#703 by GitHub stars

onvoyage-ai/gtm-engineer-skills

Claude Code skill for improving website AEO (AI Engine Optimization) and GEO (Generative Engine Optimization) scores — 16 foundational checks, 6 intelligence dimensions, framework-specific fixes

Marketing Data

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View on GitHub Add to my skills

Verified commit cfdb9edd84109077153fa7faf776eb35f6c04370

1.4kGitHub stars

13stars in 7 days

12skills in this repository

1commit in 30 days

Heat

5.7

Star growth, last 7 daysAhead of 83% of tracked repositories
Star growth, last 24 hoursAhead of 73% of tracked repositories
Rank movement, last 7 daysAhead of 29% of tracked repositories
Commits, last 30 daysAhead of 54% of tracked repositories
Accounts asking about it through MCP, last 7 daysNot available
Hot votes this weekAhead of 0% of tracked repositories

Heat never changes the order by stars, and sponsorship never touches it. How heat works

Stars over time

Individual skills in this repository

audit-content audit-content
audit-website-aeo audit-website-aeo
build-backlinks build-backlinks
build-resource-pages build-resource-pages
create-geo-charts create-geo-charts
geo-content-planning geo-content-planning
geo-content-research geo-content-research
improve-aeo-geo improve-aeo-geo
reddit-opportunity-research reddit-opportunity-research
research-brand research-brand
research-keywords research-keywords
write-seo-geo-content write-seo-geo-content

How it works

Choose a skill

audit-content

When your agent uses it

Verifies truthfulness, accuracy, and link integrity of content before publishing. Catches fabricated statistics, dead URLs, misattributed sources, and company claims that contradict the brand DNA.

What it loads into context

Frontmatter

44 tokens

Always available to the agent

SKILL.md

1,826 tokens

When the skill is activated

Reference documents

0 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

When To Use This Skill
Workflow
Output Format
Rules
What This Skill Does NOT Do

Files

SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes
SKILL.mdcore7,646 bytes

Read SKILL.md


# Audit Content

You are a content auditor. Your job is to verify the truthfulness, accuracy, and link integrity of content before it gets published. You catch fabricated statistics, dead URLs, misattributed sources, and company claims that don't match the brand DNA.

## When To Use This Skill

Use after writing content and before publishing. Run it on:
- Individual articles
- Batches of articles in a content folder
- Any content that cites external sources, statistics, or company claims

## Workflow

### Step 1: Load context

View the complete source on GitHub

audit-website-aeo

When your agent uses it

Audits a live website for AI-engine discoverability (AEO/GEO). Crawls the site, runs 16 deterministic checks plus a 6-dimension content evaluation, and produces a scored report (A-F) with prioritized fixes. Use to get a baseline before improve-aeo-geo, or to measure progress after changes.

What it loads into context

Frontmatter

77 tokens

Always available to the agent

SKILL.md

3,097 tokens

When the skill is activated

Reference documents

2,107 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Workflow
The 16 deterministic checks
Report Format
Rules
Research References

Scripts executed separately

scripts/aeo-audit.mjs

Files

README.mddoc3,857 bytes
SKILL.mdcore11,702 bytes
SKILL.mdcore11,702 bytes
examples/anthropic-com-audit.mddoc4,322 bytes
scripts/aeo-audit.mjsruns45,498 bytes

Read SKILL.md


# Audit Website AEO/GEO Skill

You audit a **live website** the way an AI agent would — crawling its pages, parsing structure, and judging whether the content is citation-worthy for ChatGPT, Claude, Perplexity, and Google AI Overviews.

The audit has two halves:

- **Foundational (50%)** — 16 deterministic pass/fail checks run by a script. Reproducible, no judgment.
- **Intelligence (50%)** — 6 content-quality dimensions **you** score by reading the pages, using the rubric below.

Final score = `0.5 × foundational + 0.5 × intelligence`, mapped to an A-F grade.

This skill produces a **diagnosis**. To then fix a codebase, hand off to the **`improve-aeo-geo`** skill.

---

View the complete source on GitHub

build-backlinks

When your agent uses it

Finds free backlink and brand mention opportunities across Hacker News, Quora, GitHub, directories, and niche communities. Outputs a prioritized action plan with draft responses ready to post. Use after brand research and content creation to amplify reach and AI engine citations.

What it loads into context

Frontmatter

60 tokens

Always available to the agent

SKILL.md

2,244 tokens

When the skill is activated

Reference documents

216 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Why this matters for GEO
Inputs
Process
Output Format
Rules

Files

README.mddoc891 bytes
SKILL.mdcore9,317 bytes

Read SKILL.md


You are a brand presence strategist who finds free, high-impact opportunities to get a brand mentioned and linked across the web. Your goal is to produce a **ready-to-execute action plan** — not theory, not a strategy deck. Every item in your output should be something the user can do today.

## Why this matters for GEO

AI engines (ChatGPT, Claude, Perplexity, Gemini) cite brands that appear across diverse, authoritative sources. A single mention on a high-traffic Reddit thread or Hacker News post can trigger AI citation. Unlike traditional SEO backlinking (mass email outreach, PBNs), GEO backlinks are about **showing up where AI trains and retrieves from**.

High-value sources for AI citation:
- Hacker News (heavily indexed by AI engines)
- Quora (frequently cited in AI answers)
- Wikipedia (highest authority, strictest rules)
- GitHub (discussions, awesome-lists, READMEs)
- Stack Overflow / Stack Exchange (technical authority)
- Industry-specific forums and communities
- Free directories (G2, Capterra, Product Hunt, niche directories)

View the complete source on GitHub

build-resource-pages

When your agent uses it

Takes existing content markdown files and builds production-final resource center pages on client websites using their existing tech stack and design system. Output is live-ready — no review pass, no placeholder content, no prototype styling. Implements hub pages, section listings, article pages, and cross-linking for Blog, Guides, Learn, and Comparisons sections.

What it loads into context

Frontmatter

75 tokens

Always available to the agent

SKILL.md

3,061 tokens

When the skill is activated

Reference documents

388 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Workflow
Production Quality Standards
Design Principles
Technical Checklist
Rules

Files

README.mddoc1,837 bytes
SKILL.mdcore14,297 bytes

Read SKILL.md


# Build Resource Pages

You are a senior frontend engineer building resource centers for professional websites. You take existing content (markdown files produced by the content writing skills) and implement **production-final** resource pages — listing pages, article pages, navigation, and cross-linking — using the client's existing tech stack and design system.

**Your output ships directly to production.** Every page must be indistinguishable from the rest of the site. No rough edges. No placeholder text. No prototype styling. No "we'll polish this later." The pages you build are the pages visitors see.

Your output is code, not content. The content already exists.

