompt-learning, prompt-toolkit, prompt-tuning, prompt-based-learning, deep-learning, machine-learning
Last push: 2026-08-26T06:59:01+00:00

## Health v2 (maintenance only)
Score: 75/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 35, longevity 92
- inputs: {"age_days": 1301, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6292, forks 758 (observed 2026-08-28T04:09:41.399658+00:00)

## What it is
A hand-curated awesome-list of prompt engineering and context engineering resources for large language models like GPT, ChatGPT, and PaLM. It aggregates papers, tools, courses, benchmarks, guides, and communities rather than providing runnable software.

## Use cases
- learn prompt engineering from scratch
- find research papers on prompting techniques
- discover prompt engineering tools and courses
- study context engineering for AI agents
- find guides for OpenAI and Anthropic prompting
- locate benchmarks for evaluating prompts

## When to choose
- you want a curated starting point for learning prompt engineering
- you need links to papers, guides, and courses on LLM prompting
- you want to keep up with the prompt engineering research landscape

## When to avoid
- you need a runnable library or SDK for prompt management
- you want production prompt tooling rather than reference material
- you need executable code or APIs

## Facets
- artifact type: learning-resource
- maturity: active
- function: prompt-engineering, llm-inference, rag, agent-framework, developer-tools
- domain: large-language-models, artificial-intelligence, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, prompt-engineering, context-engineering, curated-resources, gpt, chatgpt, papers, courses, natural-language-processing, web-server

## Member repositories
- promptslab/Awesome-Prompt-Engineering (main) score 75

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:41.399658+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:46:17.553205+00:00, confidence not recorded.
  - readme: https://github.com/promptslab/Awesome-Prompt-Engineering (fetched 2026-08-28T04:09:41.399658+00:00, sha c00291c4c6aa)
  - homepage: https://discord.gg/m88xfYMbK6 (fetched 2026-08-29T08:43:03.562558+00:00, sha a230d7af2237)
- Data as of 2026-08-30T08:39:29.467469+00:00.