OpenSEO competitor analysis

01What is it?
Analyze one competitor's organic footprint, ranking keywords, content themes, backlinks, and gaps. Its edge is a particular angle on search and SEO workflows, giving the agent tighter constraints than a plain OpenSEO competitor analysis request.
02Inputs
Context for search and SEO workflows: your goals, audience, constraints, and any source material the skill asks for.
03Output
A ready-to-use result for search and SEO workflows: the analysis, copy, or recommendations the agent produces.
Paste-ready

Install as a package

Installs this one skill package for your coding agent, including any supporting files that skill ships with — not every skill in the repository. Read the tutorial.

Terminal
$ npx skills add every-app/open-seo --skill competitor-analysis

Use in Profound

Copy this file into a new Profound Skill. That's it, nothing else to install.

Copy and create in Profound
SKILL.md

OpenSEO Competitor Analysis

Goal

Analyze one competitor deeply enough to decide what to learn from, avoid, counter-position against, or outrank.

Use this for a named competitor. For identifying the market leaders first, use competitive-landscape.

Required inputs

  • projectId
  • Competitor domain
  • User's domain when comparison is requested
  • Optional topic/category/location/language

Project context

The project-context tools are free and shared with the app and other agents.

  1. Call get_project_context first and ground the analysis in it — the saved competitors say whether this domain is already known and what was concluded about it before.
  2. This skill needs competitors. If none are saved, run a minimal inline setup: save the competitor being analyzed, and ask the user (or infer from find_serp_competitors and confirm) whether there are others, write them back with update_project_context (addCompetitors), then continue the analysis. Never front-load the full interview; suggest seo-project-setup at the end for the rest.
  3. Before spending credits, check the research log. If the same research ran within the last 30 days, reuse that result and say so instead of re-buying it.
  4. On finish, write back what is durable with update_project_context — an addCompetitors upsert for this domain with a short note on its strengths and where it is vulnerable — and append a research log entry: { appendResearchLog: { summary: "Competitor analysis: <domain>. Verdict: <conclusion>" } }.

OpenSEO MCP tools

  • get_domain_overview: baseline organic traffic and keyword count.
  • get_search_console_performance: when comparing to the user's own domain and Search Console is connected, use it as the first-party baseline (real clicks/impressions/CTR/position) instead of estimating the user's own performance from third-party data.
  • get_ranked_keywords: exact keyword, URL, rank, intent, traffic, CPC, and SERP-type rows for the competitor domain or page.
  • get_backlinks_overview: backlink/referring-domain profile.
  • find_serp_competitors: validate whether the named competitor is a real search competitor across the target keyword set.
  • search_local_businesses, get_local_serp_results, and get_google_business_questions: use for local SEO competitors when Maps/local-pack visibility, nearby businesses, categories, or Google Q&A matter.
  • get_serp_results: validate direct head-to-head SERPs for important keywords.
  • research_keywords: expand gaps or category terms when needed.

Workflow

  1. Call get_domain_overview for the competitor, passing provided location/language when supported.
  2. If comparing to the user, call get_domain_overview for the user's domain too — and if Search Console is connected, get_search_console_performance for the user's real baseline.
  3. Call get_ranked_keywords for the competitor. Use filters like maxRank, minSearchVolume, excludeBrandTerms, and resultTypes to keep rows relevant.
  4. If comparing to the user, call get_ranked_keywords for the user's domain/page too, or use get_serp_results for the shared terms when a lighter check is enough.
  5. For local SEO, use search_local_businesses and get_local_serp_results around the relevant business location(s) before drawing local-pack conclusions. Add get_google_business_questions only when Q&A evidence matters.
  6. Use find_serp_competitors when the competitor was supplied by the user but its search overlap is unclear.
  7. Group competitor keywords into themes:
    • Product/category terms
    • Alternatives/comparisons
    • Templates/tools/calculators
    • Educational guides
    • Branded demand
    • Local/neighborhood terms when relevant
  8. Call get_backlinks_overview for the competitor, especially if authority appears to explain rankings. Continue without backlink evidence if it is unavailable.
  9. Use get_serp_results for important shared or target keywords to compare positioning, passing provided location/language when supported.
  10. Produce an actionable plan:
    • What they are doing well
    • Where they are vulnerable
    • Which pages/keywords to pursue
    • What to avoid copying

Output format

Start with:

  • Competitor snapshot
  • Biggest lesson
  • Best opportunity to beat them

Then include:

AreaCompetitor patternEvidenceOpenSEO opportunity

Include sections for:

  • Top keyword themes
  • Content/page types working for them
  • Backlink/authority notes
  • Head-to-head SERP observations
  • Priority actions for the user

Guardrails

  • Do not treat all competitor keywords as desirable. Filter for business fit.
  • Separate evidence from inference.
  • Do not infer competitor page/content-type patterns from keyword rows alone; use SERP or web evidence for page-level claims.
  • For local SEO, do not infer Maps/local-pack strength from national organic domain metrics alone; use local business and local SERP tools when the location is known or reasonably discoverable.
  • Do not recommend copying content; recommend a stronger angle or better answer to the same intent.
  • If the user's domain is unavailable, frame the analysis as competitor-only.

How do I install OpenSEO competitor analysis in Cursor, Claude Code, or Codex?

Run npx skills add every-app/open-seo --skill competitor-analysis in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only OpenSEO competitor analysis, not every skill in the repository.

Where does OpenSEO competitor analysis come from and what license is it under?

OpenSEO competitor analysis comes from the every-app/open-seo repository on GitHub. That repository has 13.5K GitHub stars. The skill is published under the MIT license.

Prefer plain text? Read the OpenSEO competitor analysis guide as markdown.