---

## Workflow

### Phase 1: Discover the Stack

View the complete source on GitHub

create-geo-charts

When your agent uses it

Creates data visualizations (charts, graphs, tables) optimized for AI engine parsing and citation. Produces inline SVG/HTML with text summaries, data tables, and JSON-LD so AI engines can quote the data.

What it loads into context

Frontmatter

54 tokens

Always available to the agent

SKILL.md

4,266 tokens

When the skill is activated

Reference documents

539 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Workflow
Step 9: Visual QA — Render and Verify Before Delivery
Integration with Other Skills
Complete Output Template
Quality Checklist

Files

README.mddoc2,218 bytes
SKILL.mdcore17,409 bytes
SKILL.mdcore17,409 bytes
SKILL.mdcore17,409 bytes
examples/ai-referral-traffic-share-v2.htmlasset7,167 bytes
examples/ai-referral-traffic-share.csvasset268 bytes
examples/ai-referral-traffic-share.htmlasset8,692 bytes
examples/ai-toy-brand-comparison.htmlasset10,833 bytes
examples/ai-toy-market-growth.htmlasset7,347 bytes
examples/ai-toy-parent-concerns.htmlasset7,055 bytes
examples/content-freshness-citations-preview.pngasset389,511 bytes
examples/content-freshness-citations-v2.htmlasset7,522 bytes
examples/content-freshness-citations.csvasset151 bytes
examples/content-freshness-citations.htmlasset10,047 bytes
examples/geo-strategy-impact-v2.htmlasset8,268 bytes
examples/geo-strategy-impact.csvasset291 bytes
examples/geo-strategy-impact.htmlasset10,455 bytes
examples/scooter-brand-market-share.htmlasset7,542 bytes
examples/scooter-market-growth.htmlasset8,801 bytes
examples/scooter-specs-comparison.htmlasset10,846 bytes

Read SKILL.md


# Create GEO/SEO Charts & Data Visualizations

You are an expert at creating data visualizations optimized for Generative Engine Optimization (GEO) and SEO. When invoked, you produce charts, graphs, and data tables that AI engines can parse, quote, and cite — and that rank in Google Images and AI Overviews.

Core insight: AI engines cite text, not pixels. Every chart you create must have a complete text representation alongside it. The chart is for humans; the text summary, HTML table, and structured data are for AI.

## Workflow

### Step 1: Understand the Data

Ask the user for:
1. **Data source** — raw data, research findings, or a synthesis request
2. **Chart purpose** — what point should the chart make?
3. **Target audience** — who sees this and where does it live (blog post, landing page, data page)?

View the complete source on GitHub

geo-content-planning

When your agent uses it

Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.

What it loads into context

Frontmatter

56 tokens

Always available to the agent

SKILL.md

1,965 tokens

When the skill is activated

Reference documents

1,125 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Workflow
Strict CSV Format

Files

SKILL.mdcore7,857 bytes
plan.csv.schema.mddoc4,253 bytes

Read SKILL.md


# GEO Content Planning — Produce plan.csv

You are a GEO content planner. Your job is to read the brand context and the prior research artifacts that already exist, then emit a strictly-formatted CSV that the next pipeline step can consume to build content.

This skill is planning only. Do not generate articles. Do not do new research — cluster what already exists.

> **Output contract:** Your final response text IS the deliverable. It MUST be raw CSV matching `plan.csv.schema.md` exactly. No prose, no code fences, no explanation. The harness captures your final output, validates it, cross-references it against `keywords.csv` and `prompts.csv`, and fails the artifact if any referenced keyword or prompt does not exist in those files.

> **Required inputs:** The harness injects these into your context automatically:
> - `brand_dna.md` — brand positioning, voice, audience
> - `keywords.csv` — SEO keyword targets (columns: keyword, volume, kd, intent, priority, cluster, is_pillar, ai_overview_present, source, notes)
> - `prompts.csv` — GEO prompt targets (columns: prompt, tier, citability, competition, priority, query_type, cluster, target_engines, brand_mention_mechanism, notes)
>
> You MUST reference real entries from these files. Do not invent keywords or prompts.

View the complete source on GitHub

geo-content-research

When your agent uses it

Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.

What it loads into context

Frontmatter

63 tokens

Always available to the agent

SKILL.md

6,662 tokens

When the skill is activated

Reference documents

2,061 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

How This Skill Works
Phase 1: Product Intelligence Gathering
Phase 2: AI Prompt Research
Phase 3: Emit prompts.csv (STRICT FORMAT)
Phase 4: Content Blueprint
Phase 5: Content Generation
Phase 6: Authority Infiltration Plan
Verification: Test Your GEO Standing
Quick Reference: What AI Engines Weight Most

Files

README.mddoc4,836 bytes
SKILL.mdcore27,448 bytes
SKILL.mdcore27,448 bytes
SKILL.mdcore27,448 bytes
SKILL.mdcore27,448 bytes
SKILL.mdcore27,448 bytes
SKILL.mdcore27,448 bytes
prompts.csv.schema.mddoc3,528 bytes

Read SKILL.md


# GEO Content Research — Produce prompts.csv

You are a Generative Engine Optimization (GEO) strategist. Your job is to surface the exact queries people ask AI chatbots about this category, and emit them as a strictly-formatted CSV that downstream pipeline steps can consume.

The core insight: AI engines have no paid ranking. You can't buy a ChatGPT recommendation. They only evaluate content quality, data structure, and source authority. Finding the queries where the brand *should* be mentioned is the first step — this skill's deliverable.

> **Output contract:** Your final response text IS the deliverable. It MUST be raw CSV matching `prompts.csv.schema.md` exactly. No prose, no code fences, no explanation around the CSV. The harness captures your final output verbatim, validates it against the schema, and fails the artifact if the shape is wrong. See Phase 3 for the exact format.

> **Scope in autonomous mode:** Phases 1–3 only. The legacy Phases 4–6 (Content Blueprint, Content Generation, Authority Infiltration) belong to separate skills (`geo-content-planning`, `write-seo-geo-content`) and are not this skill's job anymore. Do the research, emit the CSV, stop.

---

## How This Skill Works

View the complete source on GitHub

improve-aeo-geo

When your agent uses it

Audits a website codebase and makes code changes so AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) can better discover, parse, quote, and cite the site. Covers structured data, content structure, technical signals, and freshness.

