Platform-specific intel for harvesting Hacker News trends — point-velocity ranking, harvest URLs (front page, new, Show, Ask, Algolia), flag-tax mechanics, title rules from HN guidelines, Show HN / Ask HN / link-submission patterns, anchor commenters and dead patterns in 2026. Activates inside an octoweb:trend session whenever the user names HN / Hacker News.
Installation
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
This skill carries the platform-specific mechanics the octoweb:trend agent needs to harvest Hacker News — current ranking signals (point velocity × comment depth × flag-tax × age-decay), harvest URLs, title rules from HN guidelines, Show HN / Ask HN / link-submission patterns, anchor commenters, dead patterns. The agent owns the shared DNA loop; this skill plugs the HN parameters in.
Mental model
HN is one audience with one strict culture: skeptical, technical, anti-marketing, anti-listicle. The ranker is point velocity × comment depth × flag-tax × age-decay. Point velocity in the first 90 minutes is the entire game — a post is either on the front page or dead after that. Comments boost ranking sub-linearly but heavily — a post with 50 points and 80 comments often outranks one with 100 points and 5 comments. Flags are anonymous and powerful — 3–5 flags can sink a climbing post. A title that wins on Reddit dies on HN in 4 minutes if it editorializes or sounds like marketing.
Title rules (HN guidelines + 2026 observed reality)
DO:
Use the article's exact title for link submissions (HN guideline)
Use precise, specific noun phrases
Lead with the artifact, not the actor
DO NOT:
ALL CAPS or excessive punctuation (auto-flags)
Editorialize beyond the article's own phrasing
Use marketing-speak ("revolutionary," "game-changer," "unleash," "groundbreaking")
Add a year suffix unless the article is dated
Use question titles unless Ask HN
Show HN pattern: Show HN: <noun phrase, what it is> — <one-clause clarifier if needed>
Ask HN pattern: Ask HN: <direct question, no preamble>
Body / first-comment patterns
Show HN — first author comment with:
3–5 line context (what it is, what problem it solves, why you built it)
Pricing transparency if commercial (free for X, paid for Y) — opacity flags
Tech stack mention if relevant
Honest limits ("doesn't yet do X") — preempts critical comments
Ask HN — body sets up the question with 3–6 lines of concrete context (specific situation, what you tried, where you're stuck). Vague Ask HN dies.
Link submissions — no body needed. First-comment from submitter sometimes worth it if the article is dense.
Dead patterns (flagged / killed reliably)
"I built X with AI" without substantive demo
Listicle blog posts ("10 tools for ...")
LinkedIn-style motivational
Recycled OpenAI / Anthropic press releases without analysis
Pure SaaS launch posts not in Show HN format
Anything reading as "ChatGPT wrote this" / generative-content tells
Self-promotional past Show HN format
Anchor commenters
Specific high-karma users reliably comment on niche threads. Identify them during harvest — their participation often signals the post will survive the front-page filter. Do not @-mention them in the post (HN doesn't support that culturally) but note them for the user's awareness.
Timing
Best windows: Tue–Thu 8–11 AM ET. Weekend mornings work for personal-blog technical writing.
Late Friday and weekends: slower for hard-tech, faster for opinion pieces.
Post then be available — first 90 minutes the submitter must answer top comments.
Saturated-angle detection
HN's tech-niche saturation cycles fast. Run Algolia "pastWeek" search on the user's topic terms. If 5+ front-page posts hit the same angle in the last 7 days, mark saturated. Common 2026 saturated angles in agents / LLM space: "Why we moved off OpenAI / off Anthropic," "Why we built our own RAG," "GPT-X benchmark results," generic "agent failure" post-mortems without specifics.
Examples
Example 1: Front-page post with full DNA call
Bad — count without context:
Show HN post got 400 points yesterday.
Good — velocity, flag-state, domain, anchor commenters labeled:
"Show HN: {{tool name}} – local agent eval harness"
412 pts / 187 comments / 5h on front page / 82% upvote-implied / not flagged
Submitter: {{handle}} (karma 3,400 — credible)
Domain: github.com — domain trust bonus
Front-page entry: 14 minutes after submission (very fast climb)
Points/hour first 4h: ~75/h (breakout band)
Anchor commenters participating: {{handle1}}, {{handle2}} — high-karma niche regulars
Title type: Show HN, noun phrase + one-clause clarifier
First-comment author post: 5 lines — what it is, problem it solves, stack, free / paid, known limits
DNA: github-hosted artifact + transparent pricing + honest-limit preempt
Example 2: Flagged-cluster teaching example
{{Title}} — 84 pts in 35 min then [flagged] at 47 pts
Submitter karma: 120 (new account)
Domain: marketing-domain.com
Inferred flag reason: SaaS-launch tone + marketing domain + new-account submitter + non-Show-HN format
Lesson: do not submit a SaaS launch post outside the Show HN format from a low-karma account.
Checklist
Before returning the HN section of the brief:
Every cited post has title (verbatim), points, comments, hours-since-submit, domain, submitter handle and karma band, URL, flag-state
Point velocity (pts/hour first 4h) computed and used as primary signal — not raw points
Survival past 90 min noted
Flagged-but-alive and outright-flagged posts surfaced as teaching examples
Anchor commenters identified for the niche (not @-mentioned, just noted)
