Trend Landing Page: an Agent Skill for new-keyword pages

Free SKILL.md · works in Claude Code, OpenAI Codex and Cursor · tested on getaicodingagent.com

trend-landing-page is a free Agent Skill that turns a fresh search term — a just-announced or rumored model, product or event — into an answer-first landing page: it researches official and reputable sources, separates confirmed facts from reports and rumors in a fact ledger, writes the page with a sourced FAQ and NewsArticle, FAQPage and BreadcrumbList JSON-LD, then links it internally and updates the sitemap and llms.txt.

What it does

  • Researches in three source tiers (official, reputable reporting, social) and opens every source instead of trusting snippets
  • Builds a claim-by-claim fact ledger: CONFIRMED / REPORTED / RUMORED / UNSUPPORTED
  • Writes title, meta description and an answer-first page structure aimed at real intents (release date, pricing, vs rival, availability)
  • Adds valid NewsArticle (with citations), FAQPage and BreadcrumbList JSON-LD
  • Wires the page in: internal links from related pages, sitemap, llms.txt, news feed, IndexNow — and records a re-check trigger

Who it's for

  • Content sites and newsletters that want to rank first on new AI terms without publishing rumors as facts
  • Developer-marketers who build pages from data and templates with a coding agent
  • Anyone tired of AI-written 'news' pages that invent release dates and benchmarks

Real case: getaicodingagent.com

Our Gemini 4 Carbon explainer was produced with this workflow two days after Business Insider reported the internal model. The page states plainly that Carbon is reported, unconfirmed, lists what Business Insider actually said, shows what is known vs unknown, and leaves out viral X claims that Carbon "beats Opus 5.5 and GPT-6 Astra" because no source we could verify supports them. It is linked from every tool page that runs Gemini models, the news feed, the sitemap and llms.txt.

Example output

Fact ledger — "Gemini 4 Carbon" (2026-10-11)
| Claim                                         | Status      | Source                    |
| Internal Gemini 4 version named Carbon exists | REPORTED    | Business Insider, Oct 9   |
| Possibly a checkpoint of Gemini 4 Argon       | REPORTED    | Business Insider          |
| "Feels like Opus 5.5" for coding              | REPORTED    | BI (employee quote)       |
| Gemini 4 Argon announced Sep 30, $2/$10 per M | CONFIRMED   | blog.google, Reuters      |
| Carbon beats Opus 5.5 and GPT-6 Astra         | UNSUPPORTED | X posts only — excluded   |
| Release date / pricing for Carbon             | UNKNOWN     | Google declined to comment|

New page: /models/gemini-4-carbon  (status: reported)
Sources used: 5 (Tier1 1, Tier2 3); claims excluded as unsupported: 2
Linked from: 10 tool pages, home news, /news; sitemap + llms.txt updated
Re-check: Google announces Carbon or ships an Argon update — every 24-48 h

Install

One line — all three agents

for d in ~/.claude/skills ~/.agents/skills; do mkdir -p "$d/trend-landing-page" && curl -fsSL https://getaicodingagent.com/skills/trend-landing-page/SKILL.md -o "$d/trend-landing-page/SKILL.md"; done

Installs to ~/.claude/skills (Claude Code) and ~/.agents/skills (Codex and Cursor). Restart the agent afterwards.

Claude Code

mkdir -p ~/.claude/skills/trend-landing-page && curl -fsSL https://getaicodingagent.com/skills/trend-landing-page/SKILL.md -o ~/.claude/skills/trend-landing-page/SKILL.md

Personal skill for all projects. For one project, use .claude/skills/trend-landing-page/SKILL.md in the repo and commit it. Run it with /trend-landing-page or just describe the task. Claude Code skills docs.

OpenAI Codex

mkdir -p ~/.agents/skills/trend-landing-page && curl -fsSL https://getaicodingagent.com/skills/trend-landing-page/SKILL.md -o ~/.agents/skills/trend-landing-page/SKILL.md

User-level skill. For a repository, use .agents/skills/trend-landing-page/SKILL.md (Codex scans .agents/skills from the working directory up to the repo root). Restart Codex; it picks the skill from its description, or name it in your prompt. Codex skills docs.

