seo-keyword-research

SkillFiles & storage

Discovers, scores, and clusters keywords for SEO and GEO planning.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the seo-keyword-research skill

About this capability

A curated guide to convention files AI agents read, write, and act on: AGENTS.md, CLAUDE.md, SKILL.md, llms.txt, MCP configs, rules, and examples.

What this skill tells your AI

The instructions your AI receives, as published by itamarzand88/awesome-agent-conventions in conventions/skill-md/examples/content-comms/seo-keyword-research/SKILL.md and read by ahel’s review.


name: keyword-research description: 'Use when the user asks to "find keywords", "挖词", or "搜什么词"; prioritizes search volume, keyword difficulty, intent, and topic clusters from provided or connected data. Not for competitor-relative coverage gaps — use content-gap-analysis. 关键词研究/内容选题' version: "9.9.10" license: Apache-2.0 compatibility: "Claude Code and compatible agent-skill hosts" homepage: "https://github.com/aaron-he-zhu/seo-geo-claude-skills" when_to_use: "Use when starting keyword research for a new page, topic, or campaign. Also when the user asks about search volume, keyword difficulty, topic clusters, long-tail keywords, what to write about, 关键词研究, 挖词, 内容选题, or 搜什么词." argument-hint: " [market/language]" metadata: author: aaron-he-zhu version: "9.9.10" geo-relevance: "medium" tags: - seo - geo - keyword-research - search-volume - keyword-difficulty - topic-clusters - search-intent - long-tail-keywords - 关键词研究 - SEO关键词 - キーワード調査 - 키워드분석 - palabras-clave triggers: - "keyword research" - "search volume analysis" - "what should I write about" - "give me keyword ideas" - "how competitive is this keyword" - "Ahrefs keyword explorer alternative" - "Google Keyword Planner alternative" - "关键词分析" - "长尾关键词" - "帮我挖词"

Keyword Research

Discovers, scores, and clusters keywords for SEO and GEO planning.

Quick Start

Research keywords for [topic/product/service]
What keywords is [competitor URL] ranking for that I should target?

Skill Contract

Expected output: a prioritized keyword brief plus the standard handoff summary for memory/research/.

  • Reads: topic or seed keyword, target market/language, business goal, site DR, and any user-provided or tool metrics.
  • Writes: a user-facing research deliverable and reusable summary.
  • Promotes: durable keyword priorities, competitor facts, and pending strategy decisions to memory/hot-cache.md, memory/open-loops.md, and memory/research/.
  • Done when: every shortlisted keyword carries volume + difficulty + intent (or a labeled N/A); keywords are grouped into pillar + cluster hubs; and the deliverable names at least 3 prioritized Quick Win / Growth / GEO opportunities.
  • Primary next skill: competitor-analysis when the keyword set is ready for market comparison.

Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

Data Sources

Optional integrations: ~~SEO tool, ~~search console. Without tools, ask for seed keywords, audience, goals, and any known metrics. See CONNECTORS.md.

Zero-dependency local helper (no tool needed): python3 scripts/connectors/suggest.py "<seed>" --expand harvests free keyword ideas from Google Autocomplete (⚠️ unofficial endpoint). Search volume / difficulty still needs ~~SEO tool or own Search Console data. See scripts/connectors/README.md.

Instructions

When a user requests keyword research, run eight phases and announce each as [Phase X/8: Name]:

  1. Scope — clarify product, audience, business goal, DR, geography, and language.
  2. Discover — seed from core, problem, solution, audience, and industry terms.
  3. Variations — expand with modifiers and long-tail patterns.
  4. Classify — tag by intent (informational, navigational, commercial, transactional).
  5. Score — assign difficulty (1-100) and compute Opportunity = (Volume × Intent Value) / Difficulty, with Intent Value 1 / 1 / 2 / 3.
  6. GEO-Check — flag AI-answer-friendly queries such as questions, definitions, comparisons, lists, and how-tos.
  7. Cluster — group keywords into pillar + cluster topic hubs.
  8. Deliver — output an Executive Summary, Quick Wins / Growth / GEO opportunities, Topic Clusters, Content Calendar, and Next Steps.

Label every metric Measured (tool/export), User-provided, or Estimated (model inference); never present an estimate as measured; if a required metric is unavailable, mark it N/A — do not invent it.

Quality bar: every recommendation includes at least one specific number. Rewrite generic advice into a concrete keyword + volume + difficulty + reason.

Reference: See references/instructions-detail.md for the full 8-phase templates, expansion patterns, intent table, difficulty tiers, opportunity matrix, GEO indicators, cluster template, actionable-vs-generic examples, and advanced usage.

Example

Example outcome: 150+ keywords analyzed, 23 high-priority opportunities, ~45K/month traffic potential across 3 focus areas. See the full sample in references/example-report.md.

Advanced Usage

Intent mapping, seasonal analysis, competitor gaps, and local keyword workflows live in references/instructions-detail.md.

Tips for Success

Start with seeds, respect intent, cluster tightly, prioritize quick wins, and review quarterly. Full notes live in references/instructions-detail.md.

Save Results

Write path: memory/research/keyword-research/YYYY-MM-DD-<topic>.md; promote durable keyword priorities to memory/hot-cache.md. See Skill Contract §Save Results Template.

Reference Materials

Next Best Skill

Primary: competitor-analysis. Also: content-gap-analysis and serp-analysis.

Signals

GitHub stars
31
Forks
3
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
seo-keyword-research
Source
github.com/itamarzand88/awesome-agent-conventions