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Agent skill

SEO Competitor Pages

by seranking in seranking/seo-skills

Generate SEO-optimized "X vs Y" comparison and "alternatives to X" landing pages targeting comparative-intent keywords.

MITAuto-check passedMarketing & SEO

Install SEO Competitor Pages

skills CLI
$ npx skills add seranking/seo-skills --skill seo-competitor-pages -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install seranking/seo-skills seo-competitor-pages --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/seranking/seo-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-competitor-pages .claude/skills/seo-competitor-pages && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-competitor-pages
GitHub stars
161
Token cost
~2.3k tokens
SKILL.md length
845 words
Files
1
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

Generate SEO-optimized "X vs Y" comparison and "alternatives to X" landing pages targeting comparative-intent keywords.

  • Works in 3 steps: "X vs Y" head-to-head — direct… → "Alternatives to X" — listicle-format… → "Best X for Y" — segmented best-of page…
  • The user asks for comparison page
  • SKILL.md covers Page types this skill produces, Prerequisites, Process and Output format, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Competitor Pages is an agent skill from seranking/seo-skills. 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".

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Programmatic SEO, Landing pages and Competitor analysis. The repository describes itself as: Claude SEO Skills — production Claude Agent Skills for the SE Ranking MCP server. Content briefs, AI Search share of voice, audits, backlink gaps, keyword clusters, schema… The licence is MIT.

When your agent uses it

  • The user asks for comparison page
  • Alternatives page
  • Alternative to X
  • Competitor comparison page

Example prompts

  • “X vs Y”
  • “alternatives to X”
  • “comparison page”
  • “/seo-competitor-pages”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  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…
  3. "Best X for Y" — segmented best-of page targeting a use case or audience. Target keyword: best [category] for [use case].

What it can do on your machine

Read from SKILL.md and the folder at commit fd6d140. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Competitor Pages loads about 2.3k tokens when it runs. Until then it costs about 131 tokens; SKILL.md has 845 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~131
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from seranking/seo-skills at commit fd6d140, republished under its MIT licence (© seranking). 845 words, ~2,319 tokens.

Download SKILL.mdSave it as .claude/skills/seo-competitor-pages/SKILL.md (or your agent's skills folder).
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

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 @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 DATA_getDomainKeywordsComparison (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 SE Ranking 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).
Show full SKILL.md (247 more words)Show less

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      (DATA_getDomainCompetitors — raw step output)
    ├── 02-keyword-overlap.md         (DATA_getDomainKeywords 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:

markdown
# {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.
  • Respect rate limit. Step 5 (fetching top 3 SERP winners) takes 3 WebFetch calls + earlier MCP queries.
  • Cost: ~15–25 SE Ranking credits typical, +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.

© seranking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/seo-competitor-pages of seranking/seo-skills.

Open the folder on GitHubat commit fd6d140

Compare with similar skills

SEO Competitor Pages next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Competitor Pages compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
SEO Competitor Pages this skillseranking/seo-skills161—~2.3kAutomated safety check: PassMIT
Competitor Alternativesfreekmurze/dotfiles1k24 repos~2kAutomated safety check: PassNone
Competitor Alternativesalirezarezvani/claude-skills28k1 repos~2.8kAutomated safety check: PassMIT
Competitorscoreyhaines31/marketingskills54k—~3kAutomated safety check: PassMIT
Competitor Monitoringamplitude/builder-skills159—~1kAutomated safety check: PassNone
Service Area SEOgarrettjsmith/localseoskills121—~1.8kAutomated safety check: PassMIT

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Categories

Questions about SEO Competitor Pages

What does SEO Competitor Pages do?

Generate SEO-optimized "X vs Y" comparison and "alternatives to X" landing pages targeting comparative-intent keywords. SEO Competitor Pages is an agent skill from seranking/seo-skills. Generate SEO-optimized "X vs Y" comparison and "alternatives to X" landing pages targeting comparative-intent keywords.

When should I use SEO Competitor Pages?

SEO Competitor Pages fits situations like: the user asks for comparison page; alternatives page; alternative to X; competitor comparison page.

How do I install SEO Competitor Pages in Claude Code?

Run `npx skills add seranking/seo-skills --skill seo-competitor-pages -a claude-code`. Or copy the skill folder (skills/seo-competitor-pages in seranking/seo-skills) into .claude/skills/seo-competitor-pages in your project. Claude Code loads it when a task matches its description.

How do I install SEO Competitor Pages in Codex?

Run `npx skills add seranking/seo-skills --skill seo-competitor-pages -a codex`. Or copy the skill folder (skills/seo-competitor-pages in seranking/seo-skills) into .agents/skills/seo-competitor-pages in your project. Codex loads it when a task matches its description.

Can I use SEO Competitor Pages in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seranking/seo-skills --skill seo-competitor-pages -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-competitor-pages, .gemini/skills/seo-competitor-pages, .github/skills/seo-competitor-pages and .opencode/skills/seo-competitor-pages in your project.

What does SEO Competitor Pages need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Competitor Pages is instructions for the agent only.

Does SEO Competitor Pages access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Competitor Pages safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Competitor Pages use?

SEO Competitor Pages is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Competitor Pages use?

About 2.3k tokens (SKILL.md is roughly 9.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SEO Competitor Pages?

Skills that share tags, products or a category with SEO Competitor Pages: Competitor Alternatives (freekmurze/dotfiles, 1k stars), Competitor Alternatives (alirezarezvani/claude-skills, 28k stars), Competitors (coreyhaines31/marketingskills, 54k stars) and Competitor Monitoring (amplitude/builder-skills, 159 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Competitor Pages?

seranking (a GitHub organization) maintains it in seranking/seo-skills, which has 161 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 25, 2026.

Source: seranking/seo-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.