agentleFS
Sign inStart free
joargpjoargp/skills/news-summary/SKILL.md

news-summary

Skill1 starsChanged 10 months agoMITView on GitHub

This skill should be used when the user asks for news updates, daily briefings, or what's happening in the world. Fetches news from trusted international RSS feeds and can create voice summaries.

  • Reads credentials

4 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions4 projects use a version of this.

    Word for word · 2

    1. stvlynn/qclaw-skills★ 4100% same
    2. OpieTaylor911/openclaw-skills★ 0100% same

    Edited · 0

    None found.

    Wrote their own version · 2

    1. zjfls/zhoujie-claude-skills★ 2same name
    2. KIRRAWA/cogniforge★ 1same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository3 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep summaries concise (5-8 top stories)

    line 100

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

News Summary

Overview

Fetch and summarize news from trusted international sources via RSS feeds.

RSS Feeds

BBC (Primary)

# World news
curl -s "https://feeds.bbci.co.uk/news/world/rss.xml"

# Top stories
curl -s "https://feeds.bbci.co.uk/news/rss.xml"

# Business
curl -s "https://feeds.bbci.co.uk/news/business/rss.xml"

# Technology
curl -s "https://feeds.bbci.co.uk/news/technology/rss.xml"

Reuters

# World news
curl -s "https://www.reutersagency.com/feed/?best-regions=world&post_type=best"

NPR (US perspective)

curl -s "https://feeds.npr.org/1001/rss.xml"

Al Jazeera (Global South perspective)

curl -s "https://www.aljazeera.com/xml/rss/all.xml"

Parse RSS

Extract titles and descriptions:

curl -s "https://feeds.bbci.co.uk/news/world/rss.xml" | \
  grep -E "<title>|<description>" | \
  sed 's/<[^>]*>//g' | \
  sed 's/^[ \t]*//' | \
  head -30

Workflow

Text summary

  1. Fetch BBC world headlines
  2. Optionally supplement with Reuters/NPR
  3. Summarize key stories
  4. Group by region or topic

Voice summary

  1. Create text summary
  2. Generate voice with OpenAI TTS
  3. Send as audio message
curl -s https://api.openai.com/v1/audio/speech \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1-hd",
    "input": "<news summary text>",
    "voice": "onyx",
    "speed": 0.95
  }' \
  --output /tmp/news.mp3

Example Output Format

📰 News Summary [date]

🌍 WORLD
- [headline 1]
- [headline 2]

💼 BUSINESS
- [headline 1]

💻 TECH
- [headline 1]

Best Practices

  • Keep summaries concise (5-8 top stories)
  • Prioritize breaking news and major events
  • For voice: ~2 minutes max
  • Balance perspectives (Western + Global South)
  • Cite source if asked

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free