${var} — Optional topic filter (e.g. ai-agents, crypto, security). If empty, uses interests from MEMORY.md.

If ${var} is set, weight stories matching that topic more heavily but still include 1–2 high-signal off-topic items so the digest stays well-rounded.

Context

Read memory/MEMORY.md for tracked topics and interests.
Read the last 2 days of memory/logs/ and .cache/hn-seen-ids.json (if present) to skip stories already covered. The cache file is auto-created; safe to delete to reset dedup.

1. Gather candidates

Aim for ~40 candidate stories. Hit these sources, dedupe by id:

a. Best stories (longer-term quality ranking, less recency-biased than topstories):

curl -s "https://hacker-news.firebaseio.com/v0/beststories.json" | jq '.[0:30][]'

b. Algolia front_page — prefiltered, returns full metadata inline (one call):

curl -s "https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage=30"

c. If ${var} is set, topic-targeted Algolia search (last 36h, points>30):

SINCE=$(date -d '36 hours ago' +%s)
QUERY=$(printf %s "${var}" | jq -sRr @uri)
curl -s "https://hn.algolia.com/api/v1/search?query=${QUERY}&tags=story&numericFilters=created_at_i>${SINCE},points>30&hitsPerPage=20"

For Firebase ids without metadata, hit https://hacker-news.firebaseio.com/v0/item/${ID}.json. If any curl call fails (sandbox can block outbound), retry the same URL with WebFetch.

2. Score and rank

For each candidate, compute a composite signal:

score      = points + 1.5 * comments − age_penalty + topic_bonus
age_penalty = max(0, hours_since_post − 12) * 2
topic_bonus = +30 if matches ${var} or a MEMORY.md interest

Drop anything with score < 80 after penalties. Drop anything whose id appears in .cache/hn-seen-ids.json from the last 7 days. Drop job posts (type=job) and pure poll results.

3. Cluster into themes

Group surviving stories into 2–4 themes — common buckets: AI & agents, Infra & devtools, Security & policy, Science & culture, Business & funding. If a theme has only one story, fold it into a Misc bucket.

Pick 5–7 stories total, distributed across themes (max 3 per theme). Within a theme, take the highest scoring story plus one runner-up only if it's substantively different (different sub-topic, not just another take on the same news).

4. Mine comments for insight

For each chosen story, fetch the discussion thread:

curl -s "https://hn.algolia.com/api/v1/items/${ID}"

Extract the single most insightful comment. A good insight comment:

length > 200 chars
contains specific facts, numbers, code, or substantive critique (not generic agreement)
ideally challenges, extends, or contextualizes the article
skip "this", "+1", "lol", and obvious low-effort replies

If the comment thread is thin (<10 comments), skip the HN take and add a 1-line Author claim line from the article URL via WebFetch instead.

5. Format and send

Lead with a one-line signal line describing the day's shape (e.g. "Heavy AI-tooling day — 3 of 7 are agent infra; one acquisition story and a kernel CVE round it out.").

Output is a flat numbered list (not nested per-theme sections) — each entry carries its cluster label inline so downstream consumers can parse it linearly:

*HN Digest — ${today}*

_${signal_line}_

1. **[AI & agents]** [Title](url) — 412 pts · 287 comments
   Why it matters: 1 sentence on the actual claim or news.
   HN take: "single quoted insight from a top comment" — _commenter_
   [Discussion](https://news.ycombinator.com/item?id=ID)

2. **[Infra & devtools]** ...

Hard constraints:

under 4000 chars total
max 7 stories
every entry has both Why it matters and (HN take OR Author claim) — no headline-only entries
no marketing language; if a comment quote runs >220 chars, trim with ellipsis

Send via ./notify "$(cat digest.md)" (or pipe directly).

6. Persist and log

Write all included story ids to .cache/hn-seen-ids.json as { "id": <unix_ts>, ... } (auto-created; safe to delete to reset dedup). On each run, prune entries older than 7 days before writing.

Append to memory/logs/${today}.md:

### hacker-news-digest
- Var: ${var:-default}
- Sent ${N} stories across ${M} themes (${theme list})
- Top story: [title] (${pts}pts, ${comments}c)
- Skipped ${K} as already-seen via .cache/hn-seen-ids.json

If after filtering and dedup zero stories remain, log HN_DIGEST_EMPTY: <reason> (e.g. "all 12 candidates already sent in last 7 days") and do not call ./notify. Empty digests are noise.

Sandbox note

The sandbox may block outbound curl. Use WebFetch as a fallback for any URL fetch above. Both Firebase HN (hacker-news.firebaseio.com) and Algolia HN (hn.algolia.com) are public — no auth, no env vars in headers — so neither pre-fetch nor post-process patterns are required.

Hacker News Digest