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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。

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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

2

许可证

unknown

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/kostja94/marketing-skills
仓库路径:skills/keyword-research
安装命令:
npx skills add https://github.com/kostja94/marketing-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。

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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/kostja94/marketing-skills --skill keyword-research

简介

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。

  • 适用于关键词挖掘、搜索意图分析和竞品语言策略研究等 SEO 场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围和维护状态。
  • 使用前建议核对是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

SEO Content: Keyword Research

Guides keyword research for SEO: finding target keywords, assessing difficulty, understanding search intent, and building topical maps. ~95% of keywords get fewer than 10 searches/month; low-volume, high-intent terms often yield faster rankings and conversion.

When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

Initial Assessment

Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for product, audience, and positioning.

Identify:

  1. Product/service: What you offer
  2. Audience: Who searches for it
  3. Goals: Traffic, conversions, brand
  4. Tool access: Google Keyword Planner, Google Trends, or SEO tools

Discovery Methods

Base Discovery

MethodPurpose
User perspectiveWhat pain points? What would they search? Customer language from product context
Tool expansionRelated keywords, questions, suggestions; Google autocomplete, PAA, Related Searches
Competitor reverseAnalyze competitor titles, H1, URL; identify topics they rank for; find gaps (#4–10 = opportunity) — see competitor-research
Google PAAPeople Also Ask and Related Searches; high-value signals from real user behavior
Extract from articleWhen auditing existing content: extract seed keywords from title, H1, H2s, meta keywords, first 100 words; then search "[primary keyword]" or "[primary keyword] related keywords" for opportunities; use "[primary keyword]" site:competitor.com if competitors known

Google Autocomplete (Long-Tail Discovery)

Google autocomplete reflects real user searches; suggestions only appear if queries have actual traffic. Free; often uncovers low-volume long-tail that keyword tools miss. ~70% of search traffic is long-tail; lower competition, higher conversion.

Alphabet method (seed + space + letter):

  • Type seed keyword + space + each letter: keyword a, keyword b,... keyword z
  • Record relevant suggestions; repeat with numbers 0-9
  • Example: SEO a -> "SEO audit," "SEO agency"; SEO b -> "SEO basics," "SEO best practices"

Position variants (seed in different positions):

  • Prefix: a keyword, b keyword (discover what users add before)
  • Suffix: keyword a, keyword b (most common; alphabet method)
  • Middle: how to keyword a, best keyword for (question + modifier combos)

Question modifiers:

  • how to keyword, what is keyword, why keyword, when to keyword, keyword vs
  • keyword for beginners, keyword for small business, keyword without

Why it works: Keyword tools filter low-volume terms; autocomplete only shows queries with real traffic. Use with PAA and Related Searches for full coverage. Categorize results by intent (informational, commercial, transactional).

Incremental Discovery

  • User feedback: Support, community, reviews, NPS—high-frequency questions = unmet search demand
  • Multi-platform search: Reddit, Quora, X (Twitter), Hacker News—real questions and discussions

Search Intent

IntentContent typeExample
InformationalBlog, guide, FAQ"how to optimize sitemap"
NavigationalBrand page"alignify login"
CommercialComparison, review"SEO tools comparison"
TransactionalProduct, pricing"best SEO tool pricing"

Intent Identification

Modifier words (often signal intent):

IntentModifiers
Informational"how," "what," "why," "guide," "tutorial"
Commercial"best," "compare," "vs," "review," "top"
Transactional"buy," "price," "cheap," "coupon," "free shipping"
LocalLocation names

SERP check: Search the term—knowledge cards/Wiki → informational; product lists/reviews → commercial; brand sites → navigational. Broader terms often show mixed SERP. See serp-features for feature types.

Long-Tail Expansion

  • Google Autocomplete: Alphabet method, position variants, question modifiers; see above. Primary source for long-tail.
  • Intent modifiers: Core + "how," "best," "vs," "compare," "price"
  • Question words: "how to," "what is," "why," "when"
  • Functional modifiers: Core + "-er/-or" (e.g., "image optimizer" for tool-type queries); often higher conversion
  • Clustering: Group by SERP overlap (same top pages), semantic similarity, or intent.

Keyword Clustering & Topical Map

MethodUse
SERP overlapKeywords with overlapping top-ranking pages → same cluster
SemanticGroup by meaning, LSI, related concepts
Intent-basedGroup by intent; separate pages if intent differs within cluster

Pillar–cluster (map keywords to structure):

  • Pillar (Hub): Broad topic page; links to clusters
  • Cluster (Spoke): Focused subtopic; links back to pillar
  • Target long-tail first; then pillar. Interlink clusters within topic.
  • See content-strategy for full pillar-cluster planning and implementation.

