/seo-competitor-pages

name: seo-competitor-pages
description: Generate SEO-optimized "X vs Y" comparison and "alternatives to X" landing pages targeting comparative-intent keywords. Pulls competitor data, comparative-intent SERPs, and existing comparison pages to produce a balanced, structured page draft with feature matrix, schema, and conversion blocks. Distinct from `seo-agency-landing-page` (top-of-funnel demand-gen). Use when the user asks for "comparison page", "vs page", "alternatives page", "X vs Y", "alternative to X", or "competitor comparison page".

> Example output: [examples/seo-competitor-pages-linear-vs-jira-20260514/COMPARISON.md](../../examples/seo-competitor-pages-linear-vs-jira-20260514/COMPARISON.md)

Competitor Comparison & Alternatives Pages

Produce conversion-tuned landing pages targeting comparative-intent keywords ("X vs Y", "alternatives to X", "best X for Y"). The deliverable is a paste-ready page draft with feature matrix, balanced verdict, schema markup, and a CTA flow that converts comparison-stage traffic.

Page types this skill produces

1. **"X vs Y" head-to-head** — direct comparison between two products/services. Target keyword: `[Product A] vs [Product B]`. 2. **"Alternatives to X"** — listicle-format page positioning the user's product as one of N alternatives to a category leader. Target keyword: `[Competitor] alternatives` or `alternatives to [Competitor]`. 3. **"Best X for Y"** — segmented best-of page targeting a use case or audience. Target keyword: `best [category] for [use case]`.

Prerequisites

• SE Ranking MCP server connected.
• Claude's `WebFetch` tool available.
• User provides: (a) the user's brand/product (the page's hero), (b) target competitor(s) — at least one, optionally up to 5 for an alternatives page, (c) page type (auto-detected from the keyword if user doesn't specify), (d) target country (default `us`).

Process

1. **Validate & determine page type**

• From the user's input, detect: vs / alternatives / best-of.
• If page type unclear, ask the user. Don't guess silently.

2. **Pull competitor context** `DATA_getDomainCompetitors`

• For the user's domain, list top organic competitors by `common_keywords` overlap.
• Validate that the user's named competitor is in the list (or close).

3. **Pull keyword data per brand** `DATA_getDomainKeywords`

• For the user's domain and each named competitor, pull top 100 organic keywords.
• Identify: keywords each brand owns exclusively, keywords both rank for, gaps.

4. **Pull comparative SERPs** `DATA_getSerpResults` and `DATA_getKeywordQuestions`

• For "X vs Y" / "alternatives to X" / "best X for Y" target keyword(s):
• Top 10 organic results — who else ranks for this comparative keyword?
• PAA questions (these become FAQ section content).
• Featured snippet (if present, capture the answer pattern).

5. **Fetch existing comparison pages** `WebFetch` (always) + `mcp__firecrawl-mcp__firecrawl_scrape` (when available)

• **WebFetch first** (free): pull the top 3 SERP winners' markdown. Extract H2 outline, feature-matrix dimensions, verdict pattern, CTA placement.
• **Firecrawl second** (3 Firecrawl credits — 1 per winner) — recovers what WebFetch markdown can't show:
• Schema types from `<script type="application/ld+json">` blocks (`Product` ×N, `BreadcrumbList`, `FAQPage`, `Review`, `AggregateRating`).
• `og:title` / `og:description` / `og:image` / `twitter:card` from `metadata`.
• `<title>` and meta description lengths from real HTML.
• **If Firecrawl unavailable:** WebFetch portion runs unchanged. The "schema types" line in `evidence/04-existing-pages-teardown.md` reads `(skipped — Firecrawl required for JSON-LD)`. Schema generation in step 8 falls back to a default `Product + BreadcrumbList + FAQPage` template instead of mirroring whatever the winners use.
• This anchors the draft in observed-rewarded-pattern.

5b. **Bulk competitor scrape** `mcp__firecrawl-mcp__firecrawl_scrape` (optional, opt-in)

• When user passes `--bulk-scrape <urls>` or supplies a list of competitor URLs to compare directly (beyond the SERP top-3), Firecrawl-scrape each URL.
• For each URL, extract: `<title>`, `og:*`, `twitter:*`, JSON-LD `@type`s, hero-image presence, pricing-block detection (regex on prose for `$N/mo`, `€N/mo`, etc.), CTA count, comparison-table presence, free-tier-mention boolean.
• Output `competitor-elements.csv` — one row per competitor URL × these signals.
• Cost: 1 Firecrawl credit per URL. Surface estimate before running; refuse >50 URLs without `--confirm-cost`.

6. **Pull keyword comparison data** `DATA_getDomainKeywordsComparison` (if available for the brands)

• Side-by-side keyword overlap.

7. **Build feature matrix**

• Dimensions inferred from the top SERP winners (e.g., "Pricing", "Free tier", "Integrations", "Support tiers", "Best for").
• Cells: ✓ / ✗ / partial / "TBD — confirm with PM" placeholders for fields you can't auto-infer.
• Where SE Ranking data informs a cell (e.g., "ranks for X enterprise keywords"), pull the number.

8. **Synthesise** `COMPARISON.md`

• Hero (target keyword in H1, balanced positioning).
• TL;DR / verdict box in first 200 words.
• Feature matrix.
• Section per major dimension (each H2 = one dimension).
• PAA-derived FAQ (top 3–5 questions from step 4).
• Verdict / recommendation.
• CTA flow.
• Schema-ready JSON-LD: `Product` (×N) + `BreadcrumbList` + `FAQPage` (if real Q&A).

Output format

Create a folder `seo-competitor-pages-{target-slug}-{YYYYMMDD}/` with:

seo-competitor-pages-{target-slug}-{YYYYMMDD}/
├── COMPARISON.md                     (the page draft — primary deliverable)
├── 05-feature-matrix.md              (inferred dimensions × brands — load-bearing reference for PMs/writers)
├── schema.jsonld                     (paste-ready Product + Breadcrumb + FAQ — load-bearing artefact for engineering)
├── 05b-competitor-elements.csv