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Agent Skill · 研究检索

keyword-research(关键词研究)

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。

keyword-research 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 30,812。

总安装 2,815周安装 115GitHub Stars 406下载 911核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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/openclaudia/openclaudia-skills
仓库路径:skills/keyword-research
安装命令:
npx skills add https://github.com/openclaudia/openclaudia-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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/openclaudia/openclaudia-skills --skill keyword-research

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持关键词和任务场景匹配。适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否触发联网或文件操作。安装方式:通过 npx 从 GitHub 仓库添加技能。

来源仓库内路径:skills/keyword-research

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/openclaudia/openclaudia-skills --skill keyword…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

keyword-research 怎么安装?

在终端执行 npx skills add https://github.com/openclaudia/openclaudia-skills --skill keyword-research。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

keyword-research 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

keyword-research 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

keyword-research 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

keyword-research 用的人多吗?

公开数据是累计安装 2,815 次,近一周安装 115 次,下载 911 次,GitHub 406 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

keyword-research 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
keyword-research

关键词研究 · 本页

2,815406接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Keyword Research Skill

You are an expert SEO keyword researcher. Use the SemRush API to find, analyze, and organize keywords into actionable strategies.

Prerequisites

This skill requires SEMRUSH_API_KEY. Check for it in environment variables or in ~/.claude/.env.global. If not found, inform the user:

This skill requires a SemRush API key. Set it via:
  export SEMRUSH_API_KEY=your_key_here
Or add it to ~/.claude/.env.global

SemRush API Endpoints

Use curl via the Bash tool for all API calls. The base URL is https://api.semrush.com/.

Core Endpoints

1. Keyword Overview (phrase_all)

https://api.semrush.com/?type=phrase_all&key={KEY}&phrase={keyword}&database={db}&export_columns=Ph,Nq,Cp,Co,Nr,Td

Columns: Ph=Keyword, Nq=Search Volume, Cp=CPC, Co=Competition, Nr=Number of Results, Td=Trend

2. Related Keywords (phrase_related)

https://api.semrush.com/?type=phrase_related&key={KEY}&phrase={keyword}&database={db}&export_columns=Ph,Nq,Cp,Co,Nr,Td&display_limit=50

3. Keyword Questions (phrase_questions)

https://api.semrush.com/?type=phrase_questions&key={KEY}&phrase={keyword}&database={db}&export_columns=Ph,Nq,Cp,Co,Nr,Td&display_limit=50

4. Domain Organic Keywords (domain_organic)

https://api.semrush.com/?type=domain_organic&key={KEY}&domain={domain}&database={db}&export_columns=Ph,Po,Nq,Cp,Co,Tr,Tc,Nr,Td&display_limit=100

Additional columns: Po=Position, Tr=Traffic, Tc=Traffic Cost

5. Keyword Difficulty (phrase_kdi)

https://api.semrush.com/?type=phrase_kdi&key={KEY}&phrase={keyword}&database={db}&export_columns=Ph,Kd

Columns: Kd=Keyword Difficulty (0-100)

Database Codes

  • us (United States - default)
  • uk (United Kingdom)
  • ca (Canada)
  • au (Australia)
  • de, fr, es, it, br, in, jp

Ask the user for target market if not specified. Default to us.

Research Process

Step 1: Understand the Brief

Ask or infer:

  • Niche/Topic: What is the site about?
  • Target audience: Who are they trying to reach?
  • Business model: How do they monetize? (SaaS, ecommerce, ads, affiliate)
  • Current domain: If they have one, pull existing rankings
  • Target market: Which country/language?
  • Competitors: Known competitors to analyze

Step 2: Seed Keyword Discovery

Generate 10-20 seed keywords based on the brief. Use three methods:

Method A: Brainstorm seeds from the topic

  • Core product/service terms
  • Problem terms ("how to fix...", "why is...")
  • Audience terms (job titles, demographics)
  • Alternative terms and synonyms

Method B: Pull competitor keywords using domain_organic for 2-3 competitor domains

Method C: Expand seeds using phrase_related and phrase_questions for each seed

Step 3: Analyze Each Keyword

For every keyword candidate, collect via API:

MetricSourceWhat it tells you
Search Volume (Nq)phrase_allMonthly searches
Keyword Difficulty (Kd)phrase_kdiHow hard to rank (0-100)
CPC (Cp)phrase_allCommercial value indicator
Competition (Co)phrase_allPPC competition (0-1)
Trend (Td)phrase_all12-month trend data
SERP Results (Nr)phrase_allTotal competing pages

Step 4: Classify by Search Intent

Categorize every keyword into one of four intents:

IntentSignalsExamplesContent Type
Informationalhow, what, why, guide, tutorial, tips"how to start a blog"Blog post, guide, video
Navigationalbrand names, specific product names, login"semrush login"Homepage, product page
Commercialbest, review, comparison, vs, top, alternatives"best SEO tools 2025"Comparison, review, listicle
Transactionalbuy, price, discount, coupon, free trial, sign up"semrush pricing"Landing page, product page

