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SKILL verified Apache-2.0 Self-run

Keyword Research

skill-aaron-he-zhu-aaron-marketing-skills-keyword-research · by aaron-he-zhu

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

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Install

$ agentstack add skill-aaron-he-zhu-aaron-marketing-skills-keyword-research

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

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](../competitor-analysis/SKILL.md) when the keyword set is ready for market comparison.

Handoff Summary

> Emit the standard shape from [skill-contract.md §Handoff Summary Format](../../references/skill-contract.md).

Data Sources

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

Zero-dependency local helper (no tool needed): python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/suggest.py" "" --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](../../scripts/connectors/README.md).

Striking-distance shortcut (when ~~search console is connected): before broad discovery, mine your own GSC query data for terms already ranking in positions ~5–20 — page-one tail and page two. These are proven demand a small push can convert, so they are the fastest opportunity set. The Search Analytics API sorts by clicks and has no position filter, so request a high rowLimit and filter the 5–20 window client-side, then attach volume / difficulty / intent to that shortlist. Work this set first; treat its metrics as Measured.

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](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

See [references/example-report.md](references/example-report.md) for a full worked sample.

Save Results

Write path: memory/research/keyword-research/YYYY-MM-DD-.md; promote durable keyword priorities to memory/hot-cache.md. See [Skill Contract](../../references/skill-contract.md) §Save Results Template.

Reference Materials

  • [Instructions Detail](references/instructions-detail.md) — Workflow, scoring, cluster template, advanced usage
  • [Keyword Intent Taxonomy](references/keyword-intent-taxonomy.md) — Intent signals and content mapping
  • [Topic Cluster Templates](references/topic-cluster-templates.md) — Pillar and cluster patterns
  • [Keyword Prioritization Framework](references/keyword-prioritization-framework.md) — Scoring and prioritization rules
  • [Example Report](references/example-report.md) — Worked sample

Next Best Skill

Primary: [competitor-analysis](../competitor-analysis/SKILL.md). Also: [content-gap-analysis](../content-gap-analysis/SKILL.md) and [serp-analysis](../serp-analysis/SKILL.md).

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.