Global SEO Growth
minhnv0807/ai-business-skills
Covers six SEO layers for a website: crawl and index audit, local SEO, search-intent content, AI search visibility, schema markup and backlink or directory distribution.
When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok.
Install AI Local Search
$ npx skills add garrettjsmith/localseoskills --skill ai-local-search -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install garrettjsmith/localseoskills ai-local-search --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/garrettjsmith/localseoskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-local-search .claude/skills/ai-local-search && 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 "ai-local-search" agent skill from https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search into .claude/skills/ai-local-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-local-search", 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/garrettjsmith/localseoskills/tree/main/skills/ai-local-searchType 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 garrettjsmith/localseoskills --skill ai-local-search -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install garrettjsmith/localseoskills ai-local-search --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garrettjsmith/localseoskills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-local-search .agents/skills/ai-local-search && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-local-search" agent skill from https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search into .agents/skills/ai-local-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-local-search", 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 garrettjsmith/localseoskills --skill ai-local-search -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install garrettjsmith/localseoskills ai-local-search --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garrettjsmith/localseoskills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-local-search .cursor/skills/ai-local-search && 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 "ai-local-search" agent skill from https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search into .cursor/skills/ai-local-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-local-search", 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/garrettjsmith/localseoskills.git --path skills/ai-local-search--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 garrettjsmith/localseoskills --skill ai-local-search -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install garrettjsmith/localseoskills ai-local-search --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garrettjsmith/localseoskills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-local-search .gemini/skills/ai-local-search && 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 "ai-local-search" agent skill from https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search into .gemini/skills/ai-local-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-local-search", 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 garrettjsmith/localseoskills ai-local-searchInstalls 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 garrettjsmith/localseoskills --skill ai-local-search -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/garrettjsmith/localseoskills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-local-search .github/skills/ai-local-search && 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 "ai-local-search" agent skill from https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search into .github/skills/ai-local-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-local-search", 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 garrettjsmith/localseoskills --skill ai-local-search -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install garrettjsmith/localseoskills ai-local-search --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/garrettjsmith/localseoskills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-local-search .opencode/skills/ai-local-search && 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 "ai-local-search" agent skill from https://github.com/garrettjsmith/localseoskills/tree/main/skills/ai-local-search into .opencode/skills/ai-local-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-local-search", 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.
Facts
- Skill name
ai-local-search- GitHub stars
- 121
- Token cost
- ~2.4k tokens
- SKILL.md length
- 1,244 words
- Files
- 1
- Skills in repo
- 38
- Repo updated
- First seen
- Licence
- MIT
At a glance
When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok.
- Works in 5 steps: Structured Data Excellence → Review Profile Optimization → Content for AI Consumption → …
- Wants to optimize for AI-powered local search results including Google AI Overviews
- SKILL.md covers The Landscape (as of early 2026), How AI Models Find Local…, Optimization Strategy and Platform-Specific Notes, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
AI Local Search is an agent skill from garrettjsmith/localseoskills. When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok. Also use when the user mentions "AI Overviews," "AI search local," "ChatGPT local," "GEO," "LLMO," "generative search," "AI recommendations," "AI Mode," or "showing up in AI answers for local." For traditional map pack ranking, see gbp-optimization.
Its SKILL.md is about 2.4k 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 Local SEO and AI search optimization. It works with OpenAI and Perplexity. The repository describes itself as: Open-source Claude SEO tool for local search visibility — skills, tool integrations, and automation templates that turn Claude into a Local SEO expert. The licence is MIT.
When your agent uses it
- Wants to optimize for AI-powered local search results including Google AI Overviews
- The user mentions AI Overviews
- AI search local
- Generative search
Example prompts
- “AI Overviews,”
- “AI search local,”
- “ChatGPT local,”
- “/ai-local-search”
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 405ce20. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Local Search loads about 2.4k tokens when it runs. Until then it costs about 103 tokens; SKILL.md has 1,244 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from garrettjsmith/localseoskills at commit 405ce20, republished under its MIT licence (© garrettjsmith). 1,244 words, ~2,430 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-local-search/SKILL.md (or your agent's skills folder).- name
- ai-local-search
- description
- When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok. Also use when the user mentions "AI Overviews," "AI search local," "ChatGPT local," "GEO," "LLMO," "generative search," "AI recommendations," "AI Mode," or "showing up in AI answers for local." For traditional map pack ranking, see gbp-optimization.
- metadata.version
- 1.0.0
- metadata.author
- Garrett Smith
AI Local Search Optimization
You are an expert in how AI-powered search platforms surface local business results. Your goal is to help businesses appear in AI-generated local recommendations across Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, and other LLM-powered search experiences.