What it loads into context

Frontmatter

64 tokens

Always available to the agent

SKILL.md

5,565 tokens

When the skill is activated

Reference documents

2,869 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Workflow
Scoring Model
Priority 1: Blockers (fix these first)
Priority 2: High-Impact Structure
Priority 3: Content Quality
Priority 4: GEO Content Optimization
Framework-Specific Patterns
Verification Checklist
Research References

Files

README.mddoc5,154 bytes
SKILL.mdcore20,799 bytes
SKILL.mdcore20,799 bytes
SKILL.mdcore20,799 bytes
examples/nextjs-blog-before-after.mddoc3,388 bytes
examples/wordpress-business-before-after.mddoc1,768 bytes

Read SKILL.md


# Improve Website AEO/GEO Skill

You are an expert at AI Engine Optimization (AEO) and Generative Engine Optimization (GEO). When invoked, you analyze the user's website codebase and make concrete, actionable code changes so AI agents — ChatGPT, Claude, Perplexity, Google AI Overviews, and others — can better discover, parse, quote, and cite the site.

The web is shifting from human-first to AI-first discovery. AI agents don't browse like humans. They extract structured data, scan for direct answers, and decide in milliseconds whether content is worth citing. This skill makes websites visible to that new audience.

## Workflow

When invoked on a codebase, follow this exact sequence:

### Step 1: Baseline
- If the user has a live URL, get a baseline score first. Run the **`audit-website-aeo`** skill for a local crawl + scored report, or use the hosted [aeo-audit.sh](https://aeo-audit.sh). If an `aeo_audit_report.md` already exists, read it — its prioritized fixes and weakest pages tell you exactly what to fix.
- If no URL is available, proceed with a code-level audit.

View the complete source on GitHub

reddit-opportunity-research

When your agent uses it

Researches Reddit using a brand's Brand DNA to find promotable pain-point discussions, target subreddits, and real user search language. Produces a prioritized Reddit opportunity list for content seeding, helpful replies, and prompt research inspiration.

What it loads into context

Frontmatter

58 tokens

Always available to the agent

SKILL.md

1,918 tokens

When the skill is activated

Reference documents

241 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Inputs
Goal
Research Rules
Process
Output
What Good Output Looks Like
Final Guidance to the User

Files

README.mddoc1,080 bytes
SKILL.mdcore8,518 bytes

Read SKILL.md


# Reddit Opportunity Research

You are a Reddit growth researcher. Your job is to find where a brand can participate helpfully on Reddit, what pain points users are actively discussing, and what search language should feed content strategy and GEO prompt research.

This skill is for **promotion through useful participation**, not spam. Every recommendation should answer a real user need, fit the subreddit culture, and point to content only when it genuinely helps.

## Inputs

- `brand_dna.md` (required) — from `research-brand`
- `keyword_research.md` (optional) — to expand search terms
- `geo_prompt_targets.md` (optional) — to connect Reddit questions to GEO opportunities
- Existing content URLs or drafts (optional) — to map threads to content assets worth sharing

If `brand_dna.md` does not exist, tell the user to run `research-brand` first.

View the complete source on GitHub

research-brand

When your agent uses it

Researches a company from its URL and produces a Brand DNA file covering positioning, audience, competitors, voice, and messaging. Use when starting work with a new brand or customer.

What it loads into context

Frontmatter

43 tokens

Always available to the agent

SKILL.md

1,304 tokens

When the skill is activated

Reference documents

352 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Process
Rules

Files

README.mddoc1,368 bytes
SKILL.mdcore5,397 bytes

Read SKILL.md


# Research Brand DNA

You are a brand intelligence researcher. Given a company URL, you produce a complete Brand DNA file — everything a marketer, content strategist, or GTM team needs to start working with this brand.

**Input:** A URL (and optionally a one-liner about the company).
**Output:** A `brand_dna.md` file saved to the user's project directory.

---

## Process

### 1. Crawl the website

Fetch and read these pages (skip any that 404):

View the complete source on GitHub

research-keywords

When your agent uses it

Finds high-value SEO and GEO keywords using web search, AI analysis, and optionally paid tools like Ahrefs or Semrush. Produces a validated keywords.csv file with a fixed schema for downstream pipeline consumption.

What it loads into context

Frontmatter

49 tokens

Always available to the agent

SKILL.md

3,846 tokens

When the skill is activated

Reference documents

2,567 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

How This Skill Works
Phase 1: Brand Intelligence
Phase 2: Keyword Discovery
Phase 3: Validation & Pruning
Phase 4: Analysis & Clustering
Phase 5: Deliverable — keywords.csv (STRICT FORMAT)
Rules

Scripts executed separately

scripts/keyword-explorer.mjs
scripts/serp-analyzer.mjs

Files

README.mddoc7,397 bytes
SKILL.mdcore15,996 bytes
keywords.csv.schema.mddoc2,773 bytes
scripts/keyword-explorer.mjsruns18,231 bytes
scripts/serp-analyzer.mjsruns13,785 bytes

Read SKILL.md


# Research SEO/GEO Keywords

You are an expert keyword researcher who finds high-value keywords for both traditional SEO and Generative Engine Optimization (GEO). You use web search and AI analysis — and optionally integrate paid tool data (Ahrefs, Semrush) when the user has it.

Your job: take a brand's product, website, and competitive context, then research and deliver a prioritized keyword list as a **strict CSV artifact** ready for the content pipeline.

> **Output contract:** Your final response text IS the deliverable. It MUST be raw CSV matching `keywords.csv.schema.md` exactly. No prose, no code fences, no explanation around the CSV. The harness captures your final output verbatim, validates it against the schema, and fails the artifact if the shape is wrong. See Phase 5 for the exact format.

**Critical rule: SEO target keywords must be 1-3 words.** Longer phrases (4+ words) go in the Blog Topics section. Keywords longer than 3 words almost never have search volume in tools like Ahrefs — they waste space on the list and won't rank.

---

## How This Skill Works

View the complete source on GitHub

write-seo-geo-content

When your agent uses it

Writes product-led content pages optimized for both search engines and AI engine citations. Produces markdown files with frontmatter, following page-type frameworks (comparison, guide, use case, learn, trust) with verified sources and no fabricated data.

What it loads into context

Frontmatter

58 tokens

Always available to the agent

SKILL.md

4,279 tokens

When the skill is activated

Reference documents

702 tokens

Loaded on request

Token counts are estimates. Scripts run separately; they are not counted as reference context.

The playbook

Modes
Pre-Writing Research Protocol
GEO Writing Requirements
Page-Type Frameworks
Core Content Blocks
SEO Standards
E-E-A-T Signals
Quality Standards
GEO Checklist
Verification Checklist
Output Format

Files

README.mddoc3,051 bytes
SKILL.mdcore18,403 bytes
SKILL.mdcore18,403 bytes
SKILL.mdcore18,403 bytes
SKILL.mdcore18,403 bytes

Read SKILL.md


# Write SEO + GEO Content

You are an expert SEO and GEO content writer specializing in product-led pages that rank in search engines and get cited by AI engines. When invoked, you operate in one of two modes. Never write without completing pre-writing research first — no fabricated stats, no unverified sources, no skipped research steps.

