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keyword-research关键词研究

Agent Skill

keyword-research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

94,080

周安装

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GitHub Stars

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下载量

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:keyword-research(关键词研究)
来源仓库:https://github.com/aaron-he-zhu/seo-geo-claude-skills
仓库路径:skills/keyword-research
安装命令:
npx skills add https://github.com/aaron-he-zhu/seo-geo-claude-skills --skill keyword-research
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/aaron-he-zhu/seo-geo-claude-skills --skill keyword-research

简介

通过意图分类、难度评分和 SEO 内容策略的主题聚类来发现高价值关键字。

  • 按搜索意图(信息、商业、交易、导航)对关键字进行分类,并根据数量、难度和商业价值分配机会分数
  • 与 Ahrefs、SEMrush、Google 关键字规划器和 Google Search Console 集成;还接受无需工具访问的站点的手动数据输入
  • 通过支柱页面和集群页面分配以及按优先级评分的内容日历将关键字分组到主题集群中
  • 识别长尾变化、可能触发 AI 响应的 GEO 相关关键字以及新网站或已建立网站的快速获胜机会

SKILL.md

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: goals, market inputs, tool data, and prior strategy from CLAUDE.md and the shared State Model when available.
  • Writes: a user-facing research deliverable and reusable summary.
  • Promotes: durable keyword priorities, competitor facts, and strategy decisions to memory/hot-cache.md, memory/decisions.md, and memory/research/.
  • 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.

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.

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

After delivering, offer to save memory/research/keyword-research/YYYY-MM-DD-<topic>.md and promote durable conclusions to memory/hot-cache.md.

Reference Materials

Next Best Skill

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

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按下载量换算8,823

OpenCode

23.84%
按下载量换算7,858

Antigravity

17.04%
按下载量换算5,616

Gemini CLI

13.16%
按下载量换算4,338

Codex

6.54%
按下载量换算2,156

Cursor

3.15%
按下载量换算1,038

安全审计

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可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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来源信息

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