Aeo Content Free

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.

Context: Why This Matters Now

Google's AI Overviews and Search AI Mode are powered by Gemini 3 Flash — the model that decides which sources get cited when users ask questions. Influence happens at retrieval, not inside the model — you can't edit training data, but you can enter the "candidate set" the model selects from when it searches the web. Gemini is search-first, searching before nearly every answer, which means creating the right content can get you into the recurring retrieval set — the sources the model consistently draws from. Influence compounds through repeated inclusion.

Requirements

• web_fetch — analyze currently-cited sources and existing content
• web_search — find competing content (Brave free tier, optional)
• LLM reasoning — research, brief, draft, and evaluate
• Optional: Gemini API key (free) — use gemini-3-flash-preview with grounding to directly test what the model cites for your target prompt before and after content creation (20 samples recommended for reliable signal)

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

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Create Mode Workflow

Step 1: AI Landscape Research

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

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. 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 4b: Pre-Publish Simulation (Optional, Recommended)

Before delivering the final content, simulate how the target prompt currently performs in AI Overviews. This previews the current candidate set your content needs to outperform to enter the recurring retrieval set.

1. If the agent has access to the Gemini API (GEMINI_API_KEY), run the target prompt through gemini-3-flash-preview with Google Search grounding (20 runs)
2. From the simulation results, document:

• Currently cited sources — the top 5 URLs Gemini cites right now, with citation frequency. These are the current recurring retrieval set for this prompt.
• Current answer structure — what Gemini says, what topics it covers, what entities it names
• Your content's gap advantage — specific ways the new content outperforms each currently-cited source (based on the draft vs each source)
• Predicted citation path — which sections of your content are most likely to get cited and why (based on what the model searches for and what the current sources lack)

1. Include this as an appendix to the delivered content: "AI Overview Simulation (Pre-Publish)"

This step turns the content brief from heuristic-based to data-driven by showing exactly what your content needs to beat. The simulation reveals the current candidate set — the sources you must outperform to enter the recurring retrieval set where influence compounds through repeated inclusion.

Note: This step is optional but highly recommended. Skip only if no Gemini API key is available or if speed is critical.

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

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Refresh Mode Workflow

Step R0: Audit the Existing Page

Before any landscape research, analyze the current page:

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 R2b: Pre-Refresh Simulation (Optional, Recommended)

Same as Create Mode Step 4b, but run before editing. This tells you:

• What the current candidate set looks like for your target prompt
• Whether your existing page is already in the recurring retrieval set (and at what position)
• Which specific gaps in your content are keeping you out (or pushing you down)
• What the edit needs to accomplish to enter or improve position in the candidate set

Run the target prompt through gemini-3-flash-preview with Google Search grounding (20 runs). Document the results and use them to prioritize edits in Step R3 — focus on the gaps that will move you into or up in the recurring retrieval set.

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
• [UPDATED] — modified existing content
• [RESTRUCTURED] — reorganized for better extractability
• [UNCHANGED] — 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.

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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

Further Reading

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: psyduckler
• Source: psyduckler/aeo-skills
• License: MIT

Install and usage instructions live in the source repository linked above.