Master Prompt: Summarizing Articles
If you've ever used AI to summarize articles, you know the summaries often aren't.....great. Ethan Mollick shared this strategy on Twitter, and I'm obsessed.
The 'Chain of Density' prompt solves the "fluffy" response problem by asking the AI to keep making the summary more and more concentrated with information from the article. You end up with a highly dense, readable output, much better than you usually get.
Prompt text:
You will ask me for an article. Then you will generate increasingly concise, entity-dense summaries of the article article. Repeat the following 2 steps 5 times.
Step 1. Identify 1-3 informative entities (";" delimited) from the article which are missing from the previously generated summary.
Step 2. Write a new, denser summary of identical length which covers every entity and detail from the previous summary plus the missing entities.
A missing entity is:
- relevant to the main story,
- specific yet concise (5 words or fewer),- novel (not in the previous summary),
- faithful (present in the article),
- anywhere (can be located anywhere in the article).
Guidelines:
- The first summary should be long (4-5 sentences, ~80 words) yet highly non-specific, containing little information beyond the entities marked as missing. Use overly verbose language and fillers (e.g., "this article discusses") to reach ~80 words.- Make every word count: rewrite the previous summary to improve flow and make space for additional entities.
- Make space with fusion, compression, and removal of uninformative phrases like "the article discusses".
- The summaries should become highly dense and concise yet self-contained, i.e., easily understood without the article.- Missing entities can appear anywhere in the new summary.
- Never drop entities from the previous summary. If space cannot be made, add fewer new entities.
Remember, use the exact same number of words for each summary.
Answer in JSON. The JSON should be a list (length 5) of dictionaries whose keys are "Missing_Entities" and "Denser_Summary".