AEO Content Skill (Free)

Source: github.com/psyduckler/aeo-skills
Part of: AEO Skills Suite — Prompt Research → Content → Analytics

Create or refresh content that AI assistants want to cite — using zero paid APIs.

Requirements

• - web_fetch — analyze currently-cited sources and existing content
• INLINECODE1 — find competing content (Brave free tier, optional)
• LLM reasoning — research, brief, draft, and evaluate

Mode Detection

• - Create mode — User provides a target prompt but no existing URL → write new content
• Refresh mode — User provides an existing page URL (+ optional target prompt) → audit and update

Input

• - Target prompt (required for create, optional for refresh) — the AI prompt this content should win
• Brand/domain (required) — who the content is for
• Existing URL (refresh mode) — the page to update
• Topic context (optional) — additional info about the brand's angle
• Content type (optional) — guide, comparison, how-to, explainer

Create Mode Workflow

Step 1: AI Landscape Research

Search the target prompt and close variants to understand the current answer landscape:

1. 1. Web search the exact prompt — search engines show similar sources to what AI cites
2. web_fetch the top 5-10 results — these are the pages AI models draw from
3. web_search for "[topic]" site:reddit.com — find real user questions and discussions

For each top-ranking page, extract:

• - Main points and structure
• Unique data, frameworks, or insights
• Gaps — what they miss or get wrong
• Freshness — when was it last updated?

Step 2: Build the Content Brief

Use the template in references/content-brief-template.md to structure research.

Key decisions:

• - Mandatory topics — every sub-topic the AI currently covers in its answer
• Unique value angle — what will this content add that no current source provides? (Most important decision.)
• Content structure — outline with H2/H3 headings that mirror question phrasing
• Target specs — word count, format, tone

Step 3: Write Citation-Worthy Content

Draft following citation signals from references/citation-signals.md. Key principles:

• - Lead each section with a direct, quotable 1-2 sentence answer
• Use descriptive headings that match question phrasing
• Include original data, frameworks, or expert perspective
• Name specific tools, companies, people, statistics
• Cover every sub-question the AI currently answers, then go deeper on 2-3 areas
• Cut fluff — every paragraph earns its place

Step 4: Self-Evaluate

Before delivering, check the draft against currently-cited sources:

1. 1. Coverage — addresses every topic the top sources cover?
2. Depth — goes deeper on at least 2-3 areas?
3. Uniqueness — offers something no current source has?
4. Extractability — AI can pull a direct answer from each section?
5. Entity richness — specific names, tools, numbers throughout?
6. Freshness — examples, data, references are current?

Step 5: Deliver with Publishing Guidance

Output final content plus title, meta description (150-160 chars), and:

• - Add publication date + author byline with credentials
• Ensure page is indexable (no noindex, no paywall)
• Add schema markup if applicable (FAQ, HowTo, Article)
• Internal link from existing related content
• Re-check target prompt in AI models 2-4 weeks after indexing

Refresh Mode Workflow

Step R0: Audit the Existing Page

Before any landscape research, analyze the current page:

1. 1. web_fetch the existing URL — get the full content
2. Extract current structure: headings, topics covered, depth per section
3. Note: publication date, last updated date, author info
4. Check freshness: outdated stats, old tool names, expired examples, stale references
5. Identify what's already strong (keep these sections)

Step R1: AI Landscape Research

Same as Create Step 1 — research what AI models currently cite for the target prompt. If no target prompt was provided, infer it from the page's topic and title.

Step R2: Gap Analysis (Diff)

Compare existing content against the competitive landscape:

• - Missing topics — sub-topics AI covers that the page doesn't → flag for addition
• Outdated info — old statistics, discontinued tools, expired examples → flag for replacement
• Missing entities — competitors, tools, people the AI mentions that the page doesn't → flag for inclusion
• Structural issues — buried answers, vague headings, no clear extractable statements → flag for restructure
• Freshness gaps — old dates, prior-year references → flag for update
• Strengths to preserve — sections already well-written, potentially already cited → keep as-is

Output: a prioritized list of changes with rationale for each.

Step R3: Edit (Not Rewrite)

Apply changes surgically:

• - Add new sections for coverage gaps (place them logically in the existing structure)
• Update outdated data points, examples, tool names, statistics
• Restructure weak sections — add extractable lead sentences, improve headings
• Weave in missing entities naturally (don't keyword-stuff)
• Preserve sections that are already strong
• Update publication/modified date

Output the refreshed content with clear markup showing changes:

• - [ADDED] — new sections or paragraphs
• INLINECODE9 — modified existing content
• INLINECODE10 — reorganized for better extractability
• INLINECODE11 — kept as-is (note why it's strong)

Step R4: Before/After Summary

Provide a clear comparison:

• - What was added (new sections, topics, entities)
• What was updated (stats, examples, references)
• What was restructured (headings, lead sentences)
• What was removed (outdated info)
• Expected impact on citation-worthiness

Step R5: Self-Evaluate + Deliver

Same 6-point evaluation as Create Step 4, plus:

• - Does the refresh maintain the page's existing voice and style?
• Are all internal/external links still valid?
• Is the updated date reflected?

Deliver with the same publishing guidance as Create Step 5.

Tips

• - The unique value angle is make-or-break for both modes
• For refresh: resist the urge to rewrite everything. Surgical edits that add missing pieces are more efficient and preserve existing authority
• First-party data is the strongest citation signal — if the brand has relevant data, use it prominently
• For comparison prompts ("X vs Y"), be balanced — AI models avoid citing biased sources
• Shorter, sharper content that directly answers the prompt beats long rambling pieces
• This skill pairs with aeo-prompt-research-free which identifies target prompts