blog-post

You can automate data-driven blog posts by gathering statistics from Deadlock API endpoints, patch notes, and community discussions, then drafting Markdown files with baked-in data and citations. This process grounds your content in real numbers while matching your existing tone.

To generate a tone-matched Markdown draft, the skill references existing content in the content/blog directory to align voice and formatting. It then produces a final Markdown draft at content/blog/<slug>.md with baked-in statistics and citations.

Yes, automated research extracts exact statistics from Deadlock API endpoints, assets, and patch notes, alongside community discussions. This data gathering grounds your blog posts in real numbers during the drafting phase.

The best way to add visuals is to prepare optional plots when the topic benefits from visualizations. The skill generates charts and embeds references directly within the Markdown draft to support the baked-in statistics.

You need to provide a topic and a slug to deliver drafts ready for the content/blog repository. The skill uses this single slug to output the final Markdown file at content/blog/<slug>.md.

Automated blog writing works without manual data analysis by performing API data gathering and web research internally. It applies a humanizer pass to ensure the tone-aligned writing reads naturally while retaining exact statistics.