Geo Fundamentals
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
$ npx skills add alinaqi/maggy --skill aeo-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install alinaqi/maggy aeo-optimization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aeo-optimization .claude/skills/aeo-optimization && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "aeo-optimization" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimization into .claude/skills/aeo-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeo-optimization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add alinaqi/maggy --skill aeo-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install alinaqi/maggy aeo-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/aeo-optimization .agents/skills/aeo-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "aeo-optimization" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimization into .agents/skills/aeo-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeo-optimization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add alinaqi/maggy --skill aeo-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install alinaqi/maggy aeo-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/aeo-optimization .cursor/skills/aeo-optimization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "aeo-optimization" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimization into .cursor/skills/aeo-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeo-optimization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/alinaqi/maggy.git --path skills/aeo-optimization--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add alinaqi/maggy --skill aeo-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install alinaqi/maggy aeo-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/aeo-optimization .gemini/skills/aeo-optimization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "aeo-optimization" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimization into .gemini/skills/aeo-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeo-optimization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install alinaqi/maggy aeo-optimizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add alinaqi/maggy --skill aeo-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/aeo-optimization .github/skills/aeo-optimization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "aeo-optimization" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimization into .github/skills/aeo-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeo-optimization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add alinaqi/maggy --skill aeo-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install alinaqi/maggy aeo-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alinaqi/maggy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/aeo-optimization .opencode/skills/aeo-optimization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "aeo-optimization" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/aeo-optimization into .opencode/skills/aeo-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aeo-optimization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
aeo-optimizationAI Engine Optimization - semantic triples, page templates, content clusters for AI citations
Aeo Optimization is an agent skill from alinaqi/maggy. AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Marketing & SEO, covering AI search optimization. It works with OpenAI. The repository describes itself as: What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 72a456e. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and html).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
schema.orgAlso links to:
hubspot.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Aeo Optimization loads about 3.7k tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 817 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from alinaqi/maggy at commit 72a456e, republished under its MIT licence (© alinaqi). 817 words, ~3,677 tokens.
.claude/skills/aeo-optimization/SKILL.md (or your agent's skills folder).Purpose: Optimize content for AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) so your brand gets cited in AI-generated answers.
Source: Based on HubSpot's AEO Guide and industry best practices.
┌────────────────────────────────────────────────────────────────┐
│ THE GREAT DECOUPLING │
│ ──────────────────────────────────────────────────────────── │
│ Impressions ≠ Clicks anymore. │
│ AI engines compile answers from multiple sources. │
│ More buyer journey happens inside chat experiences. │
│ 58% of Google searches = zero clicks (AI overviews). │
├────────────────────────────────────────────────────────────────┤
│ THE OPPORTUNITY │
│ ──────────────────────────────────────────────────────────── │
│ Shape what AI engines say about your category and product. │
│ Get cited as the authoritative source. │
│ Best answer > Best page ranking. │
└────────────────────────────────────────────────────────────────┘Key Stats:
AI engines use three main signals to select content for answers:
Facts that appear across multiple credible sources get trusted and reused.
How to build consensus:
Net-new insight beats generic advice. AI engines prefer content that adds value.
How to add information gain:
Clear entities and tidy structure reduce ambiguity and boost quotability.
How to optimize structure:
What they are: Compact facts that AI engines (and humans) can't misread.
Pattern: [Subject] [verb] [object].
✅ GOOD (clear triples):
- HubSpot CRM syncs contact and company data.
- Lead Scoring assigns priority based on engagement.
- Workflows trigger email sequences from events.
❌ BAD (vague, no clear entity):
- The system helps with various tasks.
- It can do many things for users.
- This improves overall performance.For every key claim, ask:
Every substantive paragraph should follow this structure:
[Feature] helps [User/Role] with [Job].
It [mechanism/inputs] to [process].
Teams see [metric/result] in [timeframe/context].
Triples:
- [Subject] [verb] [object].
- [Subject] [verb] [object].Lead Scoring helps sales teams prioritize prospects. It combines
page views, email engagement, and firmographic data to assign a
numeric score, then auto-enrolls high scorers into follow-up
sequences. Reps focus on qualified accounts and book 40% more
meetings.
- Lead Scoring assigns scores from engagement data.
- High scorers trigger automated follow-up sequences.Goal: Define the category, tie it to your product, earn citations.
# What is [Category]? — [1-2 line value promise]
## What is [Category]? (~80 words)
[Plain definition in everyday language. Name adjacent entities.]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## Why it matters now (~60 words)
[One paragraph. Mention shift to answers over links; tie to buyer outcomes.]
