Agent skill

edit-article

Edit and improve articles by restructuring sections, improving clarity, and tightening prose. Use when user wants to edit, revise, or improve an article draft.

stevesolungithub.com/stevesolunGitHub ↗
claude-codeMIT
Install
npx skills add stevesolun/ctx --skill edit-article --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Path: imported-skills/mattpocock/edit-article/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 569
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

1. First, divide the article into sections based on its headings. Think about the main points you want to make during those sections. Consider that information is a directed acyclic graph, and that pieces of information can depend on other pieces of information. Make sure that the order of the sections and their contents respects these dependencies. Confirm the sections with the user. 2. For each section: 2a. Rewrite the section to improve clarity, coherence, and flow. Use maximum 240 characters per paragraph.

More from ctx
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About this skill
What does the edit-article skill do?

Edit and improve articles by restructuring sections, improving clarity, and tightening prose. Use when user wants to edit, revise, or improve an article draft.

How do I install it?

Run `npx skills add stevesolun/ctx --skill edit-article --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From stevesolun/ctx, a repository with 569 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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