AGENT SKILLBY EVERY-APP
OpenSEO competitor analysis
AT A GLANCE
OpenSEO competitor analysis is an agent skill for go-to-market. Analyze one competitor's organic footprint, ranking keywords, content themes, backlinks, and gaps. It is published by every-app in the every-app/open-seo GitHub repository (13.5K stars) under the MIT license. Install it with: npx skills add every-app/open-seo --skill competitor-analysis
- SOURCE REPOSITORY
- every-app/open-seo (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 5.1 KB88 LINES
QUICK ANSWER
- WHAT IT IS01
- 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.
- INPUTS02
- Context for search and SEO workflows: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result for search and SEO workflows: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add every-app/open-seo --skill competitor-analysisREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 7
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.
- Call
get_project_contextfirst and ground the analysis in it — the saved competitors say whether this domain is already known and what was concluded about it before. - 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_competitorsand confirm) whether there are others, write them back withupdate_project_context(addCompetitors), then continue the analysis. Never front-load the full interview; suggestseo-project-setupat the end for the rest. - 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.
- On finish, write back what is durable with
update_project_context— anaddCompetitorsupsert 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, andget_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#
- Call
get_domain_overviewfor the competitor, passing provided location/language when supported. - If comparing to the user, call
get_domain_overviewfor the user's domain too — and if Search Console is connected,get_search_console_performancefor the user's real baseline. - Call
get_ranked_keywordsfor the competitor. Use filters likemaxRank,minSearchVolume,excludeBrandTerms, andresultTypesto keep rows relevant. - If comparing to the user, call
get_ranked_keywordsfor the user's domain/page too, or useget_serp_resultsfor the shared terms when a lighter check is enough. - For local SEO, use
search_local_businessesandget_local_serp_resultsaround the relevant business location(s) before drawing local-pack conclusions. Addget_google_business_questionsonly when Q&A evidence matters. - Use
find_serp_competitorswhen the competitor was supplied by the user but its search overlap is unclear. - Group competitor keywords into themes:
- Product/category terms
- Alternatives/comparisons
- Templates/tools/calculators
- Educational guides
- Branded demand
- Local/neighborhood terms when relevant
- Call
get_backlinks_overviewfor the competitor, especially if authority appears to explain rankings. Continue without backlink evidence if it is unavailable. - Use
get_serp_resultsfor important shared or target keywords to compare positioning, passing provided location/language when supported. - 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:
| Area | Competitor pattern | Evidence | OpenSEO 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.
FAQ
07 QUESTIONS
01What is the OpenSEO competitor analysis agent skill?
Analyze one competitor's organic footprint, ranking keywords, content themes, backlinks, and gaps. It is listed under go-to-market in the 100xLab agent skills directory.
02How 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.
03What does the OpenSEO competitor analysis SKILL.md cover?
The SKILL.md includes sections on Goal, Required inputs, Project context, OpenSEO MCP tools, Workflow and Output format. Read the full text on this page or in plain markdown at /resources/agent-skills/every-app-open-seo--competitor-analysis--tfdugk/raw.
04Which agents can use OpenSEO competitor analysis?
OpenSEO competitor analysis installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is OpenSEO competitor analysis under?
The every-app/open-seo repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is OpenSEO competitor analysis free to use?
Reading, copying and installing OpenSEO competitor analysis costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of OpenSEO competitor analysis?
OpenSEO competitor analysis comes from https://github.com/every-app/open-seo, which has 13.5K GitHub stars. The SKILL.md is at https://github.com/every-app/open-seo/blob/HEAD/.agents/skills/competitor-analysis/SKILL.md. The author is every-app.
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ATTRIBUTION
OpenSEO competitor analysis was written by its original authors and is published in every-app/open-seo (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.