## How to apply it (3-5 bullets)
- [Action 1]
- [Action 2]
- [Action 3]
## FAQ
**Q: [Question]?**
A: [~1 sentence answer]
**Q: [Question]?**
A: [~1 sentence answer]
**Q: [Question]?**
A: [~1 sentence answer]
---
**Links:** [Category hub] | [Product/Feature] | [Credible source 1] | [Credible source 2]
**CTA:** [Demo / Template / Signup]
**Schema:** Article + FAQ. Author + last updated.Goal: Clarify capability, fit, and next step; reinforce category linkage.
# [Product/Feature] — [Outcome in 3-5 words]
**[Product/Feature] enables [Outcome] for [User/Role].**
## [Feature Area 1]
[2-4 sentences using Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## [Feature Area 2]
[2-4 sentences using Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## [Feature Area 3]
[2-4 sentences using Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## FAQ
**Q: [Question]?**
A: [~1 sentence]
**Q: [Question]?**
A: [~1 sentence]
**Q: [Question]?**
A: [~1 sentence]
---
**Links:** Back to [Category Explainer] | Forward to [Demo/Trial]
**Proof:** [Benchmark/Analyst/Customer proof]
**Notes:** Requirements/limits (pricing tier, integrations)
**Schema:** Article + FAQ. Author + last updated.Goal: Help readers decide with clear criteria; earn fair citations.
# [Product] vs. [Alternative] — Which fits [Use case]?
## Comparison Table
| Criterion | [Product] | [Alt A] | [Alt B] | Source |
|-----------|-----------|---------|---------|--------|
| [Feature/Limit] | [value] | [value] | [value] | [link] |
| [Requirement] | [value] | [value] | [value] | [link] |
| [Best for] | [value] | [value] | [value] | [link] |
*Source-back all claims in the table or footnotes.*
## Fit Statements
1. **[Product]** suits [Team/Use case] when [Condition].
2. **[Alt A]** fits [Team/Use case] when [Condition].
3. **[Alt B]** works for [Team/Use case] when [Condition].
---
**Links:** [Category Explainer] | [Feature pages]
**CTA:** [Try / Demo / Talk to Sales]
**Schema:** Article. Author + last updated.Goal: Connect product to outcomes in a context readers recognize.
# [Industry/Use Case] — [Outcome KPI]
**Teams reduce [Metric] by [Y%] in [Timeframe].**
## Mini Case Study
[Company/Role] used [Product/Feature] to [Action], resulting in
[Metric improvement] within [Timeframe].
## How It Works
### [Feature 1]
[Feature → How → Outcome paragraph]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
### [Feature 2]
[Feature → How → Outcome paragraph]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## Who Uses This
**Roles:** [Role 1], [Role 2], [Role 3]
**Workflows:** [Workflow 1], [Workflow 2]
**Integrations:** [Integration 1], [Integration 2]
---
**Links:** [Product/Feature pages] | [Supporting blog]
**CTA:** [Industry template / Demo variant]
**Schema:** Article. Author + last updated.Goal: Add information gain and support your content cluster.
# [Topic] — [Specific promise]
## Opening (~60-80 words)
[State the problem. Align terminology with Category Explainer. Preview outcome.]
## [Section 1 Heading] (~120 words max)
[Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
**Internal link:** [Related page]
**External citation:** [Credible source]
## [Section 2 Heading] (~120 words max)
[Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
**Internal link:** [Related page]
**External citation:** [Credible source]
## Key Takeaway
[1-2 lines summarizing the main point]
**CTA:** [Single primary action]
---
**Schema:** Article. Author + last updated.| Element | Implementation |
|---|---|
| Schema markup | Article + FAQ (if FAQ exists) |
| Author attribution | Name, bio, credentials, photo |
| Last updated date | Visible, machine-readable |
| Internal links | 3-5 per page (upstream/downstream) |
| External citations | 1-2 credible sources per section |
| Single CTA | Demo, template, or signup (repeated once near end) |
<!-- Article Schema -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "[Page Title]",
"author": {
"@type": "Person",
"name": "[Author Name]",
"url": "[Author Bio URL]"
},
"datePublished": "[ISO Date]",
"dateModified": "[ISO Date]",
"publisher": {
"@type": "Organization",
"name": "[Company]",
"logo": "[Logo URL]"
}
}
</script>
<!-- FAQ Schema (if FAQ section exists) -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "[Question 1]",
"acceptedAnswer": {
"@type": "Answer",
"text": "[Answer 1]"
}
},
{
"@type": "Question",
"name": "[Question 2]",
"acceptedAnswer": {
"@type": "Answer",
"text": "[Answer 2]"
}
}
]
}
</script> ┌─────────────────────┐
│ Category Explainer │
│ "What is AEO?" │
└──────────┬──────────┘
│
┌──────────────────────┼──────────────────────┐
│ │ │
▼ ▼ ▼
┌───────────────┐ ┌───────────────┐ ┌───────────────┐
│ Product Page │ │ Product Page │ │ Product Page │
│ "Feature A" │ │ "Feature B" │ │ "Feature C" │
└───────┬───────┘ └───────┬───────┘ └───────┬───────┘
│ │ │
▼ ▼ ▼
┌───────────────┐ ┌───────────────┐ ┌───────────────┐
