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Aeo content brief generator

Skill saurabhshuklagrowisto/saurabh-ai-systems/claude-skills/aeo-content-brief-generator

AI architect for GTM and martech. I design and ship production agentic systems for B2B sales and marketing: lead scraping and scoring with an eval gated learning loop, autonomous CRM enrichment, ABM pipelines, live dashboards that refresh themselves, MCP servers and Claude skills. Built at Growisto.

Install
npx -y skills add saurabhshuklagrowisto/saurabh-ai-systems --skill aeo-content-brief-generator

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What its author says it does

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Turns a "content" gap (a buyer question with no owned page answering it) into a writable brief -- the question's shape (how-to, best-of, comparison, definition), the matching schema type, a fact-grounded direct-answer opener, and a section outline with a word-count target. Never fabricates data -- when no real facts are supplied it scaffolds an explicit [INSERT] placeholder instead of inventing a claim. Use this on the `content`-type fixes returned by the AEO/GEO Improvement Bot, or on any raw list of buyer questions that need an AI-answer-shaped page written.

SKILL.md

2.9 KB, as published. Nobody here has run it

AEO Content Brief Generator

Third piece of the AEO/GEO loop. AEO / LLM Visibility Audit finds the gap questions. AEO / GEO Improvement Bot diagnoses which ones need net-new content. This skill turns each of those into a brief a writer can execute today, without inventing the facts that make the answer citable.

When to use

  • On the content-type fixes from the improvement bot's fixes[].
  • Any time the ask is "write a page that answers X the way an AI assistant would quote it" -- direct answer first, structure after.

When NOT to use

  • For schema, citation, or authority fixes -- those need markup, outreach, or backlinks, not a new page. Route them to a schema-audit or outreach skill instead.
  • As a final draft -- this produces a brief and an opener grounded in supplied facts, not the full article. A writer (human or a long-form content skill) still builds it out.

Method

  1. Classify the question's shape from its wording -- "how to" → how-to, "best/top/tools" → best-of/listicle, "vs/compare" → comparison, "what is/why" → definition, else general.
  2. Match the shape to the schema type an AI crawler parses most reliably for that shape (HowTo, ItemList, FAQPage).
  3. Draft the direct-answer opener strictly from the facts supplied for that question. If none are supplied, emit an explicit [INSERT: ...] placeholder rather than a fabricated claim -- ship-blocking on purpose.
  4. Return a section outline and word-count target sized to the shape, so the brief is handoff-ready.

Inputs

  • brand -- the brand name
  • questions[] -- each {question, facts[]}. facts are real, verifiable proof points about the brand relevant to that question; leave empty if none exist yet.

Output (JSON)

briefs[] (each with question, shape, recommended_schema, title_suggestion, opener_draft, sections[], word_count_target, needs_real_data), questions_missing_data[], and a one-line summary.

Run it

python scripts/content_brief.py         # built-in sample
python scripts/content_brief.py in.json # your own brand + questions + facts

Zero dependencies, no API keys. Feed its briefs[] to whatever writes the full page; feed questions_missing_data[] back to the brand team as "we need real proof points before this can publish."

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