seo-keyword-expansion

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Original

English

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Translation

Chinese

SEO Keyword Expansion

SEO关键词拓展

Expand seed keywords into a comprehensive candidate pool using multiple discovery methods.

通过多种发现方法将种子关键词拓展为全面的候选关键词库。

Credentials Check

凭证检查

DATAFORSEO_LOGIN

DATAFORSEO_PASSWORD

are missing, tell the user:

"DataForSEO credentials are not configured. Please run
seo-seed-discovery
first — it will guide you through the setup."

如果缺少

DATAFORSEO_LOGIN

或

DATAFORSEO_PASSWORD

，请告知用户：

"未配置DataForSEO凭证。请先运行
seo-seed-discovery
——它会引导您完成设置。"

When to Use

使用时机

After

seo-seed-discovery

has completed. Requires

config.json

and

competitors.json

in the workspace.

在

seo-seed-discovery

完成之后。工作区中需要存在

config.json

和

competitors.json

文件。

Prerequisites

前提条件

Workspace with
```
config.json
```
(from init-workspace)

competitors.json

and

competitor-keywords.json

present

包含
```
config.json
```
的工作区（来自init-workspace）

已存在

competitors.json

和

competitor-keywords.json

文件

Procedure

操作步骤

Step 1: Google Autocomplete Mining

步骤1：谷歌自动补全挖掘

bash

node {baseDir}/scripts/autosuggest.ts --workspace <workspace_path>

Mines Google Autocomplete suggestions for seed keywords. Reveals long-tail patterns users actually search. Writes

autosuggest.json

bash

node {baseDir}/scripts/autosuggest.ts --workspace <workspace_path>

为种子关键词挖掘谷歌自动补全建议，揭示用户实际搜索的长尾关键词模式。生成

autosuggest.json

文件。

Step 2: Related Keywords Discovery

步骤2：相关关键词发现

bash

node {baseDir}/scripts/related-keywords.ts --workspace <workspace_path>

Finds semantically related keywords via DataForSEO Labs. Writes

related.json

bash

node {baseDir}/scripts/related-keywords.ts --workspace <workspace_path>

通过DataForSEO Labs查找语义相关的关键词。生成

related.json

文件。

Step 3: Keyword Suggestions

步骤3：关键词建议

bash

node {baseDir}/scripts/keyword-suggestions.ts --workspace <workspace_path>

Gets AI-powered keyword suggestions from DataForSEO. Writes

suggestions.json

bash

node {baseDir}/scripts/keyword-suggestions.ts --workspace <workspace_path>

从DataForSEO获取AI驱动的关键词建议。生成

suggestions.json

文件。

Step 4: Reddit Community Mining (via SERP)

步骤4：Reddit社区挖掘（通过SERP）

bash

node {baseDir}/scripts/reddit-serp-mining.ts --workspace <workspace_path>

Searches

site:reddit.com

via SERP to discover how real users discuss topics. Extracts question patterns and pain points. Writes

reddit-insights.json

bash

node {baseDir}/scripts/reddit-serp-mining.ts --workspace <workspace_path>

通过SERP搜索

site:reddit.com

，发现真实用户讨论话题的方式。提取问题模式和痛点。生成

reddit-insights.json

文件。

Expert Analysis Framework

专家分析框架

As an expert SEO analyst, evaluate the expanded keyword pool:

Long-tail Gems: Identify high-specificity keywords from autocomplete that signal strong intent
Content Cluster Seeds: Group related keywords into potential topic clusters
User Language Patterns: What terminology do real users (especially from Reddit) use vs. industry jargon?
PSEO Patterns: Are there repeatable keyword patterns (e.g., "[tool] for [industry]") suitable for programmatic SEO?
Intent Signals: Pre-classify keywords by likely intent based on modifiers and context

作为专业SEO分析师，评估拓展后的关键词库：

长尾优质关键词：从自动补全结果中识别出具有明确意图的高特异性关键词
内容集群种子：将相关关键词分组为潜在的主题集群
用户语言模式：真实用户（尤其是Reddit用户）使用的术语与行业术语有何差异？
PSEO模式：是否存在可重复的关键词模式（例如“[工具] for [行业]”）适合程序化SEO（PSEO）？
意图信号：根据修饰词和上下文预先对关键词的可能意图进行分类

Output Format

输出格式

Total Candidates Found (by source)
Top 20 High-Potential Keywords with reasoning
Identified Keyword Clusters (topic groups)
Reddit Pain Points (user questions and concerns)
PSEO Pattern Candidates (if any detected)

找到的候选关键词总数（按来源分类）
20个高潜力关键词及理由
已识别的关键词集群（主题组）
Reddit用户痛点（用户的问题和关注点）
PSEO模式候选词（如果检测到）