Gtm Engineer Skills

GTM Engineer Skills

Search is shifting from blue links to AI answers — and the GTM playbook that won on Google does not win on ChatGPT, Claude, or Perplexity. Most AI agents still respond with generic marketing copy that no one will rank, cite, or publish.

This repo is a different kind of toolkit. Each skill is a focused agent workflow that ships a concrete GTM artifact — a brand DNA doc, a keyword or GEO prompt cluster, a content architecture, AI-citable charts, an AEO audit, a backlink plan, or code-level website fixes. Outputs are files an operator can review, publish, test, or hand to the next skill in the pipeline.

What this repo helps you do

Goal	Skills to use	Output
Understand a market and brand	research-brand, research-keywords, geo-content-research	Brand DNA, SEO/GEO keyword clusters, AI prompt targets
Find demand in real communities	reddit-opportunity-research, build-backlinks	Subreddit opportunities, thread patterns, backlink and mention plan
Plan content that can rank and get cited	geo-content-planning, write-seo-geo-content	Content architecture, product-led article drafts, page briefs
Add evidence and visual assets	create-geo-charts, audit-content	AI-readable charts, data tables, JSON-LD, source verification
Ship resource pages	build-resource-pages	Frontend pages built into a client codebase
Improve AI discoverability	audit-website-aeo, improve-aeo-geo	A-F audit report, prioritized fixes, code changes

Why it exists

Search is shifting from ranked blue links to answer engines: ChatGPT, Claude, Perplexity, Google AI Overviews, and other AI surfaces. Winning there requires different work:

• Pages need direct answers, clear structure, sources, and quotable passages.
• Charts need text layers, tables, and structured data, not just pixels.
• Content plans need to account for prompts, communities, and citations, not only keyword volume.
• Websites need technical signals that crawlers and AI systems can parse reliably.

These skills turn that work into repeatable agent workflows.

Workflow

The skills are designed to run as a pipeline. Each stage creates files that become context for the next stage.

flowchart TD
    RB["research-brand<br/>URL -> brand_dna.md"]

    RK["research-keywords<br/>-> keyword_research.md"]
    ROR["reddit-opportunity-research<br/>-> reddit_opportunities.md"]
    GCR["geo-content-research<br/>-> geo_prompt_targets.md"]

    GCP["geo-content-planning<br/>-> content_architecture.md"]
    BB["build-backlinks<br/>-> backlink_plan.md"]

    WSGC["write-seo-geo-content<br/>-> markdown articles"]
    CGC["create-geo-charts<br/>-> SVG/HTML/CSV/JSON-LD"]

    AC["audit-content<br/>-> verified claims and sources"]

    BRP["build-resource-pages<br/>-> frontend pages"]
    AWA["audit-website-aeo<br/>-> scored audit report"]
    IAG["improve-aeo-geo<br/>-> website code fixes"]

    RB --> RK
    RB --> ROR
    RB --> GCR

    RK --> GCP
    ROR --> GCP
    GCR --> GCP
    ROR --> BB
    GCR --> BB

    GCP --> WSGC
    GCP --> CGC

    WSGC --> AC
    CGC --> AC

    AC --> BRP
    AWA --> IAG

Quickstart

Clone the repo, then symlink the skills you want into your agent's skill directory.

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

Codex

mkdir -p ~/.codex/skills
ln -s "$PWD/research-brand" ~/.codex/skills/research-brand
ln -s "$PWD/research-keywords" ~/.codex/skills/research-keywords
ln -s "$PWD/geo-content-planning" ~/.codex/skills/geo-content-planning
ln -s "$PWD/audit-website-aeo" ~/.codex/skills/audit-website-aeo

Claude Code

mkdir -p ~/.claude/skills
ln -s "$PWD/research-brand" ~/.claude/skills/research-brand
ln -s "$PWD/research-keywords" ~/.claude/skills/research-keywords
ln -s "$PWD/geo-content-planning" ~/.claude/skills/geo-content-planning
ln -s "$PWD/audit-website-aeo" ~/.claude/skills/audit-website-aeo

Each skill folder contains a SKILL.md file and, when useful, a README, examples, scripts, or schemas.

Example prompts

Use one skill at a time:

Use research-brand on https://example.com and create brand_dna.md.

Use research-keywords with brand_dna.md to find SEO and GEO keyword clusters for this product category.

