Surf3D AGENT:
aQuickeningNewsAgent.xo

WHAT IT DOES: 
Gathers page nodes for news articles on Art Bell's Quickening News page

WHAT ITS GOOD FOR
A cool way to sort articles and news stories by your own keyword metrics
 and then browse based on your own article ranking system
Grabs the first paragraphs of  collected sorted news articles for you to browse
On a per web page node basis:
   Metric A counts a collection of disaster and bad news related keywords
   Metric B counts a collection of solution related keywords
   Metric C counts a small group of alert and announcement related words
Getting quick glance summaries of which pages have highest hit rates

HOW IT WORKS: 
Looks at all the new story titles and links on Art Bell's Quickening news web page
Performs metric counts and extracts sentences containing preferred extraction
  keywords

HOW TO SET IT UP: 
You can go to artbell.com and click on Library and then again on Quickening News
If you go to the bottom of the page of news articles you can click on Full listing
   for a larger archive
Save-As the provided aQuickeningNewsAgent.xo to a new name, 
   such as MyQuickeningNewsAgent.xo
Type your preferred text extract keywords into the Metric channel lines A and B and C
To gather pictures open the Agent Action Configuration window and under Acquire and Capture
   select the file type (or type in) and the file size parameters you want to accept.  
Note the agent is set to gather text and include False pages

HOW TO USE IT:
Start the agent to see it build up your display of web page nodes
   No need to GET URL - the agent already has it
Point an click on web page nodes (if they are big enough) and then press the space bar
   and that will open the web page you pointed at

VARIATIONS TO TRY:
Browse the different view buttons #1 through #8
Try different searches with different keywords for OR line evaluation
Make agents for differentnew focus topics by changing keywords
Try erasing the words in the Link Text line and replacing them with all the words from
  Metric channel B (they were Metric channel A + C words) and see how the search
  engine selectively prunes articles that are more solution vs. problem oriented