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# Marketing ops as code: Automating events from planning to follow-up on GitHub

**[GitHub Blog](https://daily.dev/sources/ghblog)** · 12 min read · 0 upvotes · 0 comments

## Summary

A GitHub marketing lead in Japan and Korea describes automating the entire event lifecycle (landing pages, UTM links, invitations, registrant screening, CRM uploads, and reports) using GitHub Issues, labels, GitHub Actions, and GitHub Copilot. The system relies on issue forms as structured intake, labels as triggers, an AGENTS.md runbook file, Copilot agent skills written as SKILL.md files, a DRY_RUN switch for safe testing, and built-in guardrails like secret scanning push protection and Copilot's no-retention data policy. The author frames this as a template anyone with repetitive, API-accessible work can replicate by writing down their runbooks.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://github.blog/ai-and-ml/github-copilot/marketing-ops-as-code-automating-events-from-planning-to-follow-up-on-github>

## Questions this post answers

### What is a SKILL.md file in GitHub Copilot and how does it work?

A SKILL.md file is a written procedure in plain Markdown that tells GitHub Copilot what to do, in what order, and what to watch out for, functioning like an agent skill. It lets non-fixed, flexible workflows (like market-specific post-event follow-up) be executed by Copilot without hard-coding logic, and new skills go through pull request review with a CODEOWNERS file routing approvals.

_Teams turning runbooks into repeatable AI-driven workflows can find implementation write-ups like this on daily.dev._

### How can I prevent GitHub Copilot automation from accidentally leaking API secrets into a repository?

GitHub's secret scanning with push protection blocks a push before a detected secret ever lands in the repository, and for GitHub's own tokens, any that slip through are revoked automatically. This guardrail, combined with a DRY_RUN repository variable that lets every workflow run without touching external systems, allows safe experimentation with automation that touches customer data and credentials.

_Developers wiring up automation with sensitive credentials can track guardrail practices like these via daily.dev._

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---

Tags: [#github](https://daily.dev/tags/github), [#ai-agents](https://daily.dev/tags/ai-agents), [#automation](https://daily.dev/tags/automation), [#github-actions](https://daily.dev/tags/github-actions)

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