│ Blog Post │ │ Use Case │ │ Comparison │
│ (supports) │ │ (industry) │ │ (vs. alt) │
└───────────────┘ └───────────────┘ └───────────────┘Linking Rules:
| Metric | How to Track |
|---|---|
| AI citations | Manual checks in ChatGPT, Claude, Perplexity |
| Brand mentions in AI | Search "[brand] + [category]" in AI engines |
| Share of answer | How often you're cited vs competitors |
| LLM traffic | GA4 referral from chatgpt.com, claude.ai, perplexity.ai |
| Impressions-to-clicks gap | GSC impressions vs actual clicks |
| Mistake | Fix |
|---|---|
| Vague language ("it helps with things") | Use specific entities and triples |
| No clear structure | Use Feature → How → Outcome |
| Missing schema | Add Article + FAQ schema |
| No author attribution | Add author name, bio, credentials |
| Generic content | Add original data, examples, POV |
| Orphan pages | Link into content cluster |
| Fence-sitting ("it depends") | Take a clear position |
| No external citations | Add 1-2 credible sources per section |
| Aspect | Traditional SEO | AEO |
|---|---|---|
| Goal | Rank on page 1 | Get cited in AI answers |
| Success metric | Click-through rate | Share of answer |
| Content focus | Keywords | Entities + facts |
| Structure | Headers for scanning | Triples for extraction |
| Links | Backlinks for authority | Citations for consensus |
| Updates | Periodic refresh | Continuous accuracy |
[Entity/Product] [active verb] [concrete object/result].[Feature] helps [User] with [Job].
It [mechanism] to [process].
Teams see [result] in [timeframe].© alinaqi, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/aeo-optimization of alinaqi/maggy.
Open the folder on GitHubat commit 72a456e
Aeo Optimization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Aeo Optimization this skillalinaqi/maggy | 707 | — | ~3.7k | Automated safety check: Pass | MIT | |
| Geo Fundamentalswasp-lang/wasp | 19k | 9 repos | ~861 | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude | 11k | — | ~2.8k | Automated safety check: Notes | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 791 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Fire Your SEO Agencyleopard627/fire-your-seo-agency | 707 | — | ~1.1k | Automated safety check: Pass | MIT |
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
ReScienceLab/opc-skills
SEO & GEO (Generative Engine Optimization) for websites. An agent skill from ReScienceLab/opc-skills.
zubair-trabzada/geo-seo-claude
Audits a website for AI search visibility across ChatGPT, Claude, Perplexity and Google AI Overviews while checking traditional SEO, schema and E-E-A-T content quality.
AgriciDaniel/codex-seo
Live SEO data via DataForSEO MCP server. An agent skill from AgriciDaniel/codex-seo.
leopard627/fire-your-seo-agency
SEO·AEO·GEO·LLMO·NEO(네이버) 다섯 레인을 진단하고 직접 구현하며, 인용되는 콘텐츠를 계속 생산하는 서브 블로그·콘텐츠 운영 파이프라인까지 세팅하는 스킬.
Yuzzyuk/marketing-os
A complete marketing department in one skill. An agent skill from Yuzzyuk/marketing-os.
alinaqi/maggy
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
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Works with
Categories
AI Engine Optimization - semantic triples, page templates, content clusters for AI citations. Aeo Optimization is an agent skill from alinaqi/maggy.
Aeo Optimization fits situations like: tasks that involve AI search optimization.
Run `npx skills add alinaqi/maggy --skill aeo-optimization -a claude-code`. Or copy the skill folder (skills/aeo-optimization in alinaqi/maggy) into .claude/skills/aeo-optimization in your project. Claude Code loads it when a task matches its description.
Run `npx skills add alinaqi/maggy --skill aeo-optimization -a codex`. Or copy the skill folder (skills/aeo-optimization in alinaqi/maggy) into .agents/skills/aeo-optimization in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alinaqi/maggy --skill aeo-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aeo-optimization, .gemini/skills/aeo-optimization, .github/skills/aeo-optimization and .opencode/skills/aeo-optimization in your project.
SKILL.md names no scripts, command-line tools or credentials: Aeo Optimization is instructions for the agent only.
SKILL.md names 2 domains. In commands or code: schema.org; the agent is likely to contact it when it follows the instructions. As links in the text: hubspot.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Aeo Optimization is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Aeo Optimization: Geo Fundamentals (wasp-lang/wasp, 19k stars), SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars) and SEO Dataforseo (AgriciDaniel/codex-seo, 791 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
alinaqi (a GitHub user) maintains it in alinaqi/maggy, which has 707 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on September 24, 2026.
Source: alinaqi/maggy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.