I Built Reusable Marketing Skills for GitHub Copilot — Here's How (and Why)

Source: Dev.to

What if your code editor could do keyword research, audit your SEO, and optimize your content for AI search engines — without leaving VS Code?

I built a set of open‑source agent skills that turn GitHub Copilot into a hands‑on marketing strategist.
Here’s what I learned, how they work, and how you can use (or build) your own.

The problem

I run a small website. Every time I wanted to write a blog post, the workflow looked like this:

1. Open Ahrefs / Semrush → research keywords
2. Open Google Docs → write the article
3. Open WordPress → publish and fill in SEO fields
4. Open ChatGPT → rewrite for social media

Five tools. Five context switches.

And every time I found myself giving the same SEO instructions to AI assistants:

• “Use the keyword in the first paragraph”
• “Write a meta description under 155 characters”
• “Structure with H2/H3 headings”

What if I could encode all that knowledge once, and have my AI assistant apply it automatically?

The solution: Copilot Skills

GitHub Copilot (in agent mode) can read SKILL.md files from your workspace.
These files act as knowledge modules — they tell Copilot how to approach a domain, what rules to follow, and which frameworks to apply.

I created four skills that cover the full marketing workflow:

seo-keyword-research   →  Find what your audience searches for
        ↓
seo-strategy           →  Structure your site to rank
        ↓
geo-optimization       →  Get cited by AI search engines
        ↓
content-creator        →  Write content that ranks AND gets cited

What’s inside a skill?

A skill is just a Markdown file with structured knowledge.
Below is a simplified view of the GEO (Generative Engine Optimization) skill.

name: geo-optimization
description: |
  "Optimize content for AI search engines like ChatGPT, Gemini, and Perplexity.
   Use when the user mentions 'AI visibility', 'GEO', 'AI search', or 'cited by AI'."

GEO — Generative Engine Optimization

What is GEO?
GEO = optimizing content so AI‑powered search engines cite your brand in generated answers.

GEO Scorecard (16 criteria)

Anti‑patterns

The description field is the trigger – Copilot uses it to decide when to invoke the skill.
The body contains the actual knowledge the AI applies.

How it works in practice

A real session

Me: “Do keyword research for a blog about home espresso machines.”

Copilot (automatically invokes seo-keyword-research):

• Searches the web for related keywords
• Classifies intent (informational, commercial, transactional)
• Analyzes SERP features
• Outputs a structured keyword map with primary/secondary keywords, difficulty estimates, and content‑type recommendations

Me: “Now write the article and optimize it for AI search.”

Copilot (invokes content-creator + geo-optimization):

• Writes with proper H2/H3 structure
• Includes the keyword in the first paragraph
• Adds statistics with citations (GEO requirement)
• Uses authoritative tone
• Ends with a clear conclusion (AI search engines need this)
• Generates meta title and description within character limits

Me: “Publish as draft to WordPress.”

Copilot (uses REST‑API knowledge from seo-strategy):

• Creates the post via wp-json/wp/v2/posts
• Sets Yoast SEO meta fields
• Outputs the draft URL

Total time: ~15 minutes. From zero to published draft with SEO metadata.

The GEO angle: why AI search changes everything

When someone asks ChatGPT “what’s the best espresso machine for beginners?”, the answer comes from somewhere.
That somewhere could be your website — but only if your content is structured in a way AI models can parse and trust.

This is Generative Engine Optimization (GEO), essentially SEO for AI search engines.
Research (Aggarwal et al., 2024) shows that GEO techniques can boost visibility in AI‑generated answers by up to 40 %.

My geo‑optimization skill includes

• A 16‑criterion scorecard for AI‑readiness
• Writing guidelines that balance human readability and AI parseability
• Anti‑patterns (things that make AI skip your content)
• E‑E‑A‑T implementation (Experience, Expertise, Authoritativeness, Trust)

What I learned building these skills

Installation (30 seconds)

# Clone the repo directly into the .github/skills folder
git clone https://github.com/helder-ai/marketing-skills.git \
    .github/skills/marketing

That’s it. Open VS Code with Copilot agent mode and start asking marketing questions. Copilot auto‑discovers the skills.

Or as a Git submodule (stays updatable)

git submodule add https://github.com/helder-ai/marketing-skills.git \
    .github/skills/marketing

Now you have a portable, up‑to‑date library of marketing‑focused Copilot skills ready to super‑charge your content workflow.

Our Own Skills

The pattern works for any domain knowledge:

1. Create a skill file

   .github/skills/your-skill/SKILL.md

2. Add YAML front‑matter with name and description (include trigger words).
3. Write structured knowledge – tables, checklists, decision trees.
4. Add references for any factual claims.
5. Test it – ask Copilot questions in the skill’s domain and verify that the skill is invoked.

Domains that would benefit from this approach

The repo

• GitHub:
• License: CC BY‑NC 4.0 – free to use, adapt, and learn from.

If you find it useful:

• ⭐ the repo
• Open a PR if you have improvements (SEO practitioners, your expertise is especially welcome!)

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What domain knowledge would you encode as a Copilot skill?
Let me know in the comments!