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Skills/every-app/open-seo/competitive-landscape
competitive-landscape logo

competitive-landscape

every-app/open-seo
777 installs7K stars
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Installation

npx skills add https://github.com/every-app/open-seo --skill competitive-landscape

Summary

Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps.

SKILL.md

OpenSEO Competitive Landscape

Goal

Answer: "Who is winning this SEO market, what content is working for them, and where are the openings?"

Use this when the user wants a market-level view across several competitors. For a deep dive on one domain, use competitor-analysis.

Required inputs

  • projectId
  • Topic, seed keywords, market/category, or user's domain
  • Optional known competitors
  • Optional location/language

OpenSEO MCP tools

  • research_keywords: discover representative market queries.
  • get_keyword_metrics: validate known query sets with volume, difficulty, intent, and trends.
  • get_serp_results: identify recurring ranking domains across target queries.
  • find_serp_competitors: compare domains competing across supplied keywords; use this before manual SERP counting when a keyword set is available.
  • get_domain_overview: size organic footprint for candidate leaders.
  • get_search_console_performance: when the user's own domain is in the comparison and Search Console is connected, anchor their position with first-party clicks/impressions/CTR rather than third-party estimates.
  • get_ranked_keywords: find exact ranking keywords, URLs, ranks, intents, and SERP result types for leaders.
  • get_backlinks_overview: compare backlink/referring-domain strength where relevant.
  • search_local_businesses, get_local_serp_results, and get_google_business_questions: use for local SEO markets where proximity, Maps rankings, business categories, reviews, or Google Q&A affect who is winning.

Workflow

  1. Define the market query set:
  • Use provided keywords, or call research_keywords to build 5-10 representative queries.
  • Include mixed intent: informational, commercial, comparison, and tool/software terms when applicable.
  • For local SEO, include neighborhood/city/service-area queries and identify the priority locations or coordinates.
  1. If the query set is already known, use get_keyword_metrics to validate relative demand and difficulty and find_serp_competitors to identify recurring domains at scale.
  2. For local SEO, call search_local_businesses and get_local_serp_results for the highest-priority location(s) before synthesizing winners. Use get_serp_results as a complement for organic pages, not as the only local evidence.
  3. Call get_serp_results for representative queries when live SERP composition, ranking URLs, or SERP features need inspection. Send at most 10 queries per call.
  4. Identify recurring domains and group them by type:
  • Direct product competitors
  • Publishers/media
  • Marketplaces/directories
  • Communities/forums
  • Documentation/resources
  1. For the strongest recurring domains, call get_domain_overview; default to the top 3-5 domains before expanding.
  2. For direct competitors and relevant publishers, call get_ranked_keywords.
  3. Use get_backlinks_overview when backlink authority appears important or the user asks why a domain is winning. Backlinks may be unavailable if the account has not enabled that data; continue with SERP/domain evidence if it fails.
  4. Synthesize patterns: content types, themes, SERP formats, local-pack signals, authority advantages, and underserved angles.

Output format

Start with the market read:

  • Market leaders
  • Most winnable opportunity area
  • Biggest barrier to ranking

Then include:

DomainTypeWhy they matterOrganic footprintWinning themesWeakness/gap

Add:

  • Query set used
  • Content formats that are working
  • Keyword/theme gaps
  • Backlink or authority observations
  • Recommended next workflows: competitor analysis, keyword clustering, or content brief

Guardrails

  • Distinguish SEO competitors from business competitors.
  • Do not overstate exact traffic when OpenSEO returns estimates.
  • If using a small query set, call the result directional.
  • Do not assume a publisher is a product competitor; label domain types clearly.
  • For local markets, distinguish organic-page winners from Maps/local-pack winners.

Score

0–100
65/ 100

Grade

C

Popularity17/30

777 installs — growing adoption. Source repo has 7,095 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Competitive Landscape skill score badge previewScore badge

Markdown

[![Competitive Landscape skill](https://www.remoteopenclaw.com/skills/every-app/open-seo/competitive-landscape/badges/score.svg)](https://www.remoteopenclaw.com/skills/every-app/open-seo/competitive-landscape)

HTML

<a href="https://www.remoteopenclaw.com/skills/every-app/open-seo/competitive-landscape"><img src="https://www.remoteopenclaw.com/skills/every-app/open-seo/competitive-landscape/badges/score.svg" alt="Competitive Landscape skill"/></a>

Competitive Landscape FAQ

How do I install the Competitive Landscape skill?

Run “npx skills add https://github.com/every-app/open-seo --skill competitive-landscape” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Competitive Landscape skill do?

Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Competitive Landscape skill free?

Yes. Competitive Landscape is a free, open-source skill published from every-app/open-seo. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Competitive Landscape work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Competitive Landscape works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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