Geo
liangdabiao/GEO-Content-Optimizer-Skill
完整的 GEO(生成式引擎优化)服务流水线:给一个产品官网 URL 和介绍材料, 做站点诊断与 AI 答案采样、生成带验收标准的执行工单、产出可直接部署的资产 (llms.txt / JSON-LD / 定义块 / FAQ / 内容大纲与初稿)、自动验收工单是否闭环、 并打包成可直接发给客户的交付物。可按周期复跑,做长期 GEO 运营与月报。
SEO and AI discovery (GEO) - schema, ChatGPT/Perplexity optimization
$ npx skills add alinaqi/maggy --skill web-content -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install alinaqi/maggy web-content --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/web-content .claude/skills/web-content && 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 "web-content" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/web-content into .claude/skills/web-content/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "web-content", 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/web-contentType 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 web-content -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install alinaqi/maggy web-content --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/web-content .agents/skills/web-content && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "web-content" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/web-content into .agents/skills/web-content/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "web-content", 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 web-content -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install alinaqi/maggy web-content --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/web-content .cursor/skills/web-content && 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 "web-content" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/web-content into .cursor/skills/web-content/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "web-content", 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/web-content--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 web-content -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install alinaqi/maggy web-content --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/web-content .gemini/skills/web-content && 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 "web-content" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/web-content into .gemini/skills/web-content/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "web-content", 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 web-contentInstalls 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 web-content -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/web-content .github/skills/web-content && 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 "web-content" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/web-content into .github/skills/web-content/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "web-content", 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 web-content -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 web-content --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/web-content .opencode/skills/web-content && 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 "web-content" agent skill from https://github.com/alinaqi/maggy/tree/main/skills/web-content into .opencode/skills/web-content/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "web-content", 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.
web-contentSEO and AI discovery (GEO) - schema, ChatGPT/Perplexity optimization
Web Content is an agent skill from alinaqi/maggy. SEO and AI discovery (GEO) - schema, ChatGPT/Perplexity optimization
Its SKILL.md is about 3.8k 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 Web search, AI search optimization and Schema markup. It works with OpenAI and Perplexity. 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.
7 steps, taken from the first numbered list 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, json, html, regex, javascript and bash).
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.orgtwitter.comlinkedin.comgithub.comvalidator.schema.orgsearch.google.comAlso links to:
skale.sogravitatedesign.comsurferseo.comsiddharthbharath.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.
Web Content loads about 3.8k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 488 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). 488 words, ~3,793 tokens.
.claude/skills/web-content/SKILL.md (or your agent's skills folder).For creating web content optimized for both traditional SEO and AI discovery (ChatGPT, Perplexity, Claude, Gemini).
Sources: GEO Complete Guide | AI Search SEO | LLM Optimization | Generative Engine Optimization
SEO gets clicks. GEO gets citations.
Traditional SEO optimizes for Google rankings. Generative Engine Optimization (GEO) optimizes for being cited by AI assistants. Modern content needs both:
AI traffic grew 1,200% between July 2024 and February 2025. Google's search share dropped below 90% for the first time in a decade. Optimize for both.
Write for humans, structure for machines.
AI systems prefer:
## Homepage Structure
### Above the Fold
- **Headline**: Clear value proposition (what you do + for whom)
- **Subheadline**: How you deliver that value
- **Primary CTA**: One clear action
- **Trust signals**: Logos, testimonials, stats
### Content Sections
1. **Problem Statement**: Pain point you solve
2. **Solution Overview**: How you solve it (3-4 key features)
3. **Social Proof**: Testimonials, case studies, logos
4. **How It Works**: 3-step process (simple)
5. **Pricing Preview**: Or link to pricing page
6. **FAQ Section**: 5-7 common questions (GEO gold)
7. **Final CTA**: Repeat primary action
### Schema Required
- Organization schema (name, logo, founding date, social links)
- WebSite schema with SearchAction
- FAQ schema for questions section## Product Page Structure
### Hero Section
- **Product Name**: Clear, descriptive
- **One-line Description**: What it does in 10 words or less
- **Key Benefit**: Primary value proposition
- **CTA**: Buy/Try/Demo
### Content Sections
1. **TL;DR Box**: 3-5 bullet summary (AI-quotable)
2. **Problem → Solution**: What problem, how solved
3. **Features Grid**: 4-6 features with icons
4. **Comparison Table**: vs. alternatives (GEO loves these)
5. **Use Cases**: Who uses it and how
6. **Testimonials**: Real names, photos, companies
7. **Pricing**: Clear tiers if applicable
8. **FAQ**: Product-specific questions
### Schema Required
- Product schema (name, description, price, availability)
- Review schema (aggregate rating)
- FAQ schema
- BreadcrumbList schema## Blog Post Structure
### Opening (First 100 words)
- **TL;DR**: Direct answer to the title's question
- **What you'll learn**: Bullet list of takeaways
- This section should be quotable standalone
### Body Structure
- **H2 sections**: Main topics (5-7 per article)
- **H3 subsections**: Supporting points
- **Bullet lists**: For scanability
- **Stat boxes**: Highlight key numbers
- **Comparison tables**: When comparing options
### Content Elements
- Definition boxes ("What is X?")