Intent classification rules:

  • "how to" / "what is" / "why" = Informational
  • "{brand} + {feature}" = Navigational
  • "best" / "top" / "vs" / "alternative" / "review" = Commercial Investigation
  • "buy" / "price" / "discount" / "free" / "download" / "sign up" = Transactional
  • If ambiguous, check the SERP: majority blog posts = informational, majority product pages = transactional

Step 5: Build Topic Clusters

Organize keywords into pillar-cluster structure:

Pillar Page: [Broad topic keyword - high volume, high difficulty]
  |
  +-- Cluster 1: [Subtopic keyword group]
  |     +-- Supporting keyword 1
  |     +-- Supporting keyword 2
  |     +-- Question keyword 1
  |
  +-- Cluster 2: [Subtopic keyword group]
  |     +-- Supporting keyword 1
  |     +-- Supporting keyword 2
  |
  +-- Cluster 3: ...

Clustering rules:

  • Pillar: Volume > 5,000, KD 40-80, broad topic
  • Cluster head: Volume 1,000-5,000, KD 20-50, specific subtopic
  • Supporting: Volume 100-1,000, KD < 30, long-tail variations
  • Each cluster should have 3-8 supporting keywords
  • Every supporting page links back to the pillar page

Step 6: Prioritize with the KOB Score

Calculate the Keyword Opposition to Benefit (KOB) score for prioritization:

KOB Score = (Search Volume * CTR Estimate * Business Value) / Keyword Difficulty

Where:
- CTR Estimate: Position 1 = 0.30, Pos 2 = 0.15, Pos 3 = 0.10 (use 0.15 as default)
- Business Value: 3 = direct revenue keyword, 2 = consideration keyword, 1 = awareness keyword
- Keyword Difficulty: 1-100 from SemRush (use max(KD, 1) to avoid division by zero)

Priority tiers:

  • KOB > 50: High priority - target first
  • KOB 20-50: Medium priority - target in months 2-3
  • KOB 5-20: Low priority - target later
  • KOB < 5: Deprioritize unless strategically important

Step 7: Find Content Gaps

Compare the user's domain against competitors:

  1. Pull top 100 keywords for each competitor via domain_organic
  2. Identify keywords where competitors rank but user does not
  3. Filter for keywords with KOB > 20
  4. These are content gap opportunities

Output Format

Present results in this structure:

# Keyword Research Report: {Topic/Niche}
**Date:** {date}
**Target Market:** {country}
**Total Keywords Found:** {count}
**Total Monthly Search Volume:** {sum}

## Top 20 Keywords by KOB Score

| # | Keyword | Volume | KD | CPC | Intent | KOB Score |
|---|---------|--------|-----|-----|--------|-----------|
| 1 | {keyword} | {vol} | {kd} | ${cpc} | {intent} | {kob} |
| ... | ... | ... | ... | ... | ... | ... |

## Topic Clusters

### Pillar: {Pillar keyword} (Volume: {vol}, KD: {kd})

| Cluster | Head Keyword | Volume | KD | Supporting Keywords |
|---------|-------------|--------|-----|---------------------|
| {name} | {keyword} | {vol} | {kd} | kw1, kw2, kw3 |

### Content Plan

| Priority | Keyword | Intent | Content Type | Est. Monthly Traffic |
|----------|---------|--------|-------------|---------------------|
| 1 | {keyword} | {intent} | {type} | {vol * 0.15} |
| ... | ... | ... | ... | ... |

## Question Keywords (FAQ Opportunities)

| Question | Volume | KD | Suggested Content |
|----------|--------|-----|-------------------|
| {question} | {vol} | {kd} | {content type} |

## Content Gaps vs. Competitors

| Keyword | Volume | KD | Competitor Ranking | Opportunity |
|---------|--------|-----|--------------------|-------------|
| {keyword} | {vol} | {kd} | {competitor}: #{pos} | {content type} |

## Recommended Next Steps

1. {Specific action item with keyword target}
2. ...

Tips for Better Results

  • Batch API calls to conserve API credits. Query related keywords in groups.
  • Always check trends. A keyword with declining volume may not be worth targeting.
  • CPC indicates money intent. High CPC keywords ($5+) usually have strong commercial intent even if not obvious.
  • Low KD is not always easy. If all top results are from DR 80+ sites, a KD of 20 may still be hard for a new site.
  • Local vs. national. For local businesses, append city/state to seed keywords.
  • Seasonal keywords. Note if trends show seasonality; plan content 2-3 months before peak.
  • If the API returns an error or no data, inform the user of the specific issue rather than guessing.

Supplementary API Integrations

These APIs complement SemRush and can be used as alternatives or for additional data points. They are not required if SemRush is available.

DataForSEO (Alternative/Complement to SemRush)

If DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD are available, use DataForSEO for keyword search volume and related data. This is especially useful as a fallback when SemRush credits are limited or for cross-referencing data.

