PlaybookPrompts

Generate a structured content brief from a live SERP analysis

Marketing & SEO content-briefseocontent-strategy

A content brief built from actual SERP signals — not assumptions — gives writers a much clearer target. This prompt turns raw SERP observations into a brief a writer can execute without further research.

Prompt
You are an SEO content strategist. I'm creating a brief for an article targeting the keyword: {{TARGET_KEYWORD}}.

Here is what I observed in the current SERP (paste titles, meta descriptions, and any featured snippet content you can see):
{{SERP_OBSERVATIONS}}

The site publishing this article: {{SITE_DESCRIPTION}}
Word count target (optional, leave blank if unknown): {{WORD_COUNT_TARGET}}

1. Identify the dominant search intent from the SERP data. Is it informational, commercial, or a mix? What format do most top results use (listicle, how-to, comparison, long-form guide)?

2. List the headings and subheadings the article should include, based on patterns across the top results. For each heading, write one sentence explaining what the section must accomplish — not just what it should be titled.

3. Identify 2–3 angles or sections that appear in some top results but not all — these represent opportunities to be more comprehensive without bloating the article.

4. Write the recommended H1, meta title (under 60 characters), and meta description (under 155 characters) for this article.

5. List 3 things the article should NOT do based on the SERP (e.g. avoid a format that the query clearly doesn't reward, or avoid going deeper on a subtopic that's clearly out of scope for this intent).

This brief is most accurate when the SERP data is from an incognito or location-specific search relevant to the target audience.
Variables to fill in
  • {{TARGET_KEYWORD}}
  • {{SERP_OBSERVATIONS}}
  • {{SITE_DESCRIPTION}}
  • {{WORD_COUNT_TARGET}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{TARGET_KEYWORD}}{{SERP_OBSERVATIONS}}{{SITE_DESCRIPTION}}{{WORD_COUNT_TARGET}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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Pair this prompt with a tool

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