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A skill for AI agents to discover, fetch, and read articles from RSS and OPML feeds. It includes a Python-based command-line tool, caching to minimize network requests, and platform-agnostic instructions for easy integration.

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RSS Reader Skill

1. Purpose

This skill enables an agent to discover, fetch, and read content from online RSS and OPML feeds. It is designed to be operated via command-line execution.

2. Prerequisites

The execution environment must support:

  • Python 3.x.
  • The ability to install Python packages from a requirements.txt file.
  • Network access to fetch remote content.

The required Python packages are listed in scripts/requirements.txt.

3. Configuration

Before first use, a configuration file must be set up to specify the source of the RSS feeds.

  • File to Edit: assets/config.json
  • Action: Provide a valid URL for an OPML file in the opml_url field.

Example config.json:

{
  "opml_url": "https://your-opml-provider.com/feeds.opml"
}

Note: The assets directory is used for local configuration and caching. It should be excluded from version control.

4. Core Commands

The skill's functionality is exposed through the scripts/rss_fetcher.py script.

Command: List Feeds

Action: Discovers all available RSS feeds from the configured OPML URL. Syntax:

python scripts/rss_fetcher.py --opml-url <your-opml-url>

Command: List Articles from a Feed

Action: Fetches the list of recent articles from a specified RSS feed. Syntax:

python scripts/rss_fetcher.py --feed-url "<feed_xml_url>" --name "<feed_name>"
  • <feed_xml_url>: The direct URL to the feed's XML file.
  • <feed_name>: A unique name for the feed, used for caching.

Command: Read Article Content

Action: Fetches the full content of a specific article. Syntax:

python scripts/rss_fetcher.py --content-url "<article_url>" --title "<article_title>" --author "<article_author>" --date "<publication_date>"
  • <article_url>: The URL of the article to read.
  • Other parameters are used for creating a unique cache entry.

About

A skill for AI agents to discover, fetch, and read articles from RSS and OPML feeds. It includes a Python-based command-line tool, caching to minimize network requests, and platform-agnostic instructions for easy integration.

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1 watching

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