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petera2cpetera2c/simple-table/.agents/skills/keyword-research/SKILL.md

keyword-research

Skill233 starsChanged 3 months agoMITView on GitHub

Discover keyword opportunities, evaluate metrics and SERPs, and save/tag promising terms.

54 other projects use a version of this, 5 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use app-marketing-context, metadata-optimization and 6 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.
  • 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

  • JwuthriSkill

    openseo-review-web-content

    Write and review content for the OpenSEO website (web/) — blog posts, guides, feature pages, FAQs. Distills the philosophy for on-brand, useful, accurate content. Use whenever adding or editing user-facing prose in web/content or web/src.

    Also in 5 projects that use this

  • JwuthriSkill

    openseo-release-notes

    Cut an OpenSEO release — bump the version, draft user-facing release notes from commits since the last tag, run a review + subagent-verification pass, and open a "release: vX.X.X" PR. Use when the user asks to prepare a release, bump the version, or write release notes.

    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

  • opencueSkill

    serp-analysis

    Use when the user asks to "analyze SERPs"; reviews ranking factors, features, intent, AI Overviews, and snippets. SERP分析/搜索结果

    Also in 6 projects that use this

  • +2 more from Jwuthri

The file

We split this skill into the rules it gives an agent

12 rules. 0 are common, 4 are distinctive, and 8 are very specific to this project.

  • 0

    Common

    Most of the 46 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 8

    Very specific

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

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

    If projectId is missing, use list_projects first.

    line 18
  2. Distinctive:

    If the request is local SEO, identify the business, location/coordinates or service area, and local categories.

    line 34
  3. Very specific:

    Call research_keywords for exploratory seeds.

    line 35
  4. Very specific:

    Use get_keyword_metrics to hydrate a fixed keyword list — or the striking-distance queries from step 1 — with volume, KD, and intent before …

    line 36
  5. Very specific:

    Use get_ranked_keywords when the user provides a domain/page and wants opportunities based on current rankings, near-misses, or …

    line 37
  6. Distinctive:

    Remove irrelevant, duplicate, branded-only, and off-intent terms.

    line 38
  7. Very specific:

    Use get_serp_results for high-potential or ambiguous keywords when SERP intent would change the recommendation.

    line 46
  8. Very specific:

    Ask before saving keywords.

    line 48
  9. Distinctive:

    Start with the highest-signal recommendation:

    line 52
  10. Very specific:

    Do not invent metrics. If OpenSEO does not return a value, write unknown.

    line 68
  11. Very specific:

    Do not call save_keywords without explicit confirmation.

    line 69
  12. Distinctive:

    Prefer business-fit and intent-fit over chasing the largest volume term.

    line 70

“Common” is measured: kept by at least 6 in 10 of the 46 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 Keyword Research

Goal

Turn seed topics into a prioritized keyword opportunity set using OpenSEO MCP data. The output should help the user decide what to target, what to save, and what to research next.

Required inputs

  • projectId
  • One or more seed topics, products, pages, competitors, or audience problems
  • Optional market/location/language

If projectId is missing, use list_projects first. If the target market/location/language is unclear and would materially affect keyword metrics, ask the user; otherwise use the MCP tool defaults.

OpenSEO MCP tools

  • research_keywords: primary discovery tool. Use 1-5 seeds per call and prefer 150 results unless the user asks for exhaustive research.
  • get_keyword_metrics: hydrate up to 700 known keywords with volume, keyword difficulty (KD), search intent, CPC, and monthly trends in one call. Use it to score candidate or known terms — including the Search Console striking-distance queries from step 1.
  • get_ranked_keywords: pull exact ranking keyword rows when a target domain or page is part of the research brief.
  • get_search_console_performance: when Search Console is connected, start from the project's real first-party demand — queries already earning impressions and near-ranking ("striking distance") terms. Request a high rowLimit and filter average position 5-20 client-side, since the API sorts by clicks and can't filter by position. Then hydrate those striking-distance queries with get_keyword_metrics to attach difficulty and intent.
  • get_serp_results: inspect SERPs for the top candidate terms, especially when intent is ambiguous.
  • search_local_businesses, get_local_serp_results, and get_google_business_questions: use for local SEO topics when a business/location radius matters.
  • list_saved_keywords: avoid duplicating already-saved work or use existing tags as context.
  • save_keywords: save selected keywords only after explicit user confirmation.

Workflow

  1. Normalize seeds into a small set of distinct research angles. If Search Console is connected for the project, first pull get_search_console_performance (high rowLimit, default lookback), filter to striking-distance positions (~5–20) client-side, and hydrate those queries with get_keyword_metrics to attach KD and intent. That ranked, hydrated list is your fastest opportunity set — work it before broad discovery.
  2. If the request is local SEO, identify the business, location/coordinates or service area, and local categories. Use search_local_businesses and get_local_serp_results for the most important location/keyword set instead of relying only on national keyword/SERP data.
  3. Call research_keywords for exploratory seeds. Use bulk calls when possible.
  4. Use get_keyword_metrics to hydrate a fixed keyword list — or the striking-distance queries from step 1 — with volume, KD, and intent before prioritizing.
  5. Use get_ranked_keywords when the user provides a domain/page and wants opportunities based on current rankings, near-misses, or competitor-owned terms.
  6. Remove irrelevant, duplicate, branded-only, and off-intent terms.
  7. Prioritize by practical opportunity, not volume alone:
    • Strong match to the user's product/page/topic
    • Clear search intent
    • Reasonable difficulty
    • Useful volume/CPC signal
    • SERP where the user can plausibly compete
    • For local SEO, local-pack/Maps visibility and proximity fit
  8. Use get_serp_results for high-potential or ambiguous keywords when SERP intent would change the recommendation; keep the default check small.
  9. Present a shortlist and a longer opportunity table.
  10. Ask before saving keywords. When saving, suggest concise tags such as topic:<topic>, intent:<intent>, or page:<slug>.

Output format

Start with the highest-signal recommendation:

  • Best opportunity theme
  • Top keywords to target now
  • Keywords to save
  • Risks or SERP caveats

Then include a compact table:

KeywordIntentVolumeKDCPCPriorityNotes

End with next actions, including whether to run keyword clustering, create a content brief, or save the chosen keywords.

Guardrails

  • Do not invent metrics. If OpenSEO does not return a value, write unknown.
  • Do not call save_keywords without explicit confirmation.
  • Prefer business-fit and intent-fit over chasing the largest volume term.

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