Cursor

mkdir -p .cursor/skills/trend-landing-page && curl -fsSL https://getaicodingagent.com/skills/trend-landing-page/SKILL.md -o .cursor/skills/trend-landing-page/SKILL.md

Run in your project root (project skill). For all projects use ~/.cursor/skills/trend-landing-page/; Cursor also loads .agents/skills and Claude/Codex skill folders. Invoke with /trend-landing-page in Agent chat. Cursor skills docs.

Or download SKILL.md and place it at <skills-folder>/trend-landing-page/SKILL.md — the folder name must match the name in the frontmatter.

How to use it

After installing, restart your agent and ask in plain language — the agent loads the skill when the request matches its description:

  • Make a trend landing page for "<new model name>"
  • Someone leaked <product> pricing — build a what-we-know page with sources
  • Write an answer-first explainer for <term> with FAQ schema and add it to the sitemap

The full SKILL.md

93 lines · 8 KB · raw file

---
name: trend-landing-page
description: Build an answer-first, fully sourced landing page for a brand-new search term (a just-announced or rumored model, product, feature or event) before competitors do. Researches official and reputable news sources, separates confirmed facts from reports and rumors, writes the page with a sourced FAQ plus NewsArticle, FAQPage and BreadcrumbList JSON-LD, adds internal links and updates the sitemap and llms.txt. Use when the user names a new keyword, trend, leak or launch to cover.
---

# Trend landing page

Turn a fresh keyword (e.g. "Gemini 4 Carbon", "GPT-6 Astra pricing", "<product> shutdown") into a page that ranks and gets cited by AI answer engines **because it is the most accurate page on the topic** — not the loudest.

Real case: https://getaicodingagent.com/models/gemini-4-carbon was produced with this workflow within ~2 days of the Business Insider report. It clearly labels the model as *reported, unconfirmed*, quotes only what the report says, and keeps viral X claims ("beats Opus 5.5 and GPT-6 Astra") out because no source supports them. Docs: https://getaicodingagent.com/skills/trend-landing-page/

## Inputs

- **Term** (exact spelling people search) and 2–4 variants ("<term> release date", "<term> vs <rival>", "<term> pricing", "what is <term>").
- **Site repo** and how pages are generated (data file + template, MDX, CMS, Next.js route). Find the existing pattern for article/news pages and reuse it.
- **Production origin** for canonicals/JSON-LD.

## Step 1 — Research (do not write yet)

1. Search the term plus "announce", "blog", "docs", "pricing", "release date". Use the current year in queries.
2. Collect sources in tiers and **open each one** (never cite a search snippet):
   - **Tier 1 — official**: vendor blog, docs, changelog, pricing page, status page, SEC filing, official X/GitHub account.
   - **Tier 2 — reputable reporting**: Reuters, Bloomberg, The Verge, Business Insider, TechCrunch, The Information, Ars Technica, established trade press — with author and date.
   - **Tier 3 — secondary/social**: blogs, aggregators, X/Reddit posts, leakers. Use only to describe *that a claim circulates*, never as proof.
3. For each source record: URL, publisher, author, publish date, and the exact claims it supports (short quotes ≤ 25 words).
4. Check whether the vendor has commented ("declined to comment" is a fact worth stating).
5. If nothing Tier 1/Tier 2 exists, stop and tell the user the term is not page-worthy yet (or offer a short "what we know" stub explicitly marked unconfirmed).

## Step 2 — Fact ledger

Write a ledger before drafting:

| Claim | Status | Source(s) |
|---|---|---|
| … | CONFIRMED (official) / REPORTED (Tier 2, named outlet) / RUMORED (Tier 3 only) / FALSE-OR-UNSUPPORTED | URL(s) |

Rules: a claim is CONFIRMED only with a Tier 1 source. Numbers (prices, benchmarks, dates, context windows) need a source each. A claim that appears only on social media is RUMORED and must be written as "Posts on X claim … ; no report we could verify supports this." Unknowns go in a "What we don't know" list — that list is often what searchers want.

## Step 3 — Page structure

Title ≤ 60 chars with the term first and the top intent: `<Term>: Release Date, <Rival> Comparison & What We Know`. Meta description 140–160 chars with the one-sentence answer. URL: short, lowercase, hyphenated slug of the term.

