medium blog writer

The problem

Writing high-quality Medium posts takes hours of research, outlining, and drafting. AI-generated drafts often feel robotic, lack credible citations, and struggle to pass AI-detection filters without heavy manual editing.

What it does

• Executes a multi-stage research pipeline with depth settings ranging from quick scans to 20+ sources.
• Generates structured outlines and full markdown drafts based on user-configurable parameters like technical style and target word counts.
• Applies a mandatory, bundled humanizer pass to strip away common AI writing patterns and rhythmic tells.
• Performs automated quality checks for readability, SEO, citation counts, and image placement.
• Assembles a final export bundle including the post, source references, and metadata for immediate publishing.

Frameworks & tools

Works standalone using web_search and bash_tool, or integrates with the Medium Blog Generator MCP. Uses Python 3 scripts for session management and quality analysis.

Why this beats prompting it yourself

This skill replaces a dozens-of-prompts workflow with a governed pipeline. It enforces a "humanizer" protocol that goes beyond simple rewriting, and it maintains state across sessions so you can pause, edit, or pivot mid-pipeline without losing research context.

Use cases

• Drafting technical deep-dives with citations from arXiv and official documentation.
• Creating long-form storytelling or "how-to" articles with specific section counts.
• Preparing posts for AI-detection tools using the automated plagiarism chunking tool.
• Managing a high-volume blog production schedule with consistent quality checks.

Known limitations

Cannot access private paywalled content or run external AI-detection APIs directly. Image support is limited to locating public URLs for attribution rather than generating or downloading files.