Evaluate & Screen

FactorConsider
Search volumeMonthly searches; ~100+/month typical floor; niche can relax
Keyword difficulty (KD)New sites target lower KD
CPCHigher CPC often = stronger commercial intent
SERP featuresFeatured Snippet, PAA, zero-click; SERP features can satisfy intent without click—affects real traffic; see serp-features (Zero-Click section), featured-snippet
Screening order1) Remove irrelevant 2) Filter very low volume 3) Assess achievability 4) Prioritize commercial/transactional

Product Positioning Test (SEO Fit)

Test if positioning is clear enough for search:

  • XXX + Function words: Generator, Creator, Maker, Builder, Changer, Shortener, Scraper, Converter, Downloader, Translator, Extender, Summarizer, Resizer, Remover, Extractor, Recorder, Rewriter, Solver, Calculator; or Platform, Tool, Software, App, Provider, Assistant, Copilot
  • Input + to + Output: e.g., "image to video," "text to speech"—clear input/output signals intent

Agent/Copilot products: Pure native Agent hard to grow via SEO; users rarely search "agent." Release related features first (e.g., CRM, sales bot for sales agent) to build traffic, then funnel to Agent product.

Principles

  • Core rule: Someone must search it—validate with tools; avoid inventing terms
  • Functional keywords: Tool-type (-er/-or) often convert better; users are closer to action
  • Multi-language: Re-research in target language; don't translate existing lists. See translation for translation workflow.

SEO–PPC Keyword Synergy

Keyword research serves both SEO and Google Ads. Align both channels to avoid duplication, cannibalization, and wasted spend.

Data flowUse
keyword-research → google-adsKeyword list, clusters, intent; support terms (login, forum, pricing) → negative keywords for PPC
google-ads → keyword-researchPPC conversion rate, Search Terms report → SEO priority; high-converting PPC terms = worth ranking organically
keyword-research → landing-pageClusters → dedicated LP per intent; PAA questions → FAQ sections
GSC organic rank 4+If you rank well organically, consider reducing/pausing PPC on those terms to avoid cannibalization

PPC data for SEO priority: SEO ROI ≈ (Organic clicks × PPC conversion rate × Customer value) − SEO cost. Use PPC conversion data to validate which keywords to pursue in organic.

Reference: Backlinko – SEO and PPC: 8 Smart Ways to Align

Data Sources

SourceUse
AhrefsKeywords Explorer, Site Explorer
SEMrushKeyword Overview, Organic Research
GSCSearch queries, impressions, clicks
GATraffic by landing page
PostHogFeature/search usage

Report Workflow

  1. Parse — Read Excel/CSV, infer keyword, volume, KD, intent, etc. from headers
  2. Enrich — Web search, visit competitor/product pages; read project-context.md if present
  3. Build — Structure data for report
  4. Generate — Output report in chosen format

Output Format

  • Keyword list with volume, KD, intent
  • Keyword mapping to pages/content
  • Content gaps (competitors rank, you don't)
  • Priority ranking for implementation
  • Topical map (cluster → pillar → page mapping)

Report Structure Reference

SectionContent
Executive SummaryPriorities (top 3)
Keyword OverviewTotal keywords, primary intent, avg KD, content gaps count
Keyword ListKeyword, volume, KD, intent, priority, target page
Keyword MappingPage/URL, target keywords, status
Content GapsKeywords competitors rank for that you don't
Action PlanPriority, action, impact, effort
AppendixSearch intent reference (Informational, Commercial, Transactional, Navigational)

Related Skills

  • seo-strategy: SEO workflow, Product-Led SEO, audit approach; keyword research is Content phase
  • google-ads: Keywords inform Search targeting; PPC data feeds back into SEO priority
  • paid-ads-strategy: When to use paid vs organic; channel selection
  • content-strategy: Keywords inform content plan; topic clusters
  • content-optimization: Keyword placement, density vs stuffing, H2 keywords
  • title-tag, meta-description: Keywords in title, description
  • heading-structure: Keywords in H1, H2
  • link-building: Keywords inform link targets
  • serp-features: SERP features in keyword screening; PAA, Featured Snippet
  • featured-snippet: Snippet-worthy query targeting
  • competitor-research: Competitor keyword/topic analysis; reverse engineering
  • faq-page-generator: PAA questions to FAQ sections; question-based keyword to FAQ content

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