- Step-by-step instructions
- Code examples (if technical)
- Original statistics/research
- Expert quotes with attribution
### Closing
- **Summary**: Key takeaways (bulleted)
- **Next steps**: What reader should do
- **Related content**: Internal links
### Metadata Required
- Author name + bio + photo
- Publication date
- Last updated date (visible!)
- Reading time
- Article schema with author## FAQ Page Structure
### Organization
- Group questions by category
- Most common questions first
- Direct, concise answers
- Link to detailed pages for more info
### Question Format
Q: [Exact question users ask]
A: [Direct answer in first sentence, then elaboration]
### Schema Required
- FAQPage schema (critical for AI discovery)
- Each Q&A as Question/Answer schema## Landing Page Structure
### Single Focus
- One offer
- One audience
- One CTA (repeated)
### Sections
1. **Headline**: Benefit-focused, specific
2. **Problem Agitation**: Pain points
3. **Solution**: Your offer
4. **Proof**: Testimonials, stats, logos
5. **Features**: 3-5 key benefits
6. **Objection Handling**: FAQ or guarantee
7. **CTA**: Clear, urgent
### No Navigation
- Remove header nav (reduce exits)
- Single path: read → convert<div class="tldr-box">
<h3>TL;DR</h3>
<ul>
<li>Key point 1 with specific detail</li>
<li>Key point 2 with number/stat</li>
<li>Key point 3 with actionable insight</li>
</ul>
</div>Place at top of articles. AI systems extract these for summaries.
## What is [Term]?
[Term] is [concise definition in one sentence]. It [what it does] by [how it works].
**Key characteristics:**
- Characteristic 1
- Characteristic 2
- Characteristic 3Start with "What is X?" - AI systems look for this pattern.
| Feature | Product A | Product B | Our Product |
|---------|-----------|-----------|-------------|
| Price | $99/mo | $149/mo | $79/mo |
| Feature 1 | ✓ | ✗ | ✓ |
| Feature 2 | ✗ | ✓ | ✓ |
| Best For | Enterprise | Startups | SMBs |AI loves structured comparisons. Include in product and review pages.
<div class="stat-box">
<span class="stat-number">73%</span>
<span class="stat-label">of users prefer AI search for complex queries</span>
<span class="stat-source">Source: Adobe Analytics, 2024</span>
</div>Original statistics with sources get cited by AI.
## How to [Do Thing]
### Step 1: [Action Verb] [Object]
[Explanation of what to do]
**Example:**
[Concrete example]
### Step 2: [Action Verb] [Object]
[Explanation]
### Step 3: [Action Verb] [Object]
[Explanation]
**Result:** [What user achieves]Use HowTo schema markup for these.
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Your Company",
"url": "https://yoursite.com",
"logo": "https://yoursite.com/logo.png",
"foundingDate": "2020",
"description": "One sentence description",
"sameAs": [
"https://twitter.com/yourcompany",
"https://linkedin.com/company/yourcompany",
"https://github.com/yourcompany"
],
"contactPoint": {
"@type": "ContactPoint",
"email": "hello@yoursite.com",
"contactType": "customer service"
}
}{
"@context": "https://schema.org",
"@type": "Article",
"headline": "Article Title",
"description": "Meta description",
"image": "https://yoursite.com/article-image.jpg",
"author": {
"@type": "Person",
"name": "Author Name",
"url": "https://yoursite.com/team/author-name",
"jobTitle": "Role at Company",
"sameAs": [
"https://linkedin.com/in/author",
"https://twitter.com/author"
]
},
"publisher": {
"@type": "Organization",
"name": "Your Company",
"logo": {
"@type": "ImageObject",
"url": "https://yoursite.com/logo.png"
}
},
"datePublished": "2025-01-15",
"dateModified": "2025-01-20"
}{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is your product?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Direct answer here. Keep concise but complete."
}
},
{
"@type": "Question",
"name": "How much does it cost?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Pricing starts at $X/month for basic plan..."
