competitive-landscape
Skill1.2k starsChanged 21 days agoMITView on GitHub
Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps.
We split this skill into the rules it gives an agent
9 rules. 0 are common, 4 are distinctive, and 5 are very specific to this project.
0
Common
Most of the 14 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Use this when the user wants a market-level view across several competitors.
- Very specific: line 36
Use provided keywords, or call research_keywords to build 5-10 representative queries.
- Very specific: line 39
If the query set is already known, use get_keyword_metrics to validate relative demand and difficulty and find_serp_competitors to identify …
- Very specific: line 41
Call get_serp_results for representative queries when live SERP composition, ranking URLs, or SERP features need inspection.
- Very specific: line 50
Use get_backlinks_overview when backlink authority appears important or the user asks why a domain is winning.
- Distinctive: line 55
Start with the market read:
- Distinctive: line 77
Do not overstate exact traffic when OpenSEO returns estimates.
- Distinctive: line 78
If using a small query set, call the result directional.
- Distinctive: line 79
Do not assume a publisher is a product competitor.
“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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, andget_google_business_questions: use for local SEO markets where proximity, Maps rankings, business categories, reviews, or Google Q&A affect who is winning.
Workflow
- Define the market query set:
- Use provided keywords, or call
research_keywordsto 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.
- Use provided keywords, or call
- If the query set is already known, use
get_keyword_metricsto validate relative demand and difficulty andfind_serp_competitorsto identify recurring domains at scale. - For local SEO, call
search_local_businessesandget_local_serp_resultsfor the highest-priority location(s) before synthesizing winners. Useget_serp_resultsas a complement for organic pages, not as the only local evidence. - Call
get_serp_resultsfor representative queries when live SERP composition, ranking URLs, or SERP features need inspection. Send at most 10 queries per call. - Identify recurring domains and group them by type:
- Direct product competitors
- Publishers/media
- Marketplaces/directories
- Communities/forums
- Documentation/resources
- For the strongest recurring domains, call
get_domain_overview; default to the top 3-5 domains before expanding. - For direct competitors and relevant publishers, call
get_ranked_keywords. - Use
get_backlinks_overviewwhen 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. - 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:
| Domain | Type | Why they matter | Organic footprint | Winning themes | Weakness/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.
Trending
More talk lately.thin dataabout the whole repository
Who's talking about jwuthri-cloud/Tracely-ai
The biggest 1 of 1 mention linking to the repository that our crawl found. Each line is their own headline.
Other versions19 projects use a version of this.
Word for word · 4
- Jwuthri/Tracely-ai★ 1.5k100% same
- VladSez/easy-invoice-pdf★ 1.1k100% same
- petera2c/simple-table★ 231100% same
- IsaacBell/ai-marketing-toolkit★ 0100% same
Edited · 5
- every-app/open-seo★ 26k56% same
- kid7st/agenticseo★ 226% same
- ventra-rocket/EchoSEO★ 297% same
- winsley-jeune/harborrank-skills★ 129% same
- ictlondon/kraftskills★ 073% same
Wrote their own version · 10
- sendaifun/solana-new★ 178same name
- didixuxu/didi-skills★ 83same name
- xfstudio/skills★ 9same name
- microsoft/aibast-agents-library★ 8same name
- ai4brands-design/claude-skills★ 2same name
- CodeWithBehnam/cc-docs★ 2same name
- Oceanjackson1/Claude-Skill★ 2same name
- garri333/Skills★ 1same name
- Samueladewole/claude-skills★ 0same name
- Ultimate-Alchemy/claude-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
Used alongsideProjects with it also use local-seo.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
huiferSkilllocal-seo
本地 SEO 分析和优化专家。自动检测项目是否需要本地 SEO,分析 NAP(Name, Address, Phone)一致性、本地关键词优化、Google Business Profile (GBP) 优化和本地结构化数据生成。提供本地商家搜索引擎排名优化建议,包括 NAP 标准化、本地关键词策略、GBP 完整性检查、评论策略、地图嵌入和本地 SEO 审计。
Also in 4 projects that use this
In this repository43 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- canvas-generativeSkill
- castSkill
- compose-graphicsSkill
- compose-motionSkill
- compose-multiplatformSkill
- css-nativeSkill
- design-auditSkill
- desktop-principlesSkill
- framer-motionSkill
- gsap-coreSkill
- gsap-frameworksSkill
- gsap-performanceSkill
- gsap-pluginsSkill
- gsap-reactSkill
- gsap-scrolltriggerSkill
- gsapSkill
- gsap-timelineSkill
- gsap-utilsSkill
- mobile-principlesSkill
- motion-designSkill
- motion-principlesSkill
- paintSkill
- swiftui-graphicsSkill
- swiftui-motionSkill
- threejs-r3fSkill
- ui-ux-pro-maxSkill
- ai-observability-langchain-pythonSkill
- competitor-analysisSkill
- deslopSkill
- keyword-clusteringSkill
- keyword-researchSkill
- link-prospectingSkill
- maintain-greptile-rulesSkill
- merge-readySkill
- openseo-release-notesSkill
- openseo-review-web-contentSkill
- papercutsSkill
- seo-auditSkill
- seo-coachSkill
- seo-project-setupSkill
- simple-issue-descriptionSkill
- tracelySkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

