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Blogwatcher

Organization
taracodlabs
blogwatcher

Monitor RSS / Atom feeds for new posts (Python feedparser)

Overview

Publishertaracodlabs
Repositoryaiden
Skill nameblogwatcher
Stars
852
Forks
150
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by taracodlabs on GitHub. Read the source before you install it.

Installation

Install the Blogwatcher AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/taracodlabs/aiden/tree/main/skills/blogwatcher
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/taracodlabs/aiden.git /tmp/aiden
mkdir -p .claude/skills
cp -r /tmp/aiden/skills/blogwatcher .claude/skills/blogwatcher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Blogwatcher in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Blogwatcher on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Blogwatcher is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Blog and Feed Watcher

Monitor RSS and Atom feeds from blogs, news sites, and podcasts to track new posts. Uses the feedparser Python library — no API keys required for most feeds.

When to Use

  • User wants to check for new posts from specific blogs or news sites
  • User wants to aggregate headlines from multiple sources
  • User wants to monitor a research blog or tech feed for updates
  • User wants to read the latest posts from a site that has an RSS feed
  • User wants to set up periodic feed monitoring

How to Use

1. Install feedparser

powershell
pip install feedparser

2. Read a single RSS/Atom feed

python
import feedparser
from datetime import datetime

feed = feedparser.parse("https://news.ycombinator.com/rss")
print(f"Feed: {feed.feed.title}")
print(f"Posts: {len(feed.entries)}\n")

for entry in feed.entries[:5]:
  title   = entry.get("title", "No title")
  link    = entry.get("link", "")
  date    = entry.get("published", "Unknown date")
  print(f"• {title}\n  {link}\n  {date}\n")

3. Monitor multiple feeds

python
import feedparser, time

FEEDS = [
  "https://feeds.feedburner.com/oreilly/radar",
  "https://blog.openai.com/rss/",
  "https://news.ycombinator.com/rss",
  "https://simonwillison.net/atom/everything/",
]

def fetch_all(feeds, max_per_feed=5):
  results = []
  for url in feeds:
    feed = feedparser.parse(url)
    for entry in feed.entries[:max_per_feed]:
      results.append({
        "source":    feed.feed.get("title", url),
        "title":     entry.get("title", ""),
        "link":      entry.get("link", ""),
        "published": entry.get("published", ""),
      })
  return sorted(results, key=lambda x: x["published"], reverse=True)

for item in fetch_all(FEEDS):
  print(f"[{item['source']}] {item['title']}\n  {item['link']}")

4. Filter posts by keyword

python
import feedparser

def search_feed(url, keyword):
  feed    = feedparser.parse(url)
  keyword = keyword.lower()
  matches = [
    e for e in feed.entries
    if keyword in e.get("title","").lower() or keyword in e.get("summary","").lower()
  ]
  for e in matches:
    print(f"• {e.title}\n  {e.link}\n")

search_feed("https://news.ycombinator.com/rss", "llm")

5. Find the RSS feed URL for a site

Common RSS URL patterns:

https://site.com/feed
https://site.com/rss
https://site.com/feed.xml
https://site.com/atom.xml
https://site.com/blog/feed
python
import feedparser, requests
from bs4 import BeautifulSoup   # pip install beautifulsoup4

def find_feed(site_url):
  resp = requests.get(site_url, timeout=10, headers={"User-Agent": "Mozilla/5.0"})
  soup = BeautifulSoup(resp.text, "html.parser")
  for tag in soup.find_all("link", type=lambda t: t and "rss" in t or "atom" in t):
    print(tag.get("href"))

find_feed("https://simonwillison.net")

6. Save latest posts to a file

python
import feedparser, json

feed  = feedparser.parse("https://news.ycombinator.com/rss")
posts = [{"title": e.title, "link": e.link, "date": e.get("published","")} for e in feed.entries[:20]]
with open("hn_feed.json", "w") as f:
  json.dump(posts, f, indent=2)
print(f"Saved {len(posts)} posts to hn_feed.json")

Examples

"What are the latest posts from Hacker News?" → Use step 2 with https://news.ycombinator.com/rss.

"Monitor these 4 AI blogs and show me posts about agents from the last week" → Use step 3 to fetch all, then step 4 logic to filter for agent keyword.

"Does this blog have an RSS feed? If so, get the latest 5 posts" → Use step 5 to discover the feed URL, then step 2 to fetch posts.

Cautions

  • Some sites block RSS scrapers — use a browser-like User-Agent header if getting 403 errors
  • feedparser handles both RSS 2.0, RSS 1.0, and Atom — no need to distinguish them
  • entry.published format varies by feed — some use RFC 2822, others ISO 8601; don't assume a format
  • Very active feeds (e.g. Reddit) may return 100+ entries — always use slicing ([:n]) to limit output

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Blogwatcher AI skill do?

Monitor RSS / Atom feeds for new posts (Python feedparser)

Why use Blogwatcher on TypingMind?

Because you install it once and use it with any model. Blogwatcher is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Blogwatcher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/taracodlabs/aiden/tree/main/skills/blogwatcher. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Blogwatcher?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Blogwatcher?

As many as you like. As long as a model supports skills, you can use Blogwatcher with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Blogwatcher AI skill free?

Yes. It is published on GitHub by taracodlabs under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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