}
}
]
}{
"@context": "https://schema.org",
"@type": "Product",
"name": "Product Name",
"description": "Product description",
"image": "https://yoursite.com/product.jpg",
"brand": {
"@type": "Brand",
"name": "Your Company"
},
"offers": {
"@type": "Offer",
"price": "29.99",
"priceCurrency": "USD",
"availability": "https://schema.org/InStock"
},
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.8",
"reviewCount": "127"
}
}{
"@context": "https://schema.org",
"@type": "HowTo",
"name": "How to Set Up Your Account",
"description": "Step-by-step guide to getting started",
"step": [
{
"@type": "HowToStep",
"name": "Create account",
"text": "Go to signup page and enter your email"
},
{
"@type": "HowToStep",
"name": "Verify email",
"text": "Click the link in the verification email"
}
]
}✅ DO:
- TL;DR sections at top of articles
- Consistent formatting (headers, bullets)
- Named authors with credentials
- Original research and statistics
- Multi-intent content (covers related questions)
❌ AVOID:
- Thin content without substance
- Missing author attribution
- Outdated information (no dates)✅ DO:
- Original statistics with sources
- Comparison tables and structured data
- Clean URL slugs (/topic-name not /p=123)
- Short, declarative statements
- Images, charts, diagrams
- YouTube videos (Perplexity shows these)
❌ AVOID:
- Generic content without unique insights
- Missing citations/sources
- Poor URL structure✅ DO:
- Well-structured, logical content
- Clear definitions and explanations
- Technical accuracy
- Balanced perspectives
- Proper citations
❌ AVOID:
- Misleading or sensational content
- Missing context
- Outdated technical information✅ DO:
- Rich schema markup
- Detailed image alt-text
- YouTube content (Google-owned)
- Multimedia (video, audio with transcripts)
❌ AVOID:
- Missing structured data
- Images without alt-text
- Text-only content<article>
<header>
<h1>Article Title</h1>
<div class="meta">
<span class="author">By John Smith</span>
<span class="published">Published: January 15, 2025</span>
<span class="updated">Last updated: January 20, 2025</span>
</div>
</header>
</article>AI systems prefer recent content. Show dates prominently.
| Content Type | Update Frequency |
|---|---|
| Product pages | On feature changes |
| Pricing | Immediately on change |
| Blog posts | Quarterly review |
| Statistics | When new data available |
| Guides | Semi-annually |
.*chatgpt\.com.*|.*perplexity\.ai.*|.*gemini\.google\.com.*|.*copilot\.microsoft\.com.*|.*openai\.com.*|.*claude\.ai.*|.*poe\.com.*|.*you\.com.*|.*phind\.com.*// Check for AI referrer
const aiReferrers = [
'chatgpt.com',
'chat.openai.com',
'perplexity.ai',
'claude.ai',
'gemini.google.com',
'copilot.microsoft.com',
'poe.com',
'you.com',
'phind.com'
];
const referrer = document.referrer;
const isAIReferral = aiReferrers.some(ai => referrer.includes(ai));
if (isAIReferral) {
analytics.track('ai_referral', {
source: referrer,
page: window.location.pathname
});
}Add to forms:
How did you hear about us?
- [ ] Google Search
- [ ] ChatGPT
- [ ] Perplexity
- [ ] Claude
- [ ] Social Media
- [ ] Referral
- [ ] Other## SEO Checklist
- [ ] Title tag (50-60 chars) with primary keyword
- [ ] Meta description (150-160 chars) with CTA
- [ ] URL slug is clean and descriptive
- [ ] H1 matches title intent
- [ ] H2/H3 hierarchy is logical
- [ ] Images have descriptive alt-text
- [ ] Internal links to related content
- [ ] External links to authoritative sources
## GEO Checklist
- [ ] TL;DR or summary at top
- [ ] Direct answer to main question in first paragraph
- [ ] Stat boxes with sources
- [ ] Comparison tables where applicable
- [ ] FAQ section with schema
- [ ] Author name, bio, and credentials
- [ ] Publication and last-updated dates visible
- [ ] Schema markup validated
- [ ] Content can be quoted standalone
- [ ] Original insights or data included# Validate schema markup
# Use: https://validator.schema.org/
# Or: https://search.google.com/test/rich-resultsproject/
├── content/
│ ├── pages/
│ │ ├── home.md
│ │ ├── about.md
│ │ ├── pricing.md
│ │ └── contact.md
│ ├── blog/
│ │ ├── post-1.md
│ │ └── post-2.md
│ └── legal/
│ ├── privacy.md
│ └── terms.md
├── components/
│ ├── SchemaMarkup.tsx
│ ├── TLDRBox.tsx
│ ├── StatBox.tsx
│ ├── FAQSection.tsx
│ └── AuthorBio.tsx
└── lib/
└── schema.ts # Schema generators| Page Type | Schema |
|---|---|
| Homepage | Organization, WebSite |
| Blog Post | Article, Author, FAQ |
| Product | Product, Review, FAQ |
| FAQ | FAQPage |
| How-to | HowTo |
| About | Organization, Person |
© 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/web-content of alinaqi/maggy.
