Morning Briefing
Step 1 — Pull user interests from memory
memory_search("interests topics preferences technology news")
Do this first, before fetching stories — the results determine how stories are ranked. Extract any topics, technologies, or themes found. If nothing relevant comes back, fall back to HN ranking order.
Step 2 — Fetch top HN stories
python3 skills/hn-morning-brief/scripts/fetch_hn.py --limit 20
(Path is relative to the project root — openclaw installs this skill at skills/hn-morning-brief/.)
Returns JSON with: title, article_url, hn_url, domain, author, points, num_comments.
Step 3 — Rank and filter
Score each story by combining two signals:
- Relevance to user interests (from memory) — a story the user cares about is worth more regardless of score
- HN points — use as a tiebreaker and quality signal when interests are unclear
Surface the 8–12 highest-scoring stories. If memory search returned no clear interests, rank by points only.
Step 4 — Present briefing
## HN Morning Brief — {today's date}
{N} stories picked for you
1. **{Title}** `{domain}` · ⬆ {points} · 💬 {num_comments}
{one-line context or why this is interesting}
→ [Article]({article_url}) · [HN Discussion]({hn_url})
2. ...
---
Say "dive deeper into #N" or "tell me more about [title]" to get a full summary.
Diving Deeper
When the user picks a story:
- Fetch and summarize the article — read the article URL and write a 3–5 sentence summary of the key points. Do this even if the user just says "more on #3" — they want the content, not just the link.
- Show both links:
- Article:
{article_url}
- HN Discussion:
{hn_url} (often where the most interesting debate happens)
- Offer to go further: "Want me to search for more context on this?"
Gotchas
article_url is the original article. hn_url is the HN discussion thread. Never swap them — linking to the HN page when the user wants the article is a bad experience.- If the article is a PDF or appears paywalled, say so and summarize from the title, domain, and any available description instead of silently failing.
- If
memory_search returns no clear interests, rank by points and don't guess — invented interests will surface irrelevant stories.