## Modes

### Planning Mode
Use when the user needs article topics or strategy defined before writing.

1. Gather: product/service details, target audience, value proposition
2. Research keywords if not provided (search volume, intent, competition)
3. Review the user's website to understand their offering and voice
4. If available, read the user's `content_architecture.md` or content plan first
5. Propose 3-5 content topics with: title angle, page type, primary keyword, target GEO prompt, search intent, and why it fits the product

View the complete source on GitHub

Skills included

audit-content
audit-website-aeo
build-backlinks
build-resource-pages
create-geo-charts
geo-content-planning
geo-content-research
improve-aeo-geo
reddit-opportunity-research
research-brand
research-keywords
write-seo-geo-content

Repository facts

License: MIT
Created: Feb 26, 2026
Last pushed: Oct 11, 2026
Forks: 58
Open issues: 14
Project activity: Active

Rank over the last 12 weeks

Now #703 · best #486 · down 98 in 30 days

#692 on Nov 2
#695 on Nov 3
#697 on Nov 4
#702 on Nov 5
#700 on Nov 6
#703 since Nov 7

57 earlier periods

#473 on Aug 2
#479 from Aug 8 to Aug 9
#500 on Aug 10
#498 on Aug 11
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Before you install

Network or broad shell

Automated signals, not a guarantee

Checked Nov 3, 2026

Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.

Show 20 notes

audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
audit-website-aeo/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
create-geo-charts/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
create-geo-charts/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
geo-content-research/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
geo-content-research/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
geo-content-research/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
geo-content-research/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
geo-content-research/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
improve-aeo-geo/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
improve-aeo-geo/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
write-seo-geo-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
write-seo-geo-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed
write-seo-geo-content/SKILL.md:1 Analysis incomplete: Referenced executable target unavailable; not analyzed

No broad tool permissions
No dangerous shell commands
211 network referencesin 25 files: improve-aeo-geo/SKILL.md:16 improve-aeo-geo/examples/nextjs-blog-before-after.md:42 create-geo-charts/examples/geo-strategy-impact.html:37 and 22 more
No hidden or obfuscated text
No instruction overrides
3 executable scriptsin 3 files: audit-website-aeo/scripts/aeo-audit.mjs:1 research-keywords/scripts/keyword-explorer.mjs:1 research-keywords/scripts/serp-analyzer.mjs:1
5 references to secretsin 3 files: research-keywords/scripts/keyword-explorer.mjs:35 research-keywords/scripts/serp-analyzer.mjs:28 research-keywords/README.md:176
No requests to vote in Hot

Show all 219 signals by file

`audit-content/SKILL.md`

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| Category | What to extract | Example | |---|---|---| | **External URL** | Any hyperlink to an external source | `[PCMA research](https://www.pcma.org/...)` |

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|---|---|---| | **External URL** | Any hyperlink to an external source | `[PCMA research](https://www.pcma.org/...)` | | **Statistic** | Any number, percentage, or data point attributed to a source | "52% of attendees say..." |

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| **External URL** | Any hyperlink to an external source | `[PCMA research](https://www.pcma.org/...)` |

`audit-website-aeo/README.md`

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Or: > "Audit my website for AEO" > "Check if AI engines can cite https://example.com"

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> "Audit my website for AEO" > "Check if AI engines can cite https://example.com" > "Run an AEO/GEO audit on [URL]"

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> "Check if AI engines can cite https://example.com"

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node scripts/aeo-audit.mjs https://example.com --max-pages=20 --out=aeo-audit.json

`audit-website-aeo/SKILL.md`

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| Claim | Source | |---|---| | Quotations = +41% visibility; Statistics = +33%; Cite Sources = +28%; in-text citations = +115% for lower-ranked sites | Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 ([arXiv](https://arxiv.

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|---|---| | Quotations = +41% visibility; Statistics = +33%; Cite Sources = +28%; in-text citations = +115% for lower-ranked sites | Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 ([arXiv](https://arxiv.org/abs/2311.09735)

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| Quotations = +41% visibility; Statistics = +33%; Cite Sources = +28%; in-text citations = +115% for lower-ranked sites | Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 ([arXiv](https://arxiv.org/abs/2311.09735)) |

`audit-website-aeo/examples/anthropic-com-audit.md`

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| Score | URL | |---|---| | 73% | https://www.anthropic.com/ |

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|---|---| | 73% | https://www.anthropic.com/ | | 80% | https://www.anthropic.com/about-anthropic-interviewer |

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```
| 73% | https://www.anthropic.com/ |
```

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| 80% | https://www.anthropic.com/about-anthropic-interviewer |

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| 86% | https://www.anthropic.com/candidate-ai-guidance |

`audit-website-aeo/scripts/aeo-audit.mjs`

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```
#!/usr/bin/env node
```

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*   node aeo-audit.mjs <url> [--max-pages=10] [--out=aeo-audit-report.json] [--json]  *  *   node aeo-audit.mjs https://example.com

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*  *   node aeo-audit.mjs https://example.com  *   node aeo-audit.mjs example.com --max-pages=20 --out=workspace/acme/aeo-audit.json

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*   node aeo-audit.mjs https://example.com

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*   node aeo-audit.mjs example.com --max-pages=20 --out=workspace/acme/aeo-audit.json  *   node aeo-audit.mjs https://example.com --json        # print JSON to stdout  *

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*   node aeo-audit.mjs https://example.com --json        # print JSON to stdout

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const FETCH_TIMEOUT_MS = 12_000; const CRAWL_CONCURRENCY = 5; const UA = "Mozilla/5.0 (compatible; AEOAuditBot/1.0; +https://github.com/onvoyage-ai/gtm-engineer-skills)";

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const UA = "Mozilla/5.0 (compatible; AEOAuditBot/1.0; +https://github.com/onvoyage-ai/gtm-engineer-skills)";

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function normalizeUrl(raw) {   const withProtocol = /^https?:\/\//i.test(raw) ? raw : `https://${raw}`;

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const withProtocol = /^https?:\/\//i.test(raw) ? raw : `https://${raw}`;

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const timeout = setTimeout(() => controller.abort(), FETCH_TIMEOUT_MS);     try {       const res = await fetch(url, {

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try {       const res = await fetch(url, {         headers: { "User-Agent": UA },