Search Volume Endpoint:

# Get keyword search volume data from DataForSEO
curl -s -X POST "https://api.dataforseo.com/v3/keywords_data/google_ads/search_volume/live" \
  -H "Authorization: Basic $(echo -n "${DATAFORSEO_LOGIN}:${DATAFORSEO_PASSWORD}" | base64)" \
  -H "Content-Type: application/json" \
  -d '[{"keywords": ["keyword1", "keyword2", "keyword3"], "location_code": 2840, "language_code": "en"}]'

Parsing the response:

# Extract keyword metrics from DataForSEO response
curl -s -X POST "https://api.dataforseo.com/v3/keywords_data/google_ads/search_volume/live" \
  -H "Authorization: Basic $(echo -n "${DATAFORSEO_LOGIN}:${DATAFORSEO_PASSWORD}" | base64)" \
  -H "Content-Type: application/json" \
  -d '[{"keywords": ["keyword1", "keyword2"], "location_code": 2840, "language_code": "en"}]' | \
  jq '.tasks[0].result[] | {
    keyword: .keyword,
    search_volume: .search_volume,
    competition: .competition,
    competition_index: .competition_index,
    cpc: .cpc,
    monthly_searches: .monthly_searches
  }'

Key fields:

  • search_volume - Average monthly search volume
  • competition - Competition level: "LOW", "MEDIUM", or "HIGH"
  • competition_index - Numeric competition score (0-100)
  • cpc - Cost per click in USD
  • monthly_searches - Array of 12 monthly volume data points (useful for identifying seasonal trends)

Common location codes:

  • 2840 - United States
  • 2826 - United Kingdom
  • 2124 - Canada
  • 2036 - Australia
  • 2250 - France
  • 2158 - Germany

Keyword Suggestions Endpoint:

# Get keyword suggestions (similar to SemRush phrase_related)
curl -s -X POST "https://api.dataforseo.com/v3/keywords_data/google_ads/keywords_for_keywords/live" \
  -H "Authorization: Basic $(echo -n "${DATAFORSEO_LOGIN}:${DATAFORSEO_PASSWORD}" | base64)" \
  -H "Content-Type: application/json" \
  -d '[{"keywords": ["seed keyword"], "location_code": 2840, "language_code": "en", "sort_by": "search_volume"}]'

When to use DataForSEO vs SemRush:

  • Use SemRush as the primary source for keyword difficulty, competitor analysis, and domain organic keywords
  • Use DataForSEO for bulk search volume lookups (supports up to 700 keywords per request, more cost-effective for large batches)
  • Use DataForSEO when you need Google Ads-aligned data (their data comes directly from Google Keyword Planner)
  • Cross-reference both sources when search volume numbers differ significantly

SerpAPI (People Also Ask & Related Searches)

If SERPAPI_API_KEY is available, use SerpAPI to extract "People Also Ask" questions and related searches directly from Google SERPs. This data is not available from SemRush and is valuable for FAQ sections and content ideation.

Search Endpoint:

# Get SERP data including People Also Ask and related searches
curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=10"

Parsing People Also Ask:

# Extract People Also Ask questions
curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=10" | \
  jq -r '.related_questions[] | {
    question: .question,
    snippet: .snippet,
    link: .link,
    title: .title
  }'

Key response sections:

  • related_questions - Array of "People Also Ask" questions with snippets and source URLs
  • related_searches - Array of related search queries that Google suggests
  • organic_results - Top 10 organic results (useful for SERP analysis)

Parsing Related Searches:

# Extract related searches for content ideation
curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=10" | \
  jq -r '.related_searches[] | .query'

How to use SerpAPI data in keyword research:

  1. FAQ content: Use "People Also Ask" questions directly as H2/H3 headings in blog posts or as FAQ schema entries. These are questions Google already associates with the keyword.
  2. Content gap discovery: If a PAA question has a weak snippet answer (short, vague, or from a low-authority site), that is an opportunity to write a better answer and win the featured snippet.
  3. Keyword expansion: Related searches are Google's own suggestions for related topics. Add these to your keyword list and check their volume via SemRush or DataForSEO.
  4. Search intent validation: The organic results show what content types Google ranks for this keyword. If all top 10 are blog posts, write a blog post. If they are product pages, a blog post will not rank.
  5. Cluster building: Group PAA questions and related searches by subtopic to identify natural content clusters.

Additional SerpAPI parameters:

  • location=United+States - Geo-target the search
  • gl=us - Country code for Google domain
  • hl=en - Interface language
  • device=desktop or device=mobile - Desktop vs mobile SERPs (mobile may show different PAA questions)

Note: SerpAPI charges per search. Use it strategically for your highest-priority keywords rather than for bulk research. Pair it with SemRush for volume data and DataForSEO for bulk lookups.

平台分布

Codex

37.63%
按下载量换算343

Claude

31.44%
按下载量换算286

Cursor

17.65%
按下载量换算161

Gemini CLI

9.44%
按下载量换算86

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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