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Seo competitor pages

Skill amirjahfar1/automate-seo-with-claude/skills/seo-competitor-pages

26 production-ready Claude SEO skills powered by the DataForSEO MCP, with Google Search Console & GA4 — keyword research, technical audits, backlinks, AI search (GEO), content briefs, competitor & SERP analysis. By NextBrainSolutions.

Install
npx -y skills add amirjahfar1/automate-seo-with-claude --skill seo-competitor-pages

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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".

SKILL.md

9.5 KB, as published. Nobody here has run it

Example output: 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

  • DataForSEO 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 mcp__dataforseo__dataforseo_labs_google_competitors_domain

    • 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 mcp__dataforseo__dataforseo_labs_google_ranked_keywords

    • 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 mcp__dataforseo__serp_organic_live_advanced (and mcp__dataforseo__dataforseo_labs_google_keyword_ideas filtered for interrogatives, for question mining)

    • 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 @types, 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.
  1. Pull keyword comparison data mcp__dataforseo__dataforseo_labs_google_domain_intersection (if available for the brands)

    • Side-by-side keyword overlap.
  2. 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 DataForSEO data informs a cell (e.g., "ranks for X enterprise keywords"), pull the number.
  3. 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       (only if --bulk-scrape ran: competitor URL × on-page-element grid)
└── evidence/
    ├── 01-competitor-context.md      (dataforseo_labs_google_competitors_domain — raw step output)
    ├── 02-keyword-overlap.md         (dataforseo_labs_google_ranked_keywords for each brand — raw step output)
    ├── 03-comparative-serp.md        (top 10 + PAA for the target keyword — raw step output)
    └── 04-existing-pages-teardown.md (top-3 SERP winners' structure + schema/og — Firecrawl-recovered)

Top-level: COMPARISON.md + 05-feature-matrix.md + schema.jsonld. The 01–04 step files preserve raw API/scrape outputs in evidence/. 05b-competitor-elements.csv only appears when --bulk-scrape was passed.

COMPARISON.md for an "X vs Y" page follows this shape:

# {User's Brand} vs {Competitor}: 2026 Comparison

> Updated {YYYY-MM-DD}. Compare {Brand A} and {Brand B} on pricing, features, integrations, and best-fit use case.

## TL;DR
{One paragraph balanced verdict — when to choose A, when to choose B}

## At a glance

| Dimension | {Brand A} | {Brand B} |
|---|---|---|
| Starting price | {$X/mo} | {$Y/mo} |
| Free tier | {✓/✗} | {✓/✗} |
| Best for | {use case} | {use case} |
| Integrations | {n} | {n} |
| Support | {tier} | {tier} |
| ... | | |

## {Dimension 1 header — e.g., Pricing}
{Side-by-side detail, balanced. Avoid hyperbole.}

## {Dimension 2 header — e.g., Features}
{...}

## {Dimension 3 header — e.g., Integrations}
{...}

## {Dimension 4 header — e.g., Support}
{...}

## When to choose {Brand A}
- {scenario 1}
- {scenario 2}
- {scenario 3}

## When to choose {Brand B}
- {scenario 1}
- {scenario 2}
- {scenario 3}

## FAQ
**{PAA question 1}**
{Answer}

**{PAA question 2}**
{Answer}

**{PAA question 3}**
{Answer}

## Get started
{Brand A} CTA — {link}
{Brand B} CTA — {link if balanced; otherwise drop}

## Schema
See `schema.jsonld` — paste into `<head>`.

Tips

  • Balance is conversion. Pages that pretend the user's product is always better lose trust and rankings. Honest assessments outperform partisan ones.
  • DataForSEO allows up to 2,000 calls/min, 30 concurrent. Skills pace sequentially. Step 5 (fetching top 3 SERP winners) takes 3 WebFetch calls + earlier MCP queries.
  • Cost: DataForSEO bills per call; this run issues a handful of Labs + SERP calls. Use limit/filters to cap. +3 Firecrawl credits for the schema/og benchmark in step 5, +1 Firecrawl credit per URL in step 5b (opt-in only). Pass --no-firecrawl to skip both Firecrawl steps.
  • Schema: use Product for both products in a vs page, plus BreadcrumbList, plus FAQPage if the FAQ section is real Q&A (not a manufactured one).
  • For "alternatives to X" pages, position the user's product as one of N (typically 5–10), not as #1. Numbered listicles convert better than self-promotional alternatives pages.
  • For "best X for Y" pages, segment by use case explicitly — "best for solo developers" vs "best for enterprise teams" — this lets you win multiple long-tail variants.
  • Run seo-page on the published page after 30 days to track ranking trajectory.
  • Pair with seo-content-audit to E-E-A-T-check the draft before publishing.
  • The PAA-derived FAQ in step 4 is gold — those are the questions users are actually searching, and answering them in-page raises citation-readiness for AIO.
  • Don't auto-publish. Hand the draft to a writer/PM for fact-checking and brand-voice tuning.

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