Use audit-website-aeo on https://example.com with a 20 page crawl and produce a prioritized AEO/GEO audit.

Or run a longer workflow:

Use this repo's GTM skills to research the brand, find SEO/GEO opportunities,
build a content architecture, draft the first two resource pages, and audit the
claims before publishing.

Skills

Skill	Use it for	Main output
research-brand	Understand positioning, audience, competitors, voice, and messaging from a company URL	brand_dna.md
research-keywords	Find SEO and GEO keywords using web research, AI analysis, and optional SERP scripts	keyword_research.md
reddit-opportunity-research	Discover Reddit pain points, subreddits, thread patterns, and user language	reddit_opportunities.md
geo-content-research	Identify prompts people ask AI engines about a category	geo_prompt_targets.md
geo-content-planning	Turn research into a page architecture with priority, URLs, and page types	content_architecture.md
write-seo-geo-content	Draft product-led content optimized for search and AI citation	Markdown articles with frontmatter
create-geo-charts	Produce data visualizations with text summaries, HTML tables, CSV, and JSON-LD	AI-readable chart packages
audit-content	Verify URLs, statistics, claims, source attribution, and internal consistency	Audit report
build-resource-pages	Build resource center pages inside a client codebase	Frontend implementation
audit-website-aeo	Crawl a live site and score AI discoverability with deterministic and content checks	aeo_audit_report.md
improve-aeo-geo	Apply code-level AEO/GEO fixes to a website	Website code changes
build-backlinks	Find free backlink and mention opportunities across communities and directories	backlink_plan.md

Sample outputs and examples

• audit-website-aeo/examples/anthropic-com-audit.md: example scored AEO/GEO audit.
• improve-aeo-geo/examples/nextjs-blog-before-after.md: before/after improvement plan for a Next.js blog.
• improve-aeo-geo/examples/wordpress-business-before-after.md: before/after improvement plan for a WordPress business site.
• create-geo-charts/examples/: sample charts, CSV datasets, and HTML outputs.
• geo-content-planning/plan.csv.schema.md: content plan CSV contract.
• research-keywords/keywords.csv.schema.md: keyword CSV contract.
• geo-content-research/prompts.csv.schema.md: GEO prompt CSV contract.

Built-in tools

Some skills include scripts for deterministic or higher-volume work:

Tool	Location	Purpose
AEO crawler	audit-website-aeo/scripts/aeo-audit.mjs	Zero-dependency Node crawler for 16 foundational AEO checks
Keyword explorer	research-keywords/scripts/keyword-explorer.mjs	Autocomplete, PAA, related search, and SERP feature discovery
SERP analyzer	research-keywords/scripts/serp-analyzer.mjs	Competitive SERP analysis and AI Overview opportunity detection

Run the eval suite with:

npm run test:evals

The evals currently cover CSV contract validation and deterministic regressions for the AEO crawler.

Research references

This repo's AEO/GEO guidance is grounded in published research and large-scale industry studies, including:

• GEO paper, KDD 2024: https://arxiv.org/abs/2311.09735
• SE Ranking AI Mode optimization study: https://seranking.com/blog/how-to-optimize-for-ai-mode/
• Growth Memo AI citation analysis: https://www.growth-memo.com/p/the-science-of-how-ai-pays-attention
• Ahrefs freshness and AI citation study: https://ahrefs.com/blog/do-ai-assistants-prefer-to-cite-fresh-content/
• Conductor AEO/GEO benchmarks: https://www.conductor.com/academy/aeo-geo-benchmarks-report/
• AirOps LLM content structure report: https://www.airops.com/report/structuring-content-for-llms

Platform notes

• The skills work with both Codex and Claude Code because each skill is packaged as a folder with SKILL.md.
• Reddit access differs by product. ChatGPT has native Reddit access in-product; Claude generally does not, so outputs may vary by environment.
• SEO keywords should be short search phrases. GEO prompts should be complete user questions.
• Do not fabricate data. Every statistic, benchmark, and third-party claim should have a source.

Contributing

See CONTRIBUTING.md for how to add skills, improve workflows, or contribute examples.

When adding or changing a skill, prefer:

• A clear SKILL.md with trigger conditions and workflow steps.
• A README that explains usage, outputs, and examples.
• Schemas for structured CSV/JSON outputs.
• Offline tests when behavior can be validated deterministically.

License

MIT, see LICENSE.

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