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jwuthri-cloudjwuthri-cloud/Tracely-ai/.claude/skills/competitive-landscape/SKILL.md

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
  1. Very specific:

    Use this when the user wants a market-level view across several competitors.

    line 12
  2. Very specific:

    Use provided keywords, or call research_keywords to build 5-10 representative queries.

    line 36
  3. Very specific:

    If the query set is already known, use get_keyword_metrics to validate relative demand and difficulty and find_serp_competitors to identify …

    line 39
  4. Very specific:

    Call get_serp_results for representative queries when live SERP composition, ranking URLs, or SERP features need inspection.

    line 41
  5. Very specific:

    Use get_backlinks_overview when backlink authority appears important or the user asks why a domain is winning.

    line 50
  6. Distinctive:

    Start with the market read:

    line 55
  7. Distinctive:

    Do not overstate exact traffic when OpenSEO returns estimates.

    line 77
  8. Distinctive:

    If using a small query set, call the result directional.

    line 78
  9. Distinctive:

    Do not assume a publisher is a product competitor.

    line 79

“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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
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.
  2. 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.
  3. 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.
  4. 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.
  5. Identify recurring domains and group them by type:
    • Direct product competitors
    • Publishers/media
    • Marketplaces/directories
    • Communities/forums
    • Documentation/resources
  6. For the strongest recurring domains, call get_domain_overview; default to the top 3-5 domains before expanding.
  7. For direct competitors and relevant publishers, call get_ranked_keywords.
  8. 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.
  9. 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.

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