# anthropics/prompt-eng-interactive-tutorial

Anthropic's Interactive Prompt Engineering Tutorial

Repository: https://github.com/anthropics/prompt-eng-interactive-tutorial
Canonical: https://ross.abutalabs.com/products/prompt-eng-interactive-tutorial
Language: Jupyter Notebook
License Family: other
Last push: 2026-03-01T17:07:40+00:00

## Health v2 (maintenance only)
Score: 56/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 70, release rhythm 35, longevity 63
- inputs: {"age_days": 883, "days_push": 185, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 37798, forks 4166 (observed 2026-08-28T04:12:01.575407+00:00)

## What it is
Anthropic's official interactive tutorial for prompt engineering with Claude, delivered as Jupyter Notebooks across 9 chapters with exercises and an example playground. It teaches prompt structure, common failure modes, and advanced techniques like chaining, tool use, and retrieval.

## Use cases
- learn prompt engineering for Claude
- how to write better LLM prompts
- avoid hallucinations with prompt techniques
- build complex prompts for chatbots
- practice prompt writing with exercises
- understand Claude strengths and weaknesses

## When to choose
- you are new to prompting Claude or LLMs generally
- you want hands-on exercises with an interactive playground
- you need structured coverage from basic to advanced prompting techniques

## When to avoid
- you need a production prompt management or evaluation tool rather than a tutorial
- you want vendor-neutral guidance covering many LLM providers
- you require a licensed or certified training course

## Facets
- artifact type: learning-resource
- maturity: active
- function: prompt-engineering, developer-tools
- domain: large-language-models, tutorials, artificial-intelligence
- platform: python, cross-platform
- tags: anthropic, claude, jupyter-notebook, interactive-tutorial, llm, prompting, education

## Member repositories
- anthropics/prompt-eng-interactive-tutorial (main) score 56

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:01.575407+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 2026-08-29T16:25:12.501845+00:00, confidence not recorded.
  - readme: https://github.com/anthropics/prompt-eng-interactive-tutorial (fetched 2026-08-28T04:12:01.575407+00:00, sha 89092e56106f)
- Data as of 2026-08-30T08:39:29.467469+00:00.