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```
const res = await fetch(url, {
```

`create-geo-charts/SKILL.md`

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```
{   "@context": "https://schema.org",
```
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```
"@context": "https://schema.org",
```

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},   "datePublished": "[ISO date]",   "license": "https://creativecommons.org/licenses/by/4.0/",

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"datePublished": "[ISO date]",   "license": "https://creativecommons.org/licenses/by/4.0/",   "image": {

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"license": "https://creativecommons.org/licenses/by/4.0/",

`create-geo-charts/examples/ai-referral-traffic-share-v2.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 260" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 260" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<div class="source-line">     Source: Conductor, "AEO/GEO Benchmarks Report," November 2025 (<a href="https://www.conductor.com/academy/aeo-geo-benchmarks-report/">conductor.com</a>). 13,700 domains, 3.3B sessions. AI referral traffic categ

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Source: Conductor, "AEO/GEO Benchmarks Report," November 2025 (<a href="https://www.conductor.com/academy/aeo-geo-benchmarks-report/">conductor.com</a>). 13,700 domains, 3.3B sessions. AI referral traffic categorized by source domain.

`create-geo-charts/examples/ai-referral-traffic-share.html`

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<script type="application/ld+json">   {     "@context": "https://schema.org",

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{     "@context": "https://schema.org",     "@type": "Dataset",

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```
"@context": "https://schema.org",
```

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{ "@type": "PropertyValue", "name": "Referral Traffic Share", "unitText": "%" }     ],     "creator": { "@type": "Organization", "name": "Voyage", "url": "https://onvoyage.ai" },

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],     "creator": { "@type": "Organization", "name": "Voyage", "url": "https://onvoyage.ai" },     "datePublished": "2026-03-05",

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"creator": { "@type": "Organization", "name": "Voyage", "url": "https://onvoyage.ai" },

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"datePublished": "2026-03-05",     "license": "https://creativecommons.org/licenses/by/4.0/",     "isBasedOn": "https://www.conductor.com/academy/aeo-geo-benchmarks-report/",

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"license": "https://creativecommons.org/licenses/by/4.0/",

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"isBasedOn": "https://www.conductor.com/academy/aeo-geo-benchmarks-report/",

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<!-- 3. CHART — Donut chart -->   <figure>     <svg role="img" aria-labelledby="chart2-title chart2-desc" viewBox="0 0 720 400" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<figure>     <svg role="img" aria-labelledby="chart2-title chart2-desc" viewBox="0 0 720 400" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">       <title id="chart2-title">AI Engine Referral Traffic Share</title>

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<svg role="img" aria-labelledby="chart2-title chart2-desc" viewBox="0 0 720 400" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<figcaption>       Source: Conductor, "AEO/GEO Benchmarks Report," November 2025 (<a href="https://www.conductor.com/academy/aeo-geo-benchmarks-report/">conductor.com</a>). 13,700 domains, 3.3 billion sessions analyzed. Methodology: AI refe

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Source: Conductor, "AEO/GEO Benchmarks Report," November 2025 (<a href="https://www.conductor.com/academy/aeo-geo-benchmarks-report/">conductor.com</a>). 13,700 domains, 3.3 billion sessions analyzed. Methodology: AI referral traffic catego

`create-geo-charts/examples/ai-toy-brand-comparison.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 320" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 320" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

`create-geo-charts/examples/ai-toy-market-growth.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 340" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 340" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

`create-geo-charts/examples/ai-toy-parent-concerns.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 280" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 280" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

`create-geo-charts/examples/content-freshness-citations-v2.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 360" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 360" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<div class="source-line">     Source: SE Ranking, November 2025 (<a href="https://seranking.com/blog/how-to-optimize-for-ai-mode/">seranking.com</a>). 2.3M pages, 295K domains. Supplemented by Ahrefs, 2025 (<a href="https://ahrefs.com/blog/

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Source: SE Ranking, November 2025 (<a href="https://seranking.com/blog/how-to-optimize-for-ai-mode/">seranking.com</a>). 2.3M pages, 295K domains. Supplemented by Ahrefs, 2025 (<a href="https://ahrefs.com/blog/do-ai-assistants-prefer-to-cit

`create-geo-charts/examples/content-freshness-citations.html`

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<script type="application/ld+json">   {     "@context": "https://schema.org",

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{     "@context": "https://schema.org",     "@type": "Dataset",

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```
"@context": "https://schema.org",
```

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{ "@type": "PropertyValue", "name": "Content Age", "unitText": "months" }     ],     "creator": { "@type": "Organization", "name": "Voyage", "url": "https://onvoyage.ai" },

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],     "creator": { "@type": "Organization", "name": "Voyage", "url": "https://onvoyage.ai" },     "datePublished": "2026-03-05",

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"creator": { "@type": "Organization", "name": "Voyage", "url": "https://onvoyage.ai" },

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"datePublished": "2026-03-05",     "license": "https://creativecommons.org/licenses/by/4.0/",     "isBasedOn": "https://seranking.com/blog/how-to-optimize-for-ai-mode/",

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"license": "https://creativecommons.org/licenses/by/4.0/",

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"isBasedOn": "https://seranking.com/blog/how-to-optimize-for-ai-mode/",

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<!-- 3. CHART — Vertical bar chart -->   <figure>     <svg role="img" aria-labelledby="chart3-title chart3-desc" viewBox="0 0 720 400" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<figure>     <svg role="img" aria-labelledby="chart3-title chart3-desc" viewBox="0 0 720 400" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">       <title id="chart3-title">Content Freshness vs Average AI Citations</titl

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<svg role="img" aria-labelledby="chart3-title chart3-desc" viewBox="0 0 720 400" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<figcaption>       Source: SE Ranking, "How to Optimize for AI Mode," November 2025 (<a href="https://seranking.com/blog/how-to-optimize-for-ai-mode/">seranking.com</a>). 2.3M pages, 295K domains. Supplemented by Ahrefs, 2025 (<a href="http

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Source: SE Ranking, "How to Optimize for AI Mode," November 2025 (<a href="https://seranking.com/blog/how-to-optimize-for-ai-mode/">seranking.com</a>). 2.3M pages, 295K domains. Supplemented by Ahrefs, 2025 (<a href="https://ahrefs.com/blog

`create-geo-charts/examples/geo-strategy-impact-v2.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 340" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 340" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<div class="source-line">     Source: Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 (<a href="https://arxiv.org/abs/2311.09735">arXiv</a>). 10,000 queries across 9 generative engines. Each strategy applied independently t

Network accessline 155

Source: Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 (<a href="https://arxiv.org/abs/2311.09735">arXiv</a>). 10,000 queries across 9 generative engines. Each strategy applied independently to baseline content; visibility

`create-geo-charts/examples/geo-strategy-impact.html`

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<script type="application/ld+json">   {     "@context": "https://schema.org",

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{     "@context": "https://schema.org",     "@type": "Dataset",

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```
"@context": "https://schema.org",
```

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"@type": "Organization",       "name": "Voyage",       "url": "https://onvoyage.ai"

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"name": "Voyage",       "url": "https://onvoyage.ai"     },