1. **H1**: `<Term>: what we know so far` (or "explained"/"pricing" matching intent).
2. **Answer-first paragraph** (2–3 sentences): what it is, its status (released / announced / reported / rumored), the key date and source — e.g. "**X is not a released model.** It is … according to a <Outlet> report by <Author> published <date>. <Vendor> declined to comment."
3. "Last updated <date> · Status: <status>" line, plus a visible notice box if unconfirmed.
4. **What was reported / announced** — bullet list straight from the ledger, each bullet attributable.
5. **What we know / what we don't know** — two columns or lists.
6. Intent sections as H2s: release date, pricing, vs <rival>, availability ("Can I use it in <tool>?"). Answer each in the first sentence, then context. Say "none announced" rather than speculating.
7. **What it means for <your audience>** — the original, useful part: which products are affected, what to do now ("don't switch tools on a rumor").
8. **Sources** — numbered list, publisher + title + date, linked.
9. **FAQ** — 4–6 questions phrased as people search them; answers 1–3 sentences, consistent with the body.

## Step 4 — Structured data (JSON-LD)

Add three blocks (valid JSON, content must match visible text):

```json
{"@context":"https://schema.org","@type":"NewsArticle","headline":"<title>","description":"<meta description>",
 "datePublished":"YYYY-MM-DD","dateModified":"YYYY-MM-DD","mainEntityOfPage":"<canonical URL>",
 "author":{"@type":"Organization","name":"<Site>","url":"<origin>/"},
 "publisher":{"@type":"Organization","name":"<Site>","url":"<origin>/"},
 "about":[{"@type":"Thing","name":"<Term>"}],"citation":["<source URL 1>","<source URL 2>"]}
```

plus a `FAQPage` (`mainEntity` = the visible FAQ, `Question.name` + `acceptedAnswer.text`) and a `BreadcrumbList` (Home → section → page). Use `Article` instead of `NewsArticle` for evergreen explainers.

## Step 5 — Wire it into the site

- Implement through the site's generator/data (never hand-edit generated HTML).
- Internal links **to** the new page from: the home/news feed item, the hub or category page, and every existing page about related entities (e.g. each tool that could use the model). Descriptive anchors ("Gemini 4 Carbon explainer"), not "click here".
- Internal links **from** the new page to your relevant evergreen pages (comparisons, directories).
- Add to `sitemap.xml` (with `lastmod`), to `llms.txt` (one line: `- [<Term> (reported, unconfirmed)](<url>): <description>`), and to any news JSON/RSS feed.
- Build, then validate: one H1, unique title, valid JSON-LD (`python3 -c 'import json,sys;…'` or the `seo-preflight` skill), no broken links.

## Step 6 — Ship and notify

Deploy, check the URL returns 200, resubmit the sitemap in Search Console, and ping IndexNow for the new URL if the site has a key. Then record a **re-check trigger** in the project notes: what event would change the page (official announcement, pricing page live, benchmark published) and when to check again (24–72 h for hot terms).

## Output to the user

```
New page: <URL>  (status: <confirmed/reported/rumored>)
Title / description: …
Sources used: <n> (Tier1 <a>, Tier2 <b>); claims excluded as unsupported: <list>
Linked from: <pages>; sitemap + llms.txt updated; IndexNow: <status>
Re-check: <trigger> by <date>
```

## Guardrails

- Never state rumors as facts, invent dates/prices/benchmarks, or quote more than ~25 words from any source.
- Prefer "reportedly", "according to <Outlet>", "<Vendor> has not confirmed".
- When the vendor later confirms or denies, update the page (status, dateModified, ledger) the same day — that update is what keeps it ranking.

FAQ

What does the trend landing page skill produce?
A complete, sourced page for a new search term: answer-first intro, what was reported, what we know and don't know, intent sections such as release date and pricing, a sources list and an FAQ, plus NewsArticle, FAQPage and BreadcrumbList JSON-LD, internal links and sitemap/llms.txt entries.
How does it avoid publishing rumors as facts?
Before writing, the agent builds a fact ledger and labels each claim CONFIRMED (official source), REPORTED (named reputable outlet), RUMORED (social only) or UNSUPPORTED. Only confirmed claims are stated as fact; reports are attributed; unsupported claims are excluded or explicitly debunked.
Does it work with my site generator?
Yes. The skill tells the agent to find the site's existing article pattern — a data file and template, MDX, a CMS or a Next.js route — and implement the page there rather than hand-editing generated HTML.
Can I use it in Codex and Cursor, not only Claude Code?
Yes. It is a standard SKILL.md with name and description frontmatter, which Claude Code, OpenAI Codex and Cursor all load from their skills folders.

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