voltagent-seo-content-marketing-skills

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📈 SEO & Content Marketing Skills Suite

📈 SEO与内容营销技能套件

Skill by ara.so — Marketing Skills collection.

This skill suite provides specialized commands and workflows for SEO and content marketing, derived from VoltAgent/awesome-agent-skills. It includes 10 commands for keyword research, content audits, technical SEO analysis, competitor research, and 5 multi-step workflows for comprehensive SEO campaigns.

由ara.so开发的技能——营销技能合集。

本技能套件提供专为SEO和内容营销设计的命令与流程，源自VoltAgent/awesome-agent-skills项目。它包含10个用于关键词研究、内容审核、技术SEO分析、竞品调研的命令，以及5个用于全面SEO推广的多步骤工作流。

What This Project Does

项目功能

The r16-voltagent-awesome-agent-skills-seo suite gives AI agents structured SEO expertise:

Keyword research with clustering, intent mapping, and opportunity scoring
Content audits including quality assessment, duplication detection, cannibalization analysis
Technical SEO crawl budget, Core Web Vitals, schema validation
Competitor analysis backlink gaps, topic gaps, featured snippet opportunities
Content generation SEO-optimized briefs, outlines, and publishing pipelines
Monitoring rank tracking, SERP volatility alerts
Link building prospect identification and outreach automation

All commands follow a consistent 5-step pattern: scope confirmation → live analysis → findings → action plan → next steps.

r16-voltagent-awesome-agent-skills-seo套件为AI Agent提供结构化的SEO专业能力：

关键词研究：包含聚类、意图映射和机会评分
内容审核：涵盖质量评估、重复内容检测、关键词 cannibalization（内部竞争）分析
技术SEO：抓取预算、Core Web Vitals、Schema验证
竞品分析：反向链接差距、主题差距、特色摘要机会
内容生成：SEO优化的简报、大纲和发布流程
监控：排名追踪、SERP波动提醒
外链建设：潜在合作方识别和 outreach（外联）自动化

所有命令遵循统一的5步模式：范围确认→实时分析→结果呈现→行动计划→后续步骤。

Installation

安装

Clone to Claude Skills Directory

克隆到Claude技能目录

bash

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bash

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Create skills directory if it doesn't exist

如果技能目录不存在则创建

mkdir -p ~/.claude/skills/

Clone the repository

克隆仓库

git clone https://github.com/Gravityaespot/r16-voltagent-awesome-agent-skills-seo.git
~/.claude/skills/voltagent-seo-skills/

Or copy manually

或手动复制

cp -r /path/to/downloaded/repo ~/.claude/skills/voltagent-seo-skills/

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cp -r /path/to/downloaded/repo ~/.claude/skills/voltagent-seo-skills/

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Register in Claude Code Session

在Claude代码会话中注册

In a Claude Code session:

bash

/read ~/.claude/skills/voltagent-seo-skills/SKILL.md

Or programmatically:

python

import os
from pathlib import Path

在Claude代码会话中执行：

bash

/read ~/.claude/skills/voltagent-seo-skills/SKILL.md

或通过代码实现：

python

import os
from pathlib import Path

Load skill definition

加载技能定义

skill_path = Path.home() / ".claude/skills/voltagent-seo-skills/SKILL.md" with open(skill_path) as f: skill_definition = f.read()

Register with agent

向Agent注册技能

agent.load_skill(skill_definition)

undefined

agent.load_skill(skill_definition)

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Core Commands

核心命令

/keyword-research

/keyword-research

Deep keyword clustering with intent mapping and opportunity scoring.

Usage:

bash

/keyword-research "outdoor camping gear"

/keyword-research "project management software" \
  --country US \
  --language en \
  --depth deep \
  --output json

Output Structure:

╔════════════════════════════════════════════════╗
║  Keyword Research: outdoor camping gear        ║
╠════════════════════════════════════════════════╣
║  Analyzing search data …  [██████████] 100%    ║
║  Clustering keywords …    [██████████] 100%    ║
║  Mapping intent …         [██████████] 100%    ║
╚════════════════════════════════════════════════╝

┌──────────────────────┬────────┬────┬──────────┬────────┐
│ Keyword              │ Volume │ KD │ Intent   │ Score  │
├──────────────────────┼────────┼────┼──────────┼────────┤
│ camping gear         │ 49 500 │ 67 │ Comm     │ 8.2/10 │
│ best camping gear    │ 18 100 │ 45 │ Comm/Inf │ 9.1/10 │
│ camping gear list    │  8 900 │ 32 │ Info     │ 8.7/10 │
│ camping equipment    │ 33 100 │ 71 │ Comm     │ 7.5/10 │
└──────────────────────┴────────┴────┴──────────┴────────┘

🎯 Recommended targets: best camping gear, camping gear list

API Integration:

python

import os
from seo_skills import KeywordResearch

深度关键词聚类，包含意图映射和机会评分。

使用方式：

bash

/keyword-research "outdoor camping gear"