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```
"url": "https://onvoyage.ai"
```

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},     "datePublished": "2026-03-05",     "license": "https://creativecommons.org/licenses/by/4.0/",

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"datePublished": "2026-03-05",     "license": "https://creativecommons.org/licenses/by/4.0/",     "isBasedOn": "https://arxiv.org/abs/2311.09735",

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"license": "https://creativecommons.org/licenses/by/4.0/",

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"isBasedOn": "https://arxiv.org/abs/2311.09735",

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<!-- 3. CHART -->   <figure>     <svg role="img" aria-labelledby="chart1-title chart1-desc" viewBox="0 0 720 380" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<figure>     <svg role="img" aria-labelledby="chart1-title chart1-desc" viewBox="0 0 720 380" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">       <title id="chart1-title">GEO Strategy Visibility Impact</title>

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<svg role="img" aria-labelledby="chart1-title chart1-desc" viewBox="0 0 720 380" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<!-- 4. SOURCE & METHODOLOGY -->     <figcaption>       Source: Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 (<a href="https://arxiv.org/abs/2311.09735">arXiv</a>). 10,000 queries tested across 9 generative engines. Meth

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<figcaption>       Source: Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 (<a href="https://arxiv.org/abs/2311.09735">arXiv</a>). 10,000 queries tested across 9 generative engines. Methodology: Each strategy applied indepe

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Source: Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 (<a href="https://arxiv.org/abs/2311.09735">arXiv</a>). 10,000 queries tested across 9 generative engines. Methodology: Each strategy applied independently to baseline

`create-geo-charts/examples/scooter-brand-market-share.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 300" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 300" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

`create-geo-charts/examples/scooter-market-growth.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 320" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 320" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

`create-geo-charts/examples/scooter-specs-comparison.html`

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<div class="chart-area">     <svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 380" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

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<svg role="img" aria-labelledby="chart-title chart-desc" viewBox="0 0 680 380" xmlns="http://www.w3.org/2000/svg" style="width:100%;height:auto;">

`geo-content-research/SKILL.md`

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```
{   "@context": "https://schema.org",
```
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```
"@context": "https://schema.org",
```
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```
{   "@context": "https://schema.org",
```
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```
"@context": "https://schema.org",
```
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```
{   "@context": "https://schema.org",
```
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```
"@context": "https://schema.org",
```
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```
{   "@context": "https://schema.org",
```
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```
"@context": "https://schema.org",
```

`improve-aeo-geo/README.md`

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[![AEO Audit](../assets/aeo-audit-screenshot.jpeg)](https://aeo-audit.sh/)

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**Check your score at [aeo-audit.sh](https://aeo-audit.sh/)** — then use this skill to improve it.

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2. Audit your code against 16 foundational checks and 6 content quality dimensions 3. Make targeted code changes in priority order 4. Recommend verifying your score at [aeo-audit.sh](https://aeo-audit.sh/)

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4. Recommend verifying your score at [aeo-audit.sh](https://aeo-audit.sh/)

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| Finding | Source | |---|---| | Adding quotations = **+41% AI visibility** | [GEO Paper, KDD 2024](https://arxiv.org/abs/2311.09735) — Princeton, Georgia Tech, IIT Delhi, Allen AI |

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|---|---| | Adding quotations = **+41% AI visibility** | [GEO Paper, KDD 2024](https://arxiv.org/abs/2311.09735) — Princeton, Georgia Tech, IIT Delhi, Allen AI | | Adding statistics = **+33% AI visibility** | Same peer-reviewed paper |

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| Adding quotations = **+41% AI visibility** | [GEO Paper, KDD 2024](https://arxiv.org/abs/2311.09735) — Princeton, Georgia Tech, IIT Delhi, Allen AI |

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| Adding statistics = **+33% AI visibility** | Same peer-reviewed paper | | Citing sources = **+28% AI visibility** | Same paper; up to **+115% for smaller sites** | | **44.2%** of ChatGPT citations come from first 30% of content | [Growth

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| Citing sources = **+28% AI visibility** | Same paper; up to **+115% for smaller sites** | | **44.2%** of ChatGPT citations come from first 30% of content | [Growth Memo, 2026](https://www.growth-memo.com/p/the-science-of-how-ai-pays-atten

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| **44.2%** of ChatGPT citations come from first 30% of content | [Growth Memo, 2026](https://www.growth-memo.com/p/the-science-of-how-ai-pays-attention) — 1.2M AI answers analyzed |

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| Articles 2,900+ words = **5.1 citations** vs. 3.2 for <800 words | [SE Ranking, 2025](https://seranking.com/blog/how-to-optimize-for-ai-mode/) — 2.3M pages studied |

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| Pages with FAQ sections = **4.9 citations** vs. 4.4 without | Same SE Ranking study | | Content updated within 3 months = **6 citations** vs. 3.9 for 2+ years | Same SE Ranking study | | AI cites content **25.7% fresher** than traditional

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| Content updated within 3 months = **6 citations** vs. 3.9 for 2+ years | Same SE Ranking study | | AI cites content **25.7% fresher** than traditional search | [Ahrefs, 2025](https://ahrefs.com/blog/do-ai-assistants-prefer-to-cite-fresh-c

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| AI cites content **25.7% fresher** than traditional search | [Ahrefs, 2025](https://ahrefs.com/blog/do-ai-assistants-prefer-to-cite-fresh-content/) — 17M citations |

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| ChatGPT drives **87.4%** of AI referral traffic | [Conductor, 2025](https://www.conductor.com/academy/aeo-geo-benchmarks-report/) — 13.7K domains |

`improve-aeo-geo/SKILL.md`

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### Step 1: Baseline - If the user has a live URL, get a baseline score first. Run the **`audit-website-aeo`** skill for a local crawl + scored report, or use the hosted [aeo-audit.sh](https://aeo-audit.sh). If an `aeo_audit_report.md` alre

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- If the user has a live URL, get a baseline score first. Run the **`audit-website-aeo`** skill for a local crawl + scored report, or use the hosted [aeo-audit.sh](https://aeo-audit.sh). If an `aeo_audit_report.md` already exists, read it —

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### Step 5: Verify - Re-run the audit (`audit-website-aeo` skill, or [aeo-audit.sh](https://aeo-audit.sh)) and compare against the Step 1 baseline to confirm the score improved

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- Re-run the audit (`audit-website-aeo` skill, or [aeo-audit.sh](https://aeo-audit.sh)) and compare against the Step 1 baseline to confirm the score improved

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Sitemap: https://YOURDOMAIN.com/sitemap.xml

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## Documentation - [Getting Started](https://yourdomain.com/docs/getting-started)

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- [Getting Started](https://yourdomain.com/docs/getting-started)

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- [API Reference](https://yourdomain.com/docs/api)

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## Key Pages - [About](https://yourdomain.com/about)

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```
- [About](https://yourdomain.com/about)
```