The Landscape (as of early 2026)
AI is reshaping how consumers find local businesses. Key platforms:
- Google AI Overviews: AI summaries at the top of search results, increasingly for local queries
- Google AI Mode: Conversational search experience with local recommendations
- ChatGPT + SearchGPT: Growing share of "find me a..." local discovery queries
- Gemini: Google's AI assistant, integrated with Maps data
- Perplexity: AI search engine with cited local results
- Grok: X's AI, emerging for local discovery
- Apple Intelligence: Siri + Maps integration for local queries
What's Different from Traditional Local SEO
- AI models synthesize information from multiple sources, not just rank pages
- Reviews and sentiment matter more — AI reads and summarizes them
- Structured data becomes even more critical — it's how AI understands your business
- Brand mentions across the web influence AI "knowledge" about your business
- Traditional ranking position matters less; being a cited source matters more
AI Signals Are Now Part of the Core Ranking Model
AI search signals are now recognized as a distinct ranking factor category. This isn't a fringe concern — AI Overviews now appear for over half of local search queries. AI search signals include entity clarity, web presence breadth, content structure, and brand authority across diverse sources.
Key data points:
- AI Overview prominence is rooted to industry, not city — if they appear for plumbing in Houston, they appear for plumbing in Denver
- ChatGPT traffic to local sites grew from ~0.1% to ~2% of Google traffic in one year. Growing fast, but still a fraction of total
- Top-3 local pack businesses have roughly a 26% likelihood of appearing in Gemini responses (based on restaurant-query analysis). That means ~74% don't — map pack ranking alone doesn't guarantee AI visibility
- Overall organic traffic is declining, but homepage traffic is up ~10% due to LLMs. Local businesses may need to rethink homepage content strategy
- Bing Places matters for AI — ChatGPT pulls from Bing's index. See
bing-placesfor optimization
How AI Models Find Local Businesses
Data Sources AI Uses
- Google Business Profile data (for Google AI Overviews/AI Mode/Gemini)
- Web content — website pages, especially well-structured service/location pages
- Reviews — aggregated sentiment, specific mentions of services, quality signals
- Citations and directories — NAP data, category associations
- Brand mentions — unstructured mentions across blogs, news, forums
- Structured data (schema) — machine-readable business information
- Third-party reviews — Yelp, industry platforms, social media
What Triggers AI Local Results
- "Best [service] in [city]" queries
- "Find me a [service] near [area]"
- Conversational: "I need a plumber, my pipe burst"
- Comparison: "Who's better, X or Y for [service]?"
- Recommendation: "What [business type] do you recommend in [city]?"
Optimization Strategy
1. Structured Data Excellence
AI models heavily rely on structured data to understand businesses.
- Complete LocalBusiness schema with every field populated
- Service schema for each service offered
- FAQ schema for common questions
- Review schema (aggregateRating)
areaServedfor geographic coveragehasOfferCatalogfor service details
2. Review Profile Optimization
AI reads and synthesizes reviews to form recommendations.
- Volume: more reviews = more data for AI to work with
- Diversity: reviews mentioning different services and areas
- Recency: recent reviews weighted more heavily
- Sentiment: consistently positive sentiment across platforms
- Specificity: reviews that name services, describe experiences, mention outcomes
- Multi-platform: Google, Yelp, industry-specific — AI aggregates across sources
3. Content for AI Consumption
Write content that AI can easily parse and cite.
- Clear, factual statements about your services and capabilities
- Lists of services with descriptions (not just names)
- Explicit geographic coverage statements
- Pricing information where possible (AI loves specifics)
- Credentials, certifications, years of experience — stated clearly
- FAQ pages with direct question-and-answer format
- Avoid fluffy marketing copy — AI extracts facts, not sizzle
4. Brand Mentions and Authority
AI forms opinions about businesses from web-wide signals.
- Get mentioned on local blogs, news sites, and industry publications
- Maintain consistent business information across all platforms
- Participate in local business roundups and "best of" lists
- Earn citations on authoritative industry directories
- PR and media coverage mentioning your business by name
5. GBP Completeness (for Google AI)
Google's AI products pull heavily from GBP data.
- Every GBP field filled completely
- Services section with detailed descriptions
- Products with accurate information
- Regular posts signaling active business
- Q&A populated with real questions and answers
Platform-Specific Notes
Show full SKILL.md (514 more words)Show less
Google AI Overviews & AI Mode
- Pulls from GBP data, website content, and reviews
- Map pack may still appear alongside or within AI results
- GBP optimization remains foundational
- Geogrid tools (like Local Falcon) are adding AI scan capabilities
ChatGPT / SearchGPT
- Uses web search results and its training data
- Cites sources — being the cited page matters
- Well-structured pages with clear facts get cited
- Review aggregation across platforms influences recommendations
- Less dependent on GBP, more on web content and authority
Gemini
- Deep Google ecosystem integration (GBP, Maps, Search)
- Conversational local queries are a primary use case
- GBP data is the primary data source
- Similar optimization to Google AI Overviews
Measuring AI Search Visibility
Available Tools
- Local Falcon: AI scan type for Google AI Overviews (GAIO) and AI Mode
- SAIV metric: Share of AI Voice — percentage of AI results mentioning your business
- Manual testing: Search target queries in ChatGPT, Gemini, Perplexity
- Search Console: Monitor for AI Overview impressions/clicks (limited data)
What to Track
- Mentioned in AI results for target keywords? (yes/no per platform)
- Sentiment of AI-generated mentions
- Which sources AI cites when recommending your business
- Competitor mentions in the same AI results
- Changes over time as you optimize
What's Still Emerging
Be honest with clients: AI local search is evolving rapidly.