/keyword-research "project management software" \
  --country US \
  --language en \
  --depth deep \
  --output json

输出结构：

╔════════════════════════════════════════════════╗
║  Keyword Research: outdoor camping gear        ║
╠════════════════════════════════════════════════╣
║  Analyzing search data …  [██████████] 100%    ║
║  Clustering keywords …    [██████████] 100%    ║
║  Mapping intent …         [██████████] 100%    ║
╚════════════════════════════════════════════════╝

┌──────────────────────┬────────┬────┬──────────┬────────┐
│ Keyword              │ Volume │ KD │ Intent   │ Score  │
├──────────────────────┼────────┼────┼──────────┼────────┤
│ camping gear         │ 49 500 │ 67 │ Comm     │ 8.2/10 │
│ best camping gear    │ 18 100 │ 45 │ Comm/Inf │ 9.1/10 │
│ camping gear list    │  8 900 │ 32 │ Info     │ 8.7/10 │
│ camping equipment    │ 33 100 │ 71 │ Comm     │ 7.5/10 │
└──────────────────────┴────────┴────┴──────────┴────────┘

🎯 推荐目标关键词：best camping gear, camping gear list

API集成：

python

import os
from seo_skills import KeywordResearch

Initialize with API credentials from env vars

使用环境变量中的API凭证初始化

kr = KeywordResearch( api_key=os.getenv("SEO_API_KEY"), country="US" )

Run keyword research

执行关键词研究

results = kr.analyze( seed_keyword="outdoor camping gear", depth="deep", min_volume=100, max_difficulty=60 )

Access structured data

访问结构化数据

for cluster in results.clusters: print(f"Cluster: {cluster.theme}") for kw in cluster.keywords: print(f" {kw.term}: {kw.volume} vol, {kw.difficulty} KD")

undefined

for cluster in results.clusters: print(f"Cluster: {cluster.theme}") for kw in cluster.keywords: print(f" {kw.term}: {kw.volume} vol, {kw.difficulty} KD")

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/content-audit

/content-audit

Full-site content quality analysis with duplication and cannibalization detection.

Usage:

bash

/content-audit --scope full --output md

/content-audit \
  --url https://example.com \
  --scope /blog \
  --min-words 300 \
  --check-duplicates

Output:

╔════════════════════════════════════════════════╗
║  Content Audit: example.com                    ║
╠════════════════════════════════════════════════╣
║  Crawling pages …     [████████░░]  82%  823/1002 ║
║  Analyzing content …  [██████░░░░]  65%  651/1002 ║
╚════════════════════════════════════════════════╝

┌─────────────────────┬─────────┬─────────┬────────┐
│ Issue               │ Pages   │ Severity│ Impact │
├─────────────────────┼─────────┼─────────┼────────┤
│ 🔴 Thin content     │     127 │ High    │ -45%   │
│ 🔴 Duplicate title  │      89 │ High    │ -38%   │
│ 🟠 Missing H1       │      64 │ Medium  │ -22%   │
│ 🟠 Keyword cannibal │      43 │ Medium  │ -19%   │
│ 🟡 Long meta desc   │      31 │ Low     │ -5%    │
└─────────────────────┴─────────┴─────────┴────────┘

✅ Quick wins (1-2 days):
  • Add H1 tags to 64 pages
  • Shorten 31 meta descriptions

⚠️  Medium-term (1-2 weeks):
  • Expand 127 thin content pages to 800+ words
  • Resolve 43 keyword cannibalization conflicts

全站点内容质量分析，包含重复内容和关键词内部竞争检测。

使用方式：

bash

/content-audit --scope full --output md

/content-audit \
  --url https://example.com \
  --scope /blog \
  --min-words 300 \
  --check-duplicates

输出：

╔════════════════════════════════════════════════╗
║  Content Audit: example.com                    ║
╠════════════════════════════════════════════════╣
║  Crawling pages …     [████████░░]  82%  823/1002 ║
║  Analyzing content …  [██████░░░░]  65%  651/1002 ║
╚════════════════════════════════════════════════╝

┌─────────────────────┬─────────┬─────────┬────────┐
│ Issue               │ Pages   │ Severity│ Impact │
├─────────────────────┼─────────┼─────────┼────────┤
│ 🔴 内容单薄         │     127 │ High    │ -45%   │
│ 🔴 标题重复         │      89 │ High    │ -38%   │
│ 🟠 缺少H1标签       │      64 │ Medium  │ -22%   │
│ 🟠 关键词内部竞争    │      43 │ Medium  │ -19%   │
│ 🟡 元描述过长       │      31 │ Low     │ -5%    │
└─────────────────────┴─────────┴─────────┴────────┘

✅ 快速优化方案（1-2天）：
  • 为64个页面添加H1标签
  • 缩短31个过长的元描述

⚠️ 中期优化方案（1-2周）：
  • 将127篇单薄内容扩展至800字以上
  • 解决43个关键词内部竞争冲突

/technical-seo

/technical-seo

Comprehensive technical SEO audit covering crawlability, performance, and indexability.