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- [Pricing](https://yourdomain.com/pricing)

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```
- [Blog](https://yourdomain.com/blog)
```

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## Policies - [Terms of Service](https://yourdomain.com/terms)

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- [Terms of Service](https://yourdomain.com/terms)

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- [Privacy Policy](https://yourdomain.com/privacy)

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title: 'Page Title | Brand',   description: 'Descriptive meta description of 120-160 characters.',   alternates: { canonical: 'https://yourdomain.com/page' },

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description: 'Descriptive meta description of 120-160 characters.',   alternates: { canonical: 'https://yourdomain.com/page' },   openGraph: {

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alternates: { canonical: 'https://yourdomain.com/page' },

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title: 'Page Title',     description: 'Social sharing description.',     url: 'https://yourdomain.com/page',

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description: 'Social sharing description.',     url: 'https://yourdomain.com/page',     images: [{ url: 'https://yourdomain.com/og-image.jpg' }],

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```
url: 'https://yourdomain.com/page',
```

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images: [{ url: 'https://yourdomain.com/og-image.jpg' }],

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export default function Page() {   const jsonLd = {     '@context': 'https://schema.org',

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const jsonLd = {     '@context': 'https://schema.org',     '@type': 'Article',

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```
'@context': 'https://schema.org',
```

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{ userAgent: 'CCBot', allow: '/' },     ],     sitemap: 'https://yourdomain.com/sitemap.xml',

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],     sitemap: 'https://yourdomain.com/sitemap.xml',   }

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sitemap: 'https://yourdomain.com/sitemap.xml',

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export default function sitemap(): MetadataRoute.Sitemap {   return [     { url: 'https://yourdomain.com', lastModified: new Date(), changeFrequency: 'weekly', priority: 1 },

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return [     { url: 'https://yourdomain.com', lastModified: new Date(), changeFrequency: 'weekly', priority: 1 },     { url: 'https://yourdomain.com/about', lastModified: new Date(), changeFrequency: 'monthly', priority: 0.8 },

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{ url: 'https://yourdomain.com', lastModified: new Date(), changeFrequency: 'weekly', priority: 1 },

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{ url: 'https://yourdomain.com/about', lastModified: new Date(), changeFrequency: 'monthly', priority: 0.8 },

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ogTitle: 'Page Title',   ogDescription: 'Social sharing description.',   ogImage: 'https://yourdomain.com/og-image.jpg',

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ogDescription: 'Social sharing description.',   ogImage: 'https://yourdomain.com/og-image.jpg', })

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ogImage: 'https://yourdomain.com/og-image.jpg',

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}) useHead({   link: [{ rel: 'canonical', href: 'https://yourdomain.com/page' }],

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useHead({   link: [{ rel: 'canonical', href: 'https://yourdomain.com/page' }], })

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link: [{ rel: 'canonical', href: 'https://yourdomain.com/page' }],

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<title>Page Title | Brand</title>   <meta name="description" content="Descriptive meta description." />   <link rel="canonical" href="https://yourdomain.com/page" />

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<meta name="description" content="Descriptive meta description." />   <link rel="canonical" href="https://yourdomain.com/page" />   <meta property="og:title" content="Page Title" />

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<link rel="canonical" href="https://yourdomain.com/page" />

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<svelte:head>   {@html `<script type="application/ld+json">${JSON.stringify({     "@context": "https://schema.org",

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{@html `<script type="application/ld+json">${JSON.stringify({     "@context": "https://schema.org",     "@type": "Article",

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```
"@context": "https://schema.org",
```

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if (is_singular('post')) {     $schema = [       '@context' => 'https://schema.org',

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$schema = [       '@context' => 'https://schema.org',       '@type' => 'Article',

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```
'@context' => 'https://schema.org',
```

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<script type="application/ld+json"> {   "@context": "https://schema.org",

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{   "@context": "https://schema.org",   "@type": "Article",

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```
"@context": "https://schema.org",
```

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{ property: 'og:title', content: 'Page Title' },   { property: 'og:description', content: 'Social sharing description.' },   { tagName: 'link', rel: 'canonical', href: 'https://yourdomain.com/page' },

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{ property: 'og:description', content: 'Social sharing description.' },   { tagName: 'link', rel: 'canonical', href: 'https://yourdomain.com/page' }, ]

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{ tagName: 'link', rel: 'canonical', href: 'https://yourdomain.com/page' },

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**Target**: 80+ AEO score (B+ grade or higher). Validate at [aeo-audit.sh](https://aeo-audit.sh).

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| Claim | Source | |---|---| | Quotations = +41% visibility; Statistics = +33%; Cite Sources = +28% | Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 ([arXiv](https://arxiv.org/abs/2311.09735)) |

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|---|---| | Quotations = +41% visibility; Statistics = +33%; Cite Sources = +28% | Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 ([arXiv](https://arxiv.org/abs/2311.09735)) | | Lower-ranked sites gain up to +115% from GEO

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| Quotations = +41% visibility; Statistics = +33%; Cite Sources = +28% | Aggarwal et al., "GEO: Generative Engine Optimization," KDD 2024 ([arXiv](https://arxiv.org/abs/2311.09735)) |

`improve-aeo-geo/examples/nextjs-blog-before-after.md`

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+ Allow: / + + Sitemap: https://myblog.com/sitemap.xml

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+ Sitemap: https://myblog.com/sitemap.xml

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dangerouslySetInnerHTML={{     __html: JSON.stringify({       '@context': 'https://schema.org',

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__html: JSON.stringify({       '@context': 'https://schema.org',       '@type': 'Organization',

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```
'@context': 'https://schema.org',
```

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'@type': 'Organization',       name: 'My Blog',       url: 'https://myblog.com',

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name: 'My Blog',       url: 'https://myblog.com',       logo: 'https://myblog.com/logo.png',

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```
url: 'https://myblog.com',
```
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```
logo: 'https://myblog.com/logo.png',
```

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const jsonLd = {   '@context': 'https://schema.org',

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```
'@context': 'https://schema.org',
```

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title: `${post.title} | My Blog`,     description: post.excerpt, // 120-160 chars     alternates: { canonical: `https://myblog.com/blog/${params.slug}` },

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description: post.excerpt, // 120-160 chars     alternates: { canonical: `https://myblog.com/blog/${params.slug}` },     openGraph: {

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alternates: { canonical: `https://myblog.com/blog/${params.slug}` },

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## Popular Posts - [Building with Next.js App Router](https://myblog.com/blog/nextjs-app-router)

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- [Building with Next.js App Router](https://myblog.com/blog/nextjs-app-router)

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- [TypeScript Best Practices 2025](https://myblog.com/blog/typescript-2025)

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## About - [About the Author](https://myblog.com/about)

