write-seo-geo-content

write-seo-geo-content is a skill for Claude Code, Codex from onvoyage-ai/gtm-engineer-skills. It costs 54 tokens per session (4,279 once invoked), scanned A, original, MIT.

A writing process for product-focused web pages that aims to work well in search engines and answer-generating AI systems. It creates Markdown files with page details and cited sources.

In plain words
What is it for?
Use it to plan or write comparison pages, guides, use-case pages, learning content, and trust-focused pages.
Why use it?
It prevents writing from being based on made-up claims or unchecked sources. Research is completed first so the page can match the intended audience and search purpose.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to plan or write comparison pages, guides, use-case pages, learning content, and trust-focused pages.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content
About the project

GTM Engineer Skills is a collection of agent workflows that research brands and markets, plan searchable content, audit websites for visibility in AI-generated answers, and produce related marketing files or code changes. Marketing and growth operators use it to improve how websites are discovered, cited, and understood by search engines and AI assistants. The catalogue entries are the project's individual skills.

onvoyage-ai/gtm-engineer-skills · 1,301 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add onvoyage-ai/gtm-engineer-skills --skill write-seo-geo-content
Clone the repo
git clone --depth 1 https://github.com/onvoyage-ai/gtm-engineer-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for write-seo-geo-content

README.md
[![agentmods](https://agentmods.dev/badge/skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content/github.svg)](https://agentmods.dev/skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content)
Your own site
<a href="https://agentmods.dev/skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content"><img src="https://agentmods.dev/badge/skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for write-seo-geo-content

Your own site · 80×15
<a href="https://agentmods.dev/skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content"><img src="https://agentmods.dev/badge/skills/onvoyage-ai/gtm-engineer-skills/write-seo-geo-content.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,279 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.04279
Opus 5 $0.00027 $0.02139
Sonnet 5 $0.00011 $0.00856
Haiku 4.5 $0.00005 $0.00428

Measured 13d ago against content hash 614dcc976599, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

write-seo-geo-content scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

write-seo-geo-content/SKILL.md · 419 lines

How it starts

The opening of the file, as written. The whole thing — 419 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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
  6. Get user approval on topic and keyword before proceeding to Writing Mode

Writing Mode

Use when a specific topic and keyword are confirmed.

  1. Complete all Pre-Writing Research steps
  2. Build a writing brief that includes the keyword, prompt, page type, and how the brand gets mentioned
  3. Write the content using the page-type framework
  4. Apply all SEO Standards, GEO standards, and E-E-A-T signals
  5. Verify against the Quality Checklist before delivering

Pre-Writing Research Protocol

Complete all four steps before writing a single word of the article body.

Step 1: Reference Review

  • Load any product docs, landing pages, or directories the user provides
  • Identify: core features, key differentiators, target customer, pricing, use cases
  • Note exact terminology and claims the company uses — mirror this language in the article

Step 2: Page Brief

  • Confirm the page type: comparison, guide, use case, learn/definition, or trust/FAQ
  • Confirm the primary SEO keyword
  • Confirm 1-3 target GEO prompts
  • Write one line for how the brand gets mentioned in the AI answer
  • If the user has a content plan, preserve its section, subsection, and proposed URL

Read the full file on GitHub · 419 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 419 lines · 54 tokens per session scan A 614dcc976599

Subscribe to this mod's changes

write-seo-geo-content is a skill published in the GitHub repository onvoyage-ai/gtm-engineer-skills (1,301 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 4,279 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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