- Ranking factors for AI results are less established than traditional local SEO
- AI platforms update their data sources and algorithms frequently
- Measurement tools are immature compared to traditional rank tracking
- ROI attribution from AI search is difficult
- Today's best practices may shift as platforms evolve
The safest strategy: optimize for traditional local SEO fundamentals (GBP, reviews, citations, content, links) AND layer on AI-specific tactics (structured data, clear factual content, multi-platform presence). What works for traditional local SEO mostly helps AI visibility too.
Task-Specific Questions
- Which AI platforms are priority? (Google AI, ChatGPT, all?)
- What are the target queries customers use?
- Current traditional local SEO state? (GBP, reviews, citations)
- Any existing AI scan data (Local Falcon GAIO scans)?
- Competitive landscape — are competitors showing up in AI results?
What to Do Next
| What You Found | Next Action | Skill |
|---|---|---|
| Business doesn't appear in AI Overviews | Start with GBP optimization — AI pulls from GBP data | gbp-optimization |
| Need structured data AI can parse | Implement comprehensive schema markup | local-schema |
| Need content AI platforms can cite | Create authoritative, well-structured service and location pages | local-landing-pages |
| Need to track AI visibility over time | Run AI platform scans (GAIO, ChatGPT, Gemini) via geogrid tools | geogrid-analysis |
| Reviews feeding negative AI sentiment | Improve review profile — AI synthesizes review data | review-management |
| Want to compare AI vs. traditional visibility | Run competitor analysis across both traditional and AI search | local-competitor-analysis |
Default next step: AI local search is evolving rapidly. The foundation is the same as traditional local SEO — strong GBP, strong website, strong reviews. Optimize those first, then monitor AI-specific visibility.
Tools for This Skill
See docs/tool-routing to pick based on what's connected.
- AI search visibility scans (GAIO, ChatGPT, Gemini, Grok platforms) → Local Falcon (only option for geographic AI coverage)
- AI Overview detection (check if Google shows AI Overview for a query) → live SERP tools (multiple options)
© garrettjsmith, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/ai-local-search of garrettjsmith/localseoskills.
Open the folder on GitHubat commit 405ce20
Compare with similar skills
AI Local Search 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 |
|---|---|---|---|---|---|---|
| AI Local Search this skillgarrettjsmith/localseoskills | 121 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Global SEO Growthminhnv0807/ai-business-skills | 609 | — | ~5k | Automated safety check: Pass | MIT | |
| SEONexus-JPF/note-companion | 870 | — | ~2.2k | Automated safety check: Pass | MIT | |
| 32 SEO Growthminhnv0807/ai-business-skills | 609 | — | ~5k | 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 |
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Related
Works with
Categories
Questions about AI Local Search
What does AI Local Search do?
When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok. AI Local Search is an agent skill from garrettjsmith/localseoskills. When the user wants to optimize for AI-powered local search results including Google AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity, or Grok.
When should I use AI Local Search?
AI Local Search fits situations like: wants to optimize for AI-powered local search results including Google AI Overviews; the user mentions AI Overviews; AI search local; generative search.
How do I install AI Local Search in Claude Code?
Run `npx skills add garrettjsmith/localseoskills --skill ai-local-search -a claude-code`. Or copy the skill folder (skills/ai-local-search in garrettjsmith/localseoskills) into .claude/skills/ai-local-search in your project. Claude Code loads it when a task matches its description.
How do I install AI Local Search in Codex?
Run `npx skills add garrettjsmith/localseoskills --skill ai-local-search -a codex`. Or copy the skill folder (skills/ai-local-search in garrettjsmith/localseoskills) into .agents/skills/ai-local-search in your project. Codex loads it when a task matches its description.
Can I use AI Local Search in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add garrettjsmith/localseoskills --skill ai-local-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-local-search, .gemini/skills/ai-local-search, .github/skills/ai-local-search and .opencode/skills/ai-local-search in your project.
What does AI Local Search need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Local Search is instructions for the agent only.
Does AI Local Search access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Local Search safe to install?
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.
What licence does AI Local Search use?
AI Local Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Local Search use?
About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to AI Local Search?
Skills that share tags, products or a category with AI Local Search: Global SEO Growth (minhnv0807/ai-business-skills, 609 stars), SEO (Nexus-JPF/note-companion, 870 stars), 32 SEO Growth (minhnv0807/ai-business-skills, 609 stars) and Geo Fundamentals (wasp-lang/wasp, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Local Search?
garrettjsmith (a GitHub user) maintains it in garrettjsmith/localseoskills, which has 121 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on August 15, 2026.
Source: garrettjsmith/localseoskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.