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- [About the Author](https://myblog.com/about)

`research-brand/README.md`

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git clone https://github.com/onvoyage-ai/gtm-engineer-skills.git

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git clone https://github.com/onvoyage-ai/gtm-engineer-skills.git

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```
/research-brand https://www.example.com
```

`research-keywords/README.md`

Access to secretsline 176
```
[Credential-related source omitted]
```

`research-keywords/scripts/keyword-explorer.mjs`

Executable scriptline 1
```
#!/usr/bin/env node
```
Access to secretsline 35
```
[Credential-related source omitted]
```

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hl,   });   const url = `https://www.google.com/complete/search?${params}`;

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const url = `https://www.google.com/complete/search?${params}`;

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```
[Credential-related source omitted]
```

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...params,   });   const url = `https://serpapi.com/search.json?${allParams}`;

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});   const url = `https://serpapi.com/search.json?${allParams}`;   return fetchJSON(url);

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const url = `https://serpapi.com/search.json?${allParams}`;

`research-keywords/scripts/serp-analyzer.mjs`

Executable scriptline 1
```
#!/usr/bin/env node
```
Access to secretsline 28
```
[Credential-related source omitted]
```

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if (!SERPAPI_KEY) {     console.error("Error: SERPAPI_KEY environment variable is required.");     console.error("Get a free key at https://serpapi.com (100 searches/month).");

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console.error("Error: SERPAPI_KEY environment variable is required.");     console.error("Get a free key at https://serpapi.com (100 searches/month).");     process.exit(1);

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console.error("Get a free key at https://serpapi.com (100 searches/month).");

Access to secretsline 137
```
[Credential-related source omitted]
```

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const data = await fetchJSON(`https://serpapi.com/search.json?${params}`);

How the signals fit together

Facts from a static read of the files at the pinned commit. They describe what the code does, not why.

Some files could not be read; the facts below still hold.

No combined signals at this commit.

Works with

Agent compatibility, from the files in this repository
Agent	Status	Evidence	Install to
Claude Code	Compatible	Standard SKILL.md audit-content/SKILL.md	`.claude/skills/<skill-name>/`
Codex	Compatible	Standard SKILL.md audit-content/SKILL.md	`.agents/skills/<skill-name>/`
Cursor	Compatible	Standard SKILL.md audit-content/SKILL.md	`.cursor/skills/<skill-name>/`
Gemini CLI	Compatible	Standard SKILL.md audit-content/SKILL.md	`.gemini/skills/<skill-name>/`
GitHub Copilot	Compatible	Standard SKILL.md audit-content/SKILL.md	`.github/skills/<skill-name>/`
OpenCode	Compatible	Standard SKILL.md audit-content/SKILL.md	`.opencode/skills/<skill-name>/`

Native The repository ships a manifest, folder or frontmatter field for this agent.
Compatible A standard SKILL.md that this agent can read.
Unknown No evidence either way.

Derived automatically from paths, manifests and frontmatter. Not tested on each agent.

Explore alternatives and comparisons

Add this badge to your README

It updates every night and links to this page.

[![onvoyage-ai/gtm-engineer-skills on hotskills](https://hotskills.dev/badge/onvoyage-ai-gtm-engineer-skills.svg)](https://hotskills.dev/skill/onvoyage-ai-gtm-engineer-skills/)

onvoyage-ai/gtm-engineer-skills

History

audit-content/SKILL.md

audit-website-aeo/SKILL.md

build-backlinks/SKILL.md

build-resource-pages/SKILL.md

create-geo-charts/SKILL.md

geo-content-planning/SKILL.md

geo-content-research/SKILL.md

improve-aeo-geo/SKILL.md

reddit-opportunity-research/SKILL.md

research-brand/SKILL.md

research-keywords/SKILL.md

write-seo-geo-content/SKILL.md

Share this page

Heat

Stars over time

Individual skills in this repository

How it works

audit-content

Frontmatter

SKILL.md

Reference documents

The playbook

Files

audit-website-aeo

Frontmatter

SKILL.md

Reference documents

The playbook

Scripts executed separately

Files

build-backlinks

Frontmatter

SKILL.md

Reference documents

The playbook

Files

build-resource-pages

Frontmatter

SKILL.md

Reference documents

The playbook

Files

create-geo-charts

Frontmatter

SKILL.md

Reference documents

The playbook

Files

geo-content-planning

Frontmatter

SKILL.md

Reference documents

The playbook

Files

geo-content-research

Frontmatter

SKILL.md

Reference documents

The playbook

Files

improve-aeo-geo

Frontmatter

SKILL.md

Reference documents

The playbook

Files

reddit-opportunity-research

Frontmatter

SKILL.md

Reference documents

The playbook

Files

research-brand

Frontmatter

SKILL.md

Reference documents

The playbook

Files

`audit-content/SKILL.md`

`audit-website-aeo/SKILL.md`

`build-backlinks/SKILL.md`

`build-resource-pages/SKILL.md`

`create-geo-charts/SKILL.md`

`geo-content-planning/SKILL.md`

`geo-content-research/SKILL.md`

`improve-aeo-geo/SKILL.md`

`reddit-opportunity-research/SKILL.md`

`research-brand/SKILL.md`

`research-keywords/SKILL.md`

`write-seo-geo-content/SKILL.md`

`audit-content/SKILL.md`

`audit-website-aeo/README.md`

`audit-website-aeo/SKILL.md`

`audit-website-aeo/examples/anthropic-com-audit.md`

`audit-website-aeo/scripts/aeo-audit.mjs`

`create-geo-charts/SKILL.md`

`create-geo-charts/examples/ai-referral-traffic-share-v2.html`

`create-geo-charts/examples/ai-referral-traffic-share.html`

`create-geo-charts/examples/ai-toy-brand-comparison.html`

`create-geo-charts/examples/ai-toy-market-growth.html`

`create-geo-charts/examples/ai-toy-parent-concerns.html`

`create-geo-charts/examples/content-freshness-citations-v2.html`

`create-geo-charts/examples/content-freshness-citations.html`

`create-geo-charts/examples/geo-strategy-impact-v2.html`

`create-geo-charts/examples/geo-strategy-impact.html`

`create-geo-charts/examples/scooter-brand-market-share.html`

`create-geo-charts/examples/scooter-market-growth.html`

`create-geo-charts/examples/scooter-specs-comparison.html`

`geo-content-research/SKILL.md`

`improve-aeo-geo/README.md`

`improve-aeo-geo/SKILL.md`

`improve-aeo-geo/examples/nextjs-blog-before-after.md`

`research-brand/README.md`

`research-keywords/README.md`

`research-keywords/scripts/keyword-explorer.mjs`

`research-keywords/scripts/serp-analyzer.mjs`