Open the folder on GitHubat commit 72a456e
Web Content 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 |
|---|---|---|---|---|---|---|
| Web Content this skillalinaqi/maggy | 707 | — | ~3.8k | Automated safety check: Pass | MIT | |
| Geoliangdabiao/GEO-Content-Optimizer-Skill | 205 | 1 repos | ~2.3k | Automated safety check: Notes | MIT | |
| Geo Optimizerliangdabiao/GEO-Content-Optimizer-Skill | 205 | — | ~1.1k | Automated safety check: Pass | None | |
| Geo Optimizerhuifer/claude-code-seo | 110 | — | ~650 | Automated safety check: Notes | MIT | |
| SEO Geo OptimizerNeverSight/learn-skills.dev | 216 | 1 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Money SEOiamzifei/show-me-the-money | 1k | — | ~4.4k | Automated safety check: Pass | Custom licence |
liangdabiao/GEO-Content-Optimizer-Skill
完整的 GEO(生成式引擎优化)服务流水线:给一个产品官网 URL 和介绍材料, 做站点诊断与 AI 答案采样、生成带验收标准的执行工单、产出可直接部署的资产 (llms.txt / JSON-LD / 定义块 / FAQ / 内容大纲与初稿)、自动验收工单是否闭环、 并打包成可直接发给客户的交付物。可按周期复跑,做长期 GEO 运营与月报。
liangdabiao/GEO-Content-Optimizer-Skill
GEO (Generative Engine Optimization) 全流程优化工具。帮助品牌内容被 ChatGPT、Perplexity、Gemini 等 AI 搜索引擎引用。
huifer/claude-code-seo
生成式引擎优化专家,分析和优化内容在 AI 搜索引擎(ChatGPT、Claude、Perplexity、Google SGE)中的可见性和引用率。
NeverSight/learn-skills.dev
Comprehensive SEO/GEO/AEO analysis toolkit for optimizing content visibility across traditional search engines (Google, Bing), AI platforms (ChatGPT, Perplexity, Claude, Gemini, Grokipedia), answer…
iamzifei/show-me-the-money
SEO and GEO (Generative Engine Optimization) for organic traffic and AI search visibility.
indranilbanerjee/digital-marketing-pro
Audit whether AI agents and AI crawlers can actually use a site — robots.txt rules per AI crawler token (OpenAI, Anthropic and Perplexity bots, Google-Extended, Applebot-Extended)…
alinaqi/maggy
AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
alinaqi/maggy
Claude Code Agent Teams - default team-based development with strict TDD pipeline enforcement
alinaqi/maggy
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
alinaqi/maggy
Android Java development with MVVM, ViewBinding, and Espresso testing
alinaqi/maggy
Android Kotlin development with Coroutines, Jetpack Compose, Hilt, and MockK testing
alinaqi/maggy
AI-driven testing agent that auto-discovers, generates, executes, evaluates, and fixes tests for any project type
Works with
Categories
SEO and AI discovery (GEO) - schema, ChatGPT/Perplexity optimization. Web Content is an agent skill from alinaqi/maggy.
Web Content fits situations like: tasks that involve Web search; tasks that involve AI search optimization; tasks that involve Schema markup.
Run `npx skills add alinaqi/maggy --skill web-content -a claude-code`. Or copy the skill folder (skills/web-content in alinaqi/maggy) into .claude/skills/web-content in your project. Claude Code loads it when a task matches its description.
Run `npx skills add alinaqi/maggy --skill web-content -a codex`. Or copy the skill folder (skills/web-content in alinaqi/maggy) into .agents/skills/web-content 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 web-content -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/web-content, .gemini/skills/web-content, .github/skills/web-content and .opencode/skills/web-content in your project.
SKILL.md names no scripts, command-line tools or credentials: Web Content is instructions for the agent only.
SKILL.md names 10 domains. In commands or code: schema.org, twitter.com, linkedin.com, github.com, validator.schema.org and search.google.com; the agent is likely to contact these when it follows the instructions. As links in the text: skale.so, gravitatedesign.com, surferseo.com and siddharthbharath.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.
Web Content is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.8k 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 Web Content: Geo (liangdabiao/GEO-Content-Optimizer-Skill, 205 stars), Geo Optimizer (liangdabiao/GEO-Content-Optimizer-Skill, 205 stars), Geo Optimizer (huifer/claude-code-seo, 110 stars) and SEO Geo Optimizer (NeverSight/learn-skills.dev, 216 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.