本文へ移動
cccskills
無料GitHub で公開

openseo-competitor-analysis

Deep-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor backlinks", "beat <competitor>", "competitor seo teardown".

インストール方法を見る

含まれるファイル(1)

  • SKILL.md5.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

OpenSEO Competitor Analysis

Analyze one competitor deeply enough to decide what to learn from, avoid, counter-position against, or outrank. Findings merge into brand/competitors.md — mktg's competitor memory that competitive-intel maintains qualitatively and this skill now grounds in measured rows.

On Activation

  1. Readiness + binding: mktg seo status --json --fields readiness,catalog.endpointError,project. not_configured → hand off to competitive-intel (Exa qualitative), labeling metrics unknown. For a ready state, verify live access with the free whoami MCP tool before paid calls.
  2. Brand grounding: read brand/competitors.md + brand/positioning.md (tolerate templates). If the competitor isn't named, ask — never guess the domain.

OpenSEO MCP Tools

  • get_domain_overview: baseline organic traffic + keyword count (both domains when comparing).
  • get_ranked_keywords: exact keyword/URL/rank/intent/traffic rows. Use maxRank, minSearchVolume, excludeBrandTerms, resultTypes filters to keep rows relevant.
  • get_backlinks_overview: backlink/referring-domain profile (may be unavailable — continue without it).
  • get_backlinks_profile: link-level sources, anchors, authority/spam signals, and lost/broken state when the decision needs more than a summary. Preserve target scope and pagination.
  • find_serp_competitors: validate the named competitor actually overlaps in search.
  • get_serp_results: head-to-head SERP checks for the important shared terms.
  • get_search_console_performance: when comparing to the user's domain and GSC is connected, the USER's baseline is first-party — never estimate your own side from third-party data.
  • research_keywords: expand gap terms.

Workflow

  1. get_domain_overview for the competitor (and the user's domain when comparing).
  2. get_ranked_keywords for the competitor with sensible filters; same for the user, or get_serp_results for shared terms when a lighter check suffices.
  3. find_serp_competitors when the supplied competitor's search overlap is unclear.
  4. Group keywords into themes: product/category, alternatives/comparisons, templates/tools, educational guides, branded demand.
  5. get_backlinks_overview when authority appears to explain rankings.
  6. get_serp_results for the important head-to-head terms.
  7. Synthesize the plan: what they do well, where they're vulnerable, which pages/keywords to pursue, what NOT to copy.
  8. Merge into brand/competitors.md (preserve existing sections; date the entry; confirm before overwriting populated competitor entries).
  9. Hand off: competitor-alternatives for "X vs Y" pages, seo-content for gap-driven briefs, openseo-keyword-clustering for page mapping.

Output Format

Start with: snapshot, biggest lesson, best opportunity to beat them. Then:

AreaCompetitor patternEvidenceOpenSEO opportunity

Anti-Patterns

  • Treating every competitor keyword as desirable — because ranking for a term and PROFITING from a term are different things; filter through positioning before anything lands in a plan.
  • Inferring page-level content strategy from keyword rows alone — because a keyword list can't tell you WHY a page works (structure, depth, format). Use SERP/web evidence for page-level claims.
  • Estimating the user's own performance from third-party data when GSC exists — because first-party clicks/impressions/position are free and exact; third-party estimates of your own site are the worst data in the room.
  • Recommending "copy what they do" — because imitation pages lose to the original on authority and freshness. Recommend a stronger angle on the same intent, never a replica.
  • Separating evidence from inference nowhere — because "they rank for X" (evidence) and "their content strategy is Y" (inference) carry different confidence and must read differently in brand/competitors.md.

Close the loop

After writing files, log completion so mktg plan / mktg status count the work (bare mktg run only logs loaded):

mktg run openseo-competitor-analysis --complete --writes <paths written> --result success --json

Adapted from every-app/open-seo .agents/skills/competitor-analysis (MIT). Workflow upstream; mktg brand-memory writes and handoff wiring added here.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Add a new expert to the Remotion experts page

日本語の概要は準備中です。原文の説明を表示しています。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

add-sfx

無料

Add a new sound effect to @remotion/sfx

日本語の概要は準備中です。原文の説明を表示しています。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

Use when setting up a secure email inbox for any AI agent — configuring inbound email via Resend, webhooks, tunneling for local development, and implementing security measures to prevent prompt injection attacks. Also use when someone mentions 'agent email', 'bot inbox', 'receive emails for agent', 'agent webhook', 'email security for AI', 'prompt injection via email', 'inbound email for bot', or wants their AI agent to receive and respond to emails securely.

日本語の概要は準備中です。原文の説明を表示しています。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

ai-seo

無料

Builds, measures, and improves an Answer Engine Optimization program across ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews, and Copilot. Use for AEO, GEO, LLMO, AI search visibility, AI citations, brand mentions, answer-engine monitoring, llms.txt, AI crawler audits, or questions like 'what does AI say about us?' and 'why are competitors cited instead of us?'. Produces a durable evidence report and prioritized gameplan, not a one-shot content checklist.

日本語の概要は準備中です。原文の説明を表示しています。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

Generate Apple App Store screenshot pages as a Next.js app with html-to-image export at required resolutions. Screenshots are advertisements, not documentation — every screenshot sells one idea. Use when building App Store screenshots, generating exportable marketing screenshots for iOS apps, or creating programmatic screenshot generators. Triggers on 'app store screenshots', 'App Store', 'screenshot generator', 'iOS screenshots', 'marketing screenshots', 'phone mockup', 'ASO screenshots', 'app store assets', 'app listing', 'app store page', or 'app preview images'. Also use when someone is about to submit an app and needs store assets, or when they say 'make my app store page look good'. Includes iPhone and iPad mockup components with pre-measured dimensions.

日本語の概要は準備中です。原文の説明を表示しています。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

Build detailed buyer personas and audience profiles from research. Use this skill whenever the user mentions audience, buyer persona, ideal customer, target market, ICP, watering holes, 'who am I selling to', customer research, or audience profile. Also use when content feels unfocused or generic (that's an audience problem), when conversion is low because messaging doesn't resonate, when starting any new project (audience should be first), or when any downstream skill needs audience.md but it doesn't exist yet. Even if the user doesn't explicitly ask for audience research, trigger this if they're writing copy or building a landing page without a clear audience defined. Three approaches: Quick Profile, Persona Build, Community Mining.

日本語の概要は準備中です。原文の説明を表示しています。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

MoizIbnYousaf のスキルをすべて見る

このスキルの問題を報告する