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Score Article ​

Evaluate the article at the URL provided in $ARGUMENTS.

Step 1 — Fetch ​

Use WebFetch to retrieve the article content from the URL.

Step 2 — Predict ​

Based only on the title and source domain, write what you would tell someone who asked you about this topic. This represents what someone could learn without reading the article — the "LLM baseline."

In your thinking, exhaust your knowledge of this topic before writing your prediction — cover the standard explanations, common misconceptions, and typical expert takes. The more complete your prediction, the more honest the scoring.

Step 3 — Score the delta ​

After reading the full content, rate how much the article exceeds your prediction:

  • - Your prediction covered it. This is a restatement of common knowledge.
  • . Your prediction got the gist but missed useful nuance. A good read, but the ideas are findable elsewhere with effort.
  • + Your prediction was wrong or incomplete in a way that matters. The article contains signal you'd lose if you never read it.

A + means one of:

  • Novel information: primary experience, insider context, non-public knowledge, or historical detail that isn't in the common record.
  • Novel connection: links ideas you'd know separately in a way that changes how you'd reason or act. Not just "A relates to B" but "A causes B, which means you should do C differently."

Most articles are well-written restatements of accessible knowledge. Default to .. Expect ~70% ., ~20% -, ~10% +.

Step 4 — Present results ​

Show the user:

  1. The score (-, ., or +) with a one-line summary
  2. Your prediction (what you'd have said without reading the article)
  3. If scored . or +: the delta (what was new beyond your prediction)
  4. If scored +: the delta type (novel information or novel connection)
  5. Brief reasoning for the score
  6. Tags: 3-5 short topic tags (e.g. "distributed-systems", "privacy", "nz-politics")
  7. The jury:
    • Case for reading: The strongest argument for why this is worth the reader's time
    • Case for skimming: If the reader only has 5 minutes, what sections or passages contain the real value? Be specific — cite sections, arguments, or examples worth slowing down for
    • Case for skipping: The strongest honest argument for deleting this from a reading backlog — consider: is the core insight summarisable in a sentence? Has the topic moved on since publication? Would asking an LLM get you 90% of the value?
  8. Follow up: 3-5 specific search queries or keywords for someone who wants to go deeper on the most interesting threads