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UXMagicaiUXMagicai/seosorted-skills/skills/keyword-research/SKILL.md

keyword-research

Skill0 starsChanged 40 days agoMITView on GitHub

Find SEO keywords with real search volume, keyword difficulty, CPC and intent using SEOsorted, and rank them by opportunity (quick win, high, long-term). Use when the user asks for keyword research, keyword ideas, what to write about, search volume, keyword difficulty, low-competition keywords, or wants to grow impressions/traffic with new content.

54 other projects use a version of this.

Adopted by

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Used with

Projects with it also use link-prospecting, seo-project-setup and 9 more.

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.
  • JwuthriSkill

    link-prospecting

    Find link prospects, discover contact paths, and draft outreach from SERPs and backlink signals.

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  • JwuthriSkill

    seo-project-setup

    Set up a durable local SEO workspace with project context, notes, goals, positioning, preferences, MCP checks, and Search Console data intake.

    Also in 11 projects that use this

  • appeekySkill

    app-marketing-context

    When the user wants to create or update their app marketing context document. Also use when the user mentions "app context", "marketing brief", "app positioning", or when starting any ASO or app marketing project. This is the foundation skill — all other skills check for this context first.

    Also in 6 projects that use this

  • appeekySkill

    metadata-optimization

    When the user wants to optimize App Store metadata — title, subtitle, keyword field, or description. Also use when the user mentions "optimize my title", "ASO metadata", "keyword field", "character limits", "app description", or "write my subtitle". For keyword discovery, see keyword-research. For full ASO audits, see aso-audit.

    Also in 6 projects that use this

  • liangdabiaoSkill

    review-analysis

    对亚马逊商品评论进行深度分析，自动识别产品痛点、分析退货原因，生成改进建议和客服回复模板。Invoke when user uses /review-analysis command with a product ASIN.

    Also in 5 projects that use this

  • akii-technologies-ltdSkill

    keyword-clustering

    Cluster and organize keywords into topical groups for SEO. Use when the user asks to "cluster keywords", "group keywords", "organize keywords", "keyword mapping", "topic clusters", "keyword grouping", "build a content plan", "pillar pages", "topical authority", "semantic clustering", or pastes a list of keywords.

    Also in 12 projects that use this

  • +5 more from Jwuthri

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 50 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Before writing anything, run cannibalization-check on the shortlist — keyword similarity is not the same as Google treating two queries as …

    line 27

“Common” is measured: kept by at least 6 in 10 of the 50 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

Keyword research

Steps

  1. get_site_overview for the business, market and what already exists (saved keywords by bucket, articles).
  2. Pick 3–8 seeds from the business: core product terms, problems the customer has, the categories competitors rank for. Ask the user for seeds only if the business is unclear.
  3. research_keywords operation: "ideas" per seed (each call uses one keyword-lookup credit). Collect results.
  4. Filter hard:
    • Drop navigational terms (brand names of others, "login", "near me" for non-local businesses), off-topic matches and anything the business cannot credibly write about.
    • Drop ideas flagged hasArticle — the site already targets them.
    • For regulated topics, drop terms the business must not promote (e.g. controlled substances for a pharmacy).
  5. Rank by opportunity: quick-win (volume ≥ 250 and KD ≤ 29) first, then high, then medium. Use volume ÷ (KD + 5)^1.3 as a tiebreaker inside a bucket.
  6. Merge near-duplicates ("ozempic side effects" / "side effects of ozempic") into one target with secondaries.

Output

A table: keyword, volume, KD, bucket, intent, suggested content type (guide, how-to, comparison, listicle), secondary keywords. Then total monthly volume of the shortlist.

Then

  • Offer to save the shortlist: research_keywords operation: "save" (EDITOR role).
  • Before writing anything, run cannibalization-check on the shortlist — keyword similarity is not the same as Google treating two queries as one.
  • Group into clusters with topic-clusters when there are more than ~15 targets.

Guardrails

Volume and KD come from the tool. Never estimate them. If the provider returns nothing for a seed, say so and try a broader seed.

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