Agent skill · Media & Video

web-research

Use when extracting article text from news URLs or downloading video or audio with metadata

jeremylongshoregithub.com/jeremylongshoreGitHub ↗
claude-coderead-onlyMIT
Install
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill web-research --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 3 KB
Bundled scripts: none
Version: 1.0.0
Declared author: ykotik
Allowed tools: Bash(python3*)Bash(yt-dlp*)Read
Path: plugins/productivity/cli-power-skills/skills/web-research/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,596
Language: Python
Read our review of the source →

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

From the SKILL.md

# Web Research ## When to Use - Extracting clean article text and metadata from a news/blog URL - Downloading video or audio from supported sites with full metadata - Getting video/audio metadata without downloading the media ## Tools | Tool | Purpose | Structured output | |------|---------|-------------------| | **newspaper4k** | Extract article text, title, authors, date from URLs | Python objec

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About this skill
What does the web-research skill do?

Use when extracting article text from news URLs or downloading video or audio with metadata

How do I install it?

Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill web-research --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 jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 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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