Usage:

bash

/technical-seo https://example.com

/technical-seo https://example.com \
  --check-core-web-vitals \
  --validate-schema \
  --crawl-budget-analysis

Integration Example:

javascript

const { TechnicalSEO } = require('voltagent-seo-skills');

const audit = new TechnicalSEO({
  apiKey: process.env.SEO_API_KEY,
  userAgent: 'SEO-Audit-Bot/1.0'
});

async function runAudit(url) {
  const results = await audit.analyze(url, {
    checkCoreWebVitals: true,
    validateSchema: true,
    crawlBudgetAnalysis: true,
    checkMobileFriendly: true
  });

  // Access results
  console.log('Core Web Vitals:', results.coreWebVitals);
  console.log('Schema Issues:', results.schemaValidation.errors);
  console.log('Crawl Budget:', results.crawlBudget.efficiency);

  // Generate report
  await audit.generateReport(results, 'audit-report.html');
}

runAudit('https://example.com');

全面的技术SEO审核，涵盖可抓取性、性能和可索引性。

使用方式：

bash

/technical-seo https://example.com

/technical-seo https://example.com \
  --check-core-web-vitals \
  --validate-schema \
  --crawl-budget-analysis

集成示例：

javascript

const { TechnicalSEO } = require('voltagent-seo-skills');

const audit = new TechnicalSEO({
  apiKey: process.env.SEO_API_KEY,
  userAgent: 'SEO-Audit-Bot/1.0'
});

async function runAudit(url) {
  const results = await audit.analyze(url, {
    checkCoreWebVitals: true,
    validateSchema: true,
    crawlBudgetAnalysis: true,
    checkMobileFriendly: true
  });

  // 访问结果
  console.log('Core Web Vitals:', results.coreWebVitals);
  console.log('Schema Issues:', results.schemaValidation.errors);
  console.log('Crawl Budget:', results.crawlBudget.efficiency);

  // 生成报告
  await audit.generateReport(results, 'audit-report.html');
}

runAudit('https://example.com');

/competitor-gap

/competitor-gap

Identify backlink gaps, content gaps, and featured snippet opportunities.

Usage:

bash

/competitor-gap \
  --my-site example.com \
  --competitors competitor1.com,competitor2.com,competitor3.com

/competitor-gap \
  --my-site example.com \
  --competitors competitor1.com,competitor2.com \
  --focus backlinks \
  --min-dr 40

识别反向链接差距、内容差距和特色摘要机会。

使用方式：

bash

/competitor-gap \
  --my-site example.com \
  --competitors competitor1.com,competitor2.com,competitor3.com

/competitor-gap \
  --my-site example.com \
  --competitors competitor1.com,competitor2.com \
  --focus backlinks \
  --min-dr 40

/content-brief

/content-brief

Generate AI-powered SEO content briefs with outlines, NLP terms, and word count targets.

Usage:

bash

/content-brief "best project management tools 2024"

/content-brief "how to start a podcast" \
  --target-keywords "podcast hosting,podcast equipment" \
  --word-count 2500 \
  --include-nlp-terms \
  --competitor-analysis

Programmatic Usage:

python

from seo_skills import ContentBrief

brief_generator = ContentBrief(api_key=os.getenv("SEO_API_KEY"))

brief = brief_generator.create(
    target_keyword="best project management tools 2024",
    additional_keywords=["project management software", "team collaboration"],
    word_count_target=2500,
    include_nlp_terms=True,
    analyze_competitors=True,
    top_n_competitors=10
)

生成AI驱动的SEO内容简报，包含大纲、NLP术语和字数目标。

使用方式：

bash

/content-brief "best project management tools 2024"

/content-brief "how to start a podcast" \
  --target-keywords "podcast hosting,podcast equipment" \
  --word-count 2500 \
  --include-nlp-terms \
  --competitor-analysis

代码调用方式：

python

from seo_skills import ContentBrief

brief_generator = ContentBrief(api_key=os.getenv("SEO_API_KEY"))

brief = brief_generator.create(
    target_keyword="best project management tools 2024",
    additional_keywords=["project management software", "team collaboration"],
    word_count_target=2500,
    include_nlp_terms=True,
    analyze_competitors=True,
    top_n_competitors=10
)

Access brief components

访问简报组件

print(brief.title) print(brief.meta_description) print(brief.outline) print(brief.nlp_terms) print(brief.word_count_recommendation)

undefined

print(brief.title) print(brief.meta_description) print(brief.outline) print(brief.nlp_terms) print(brief.word_count_recommendation)

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/serp-monitor

/serp-monitor

Daily rank tracking with volatility alerts and CTR optimization.

Usage:

bash

/serp-monitor \
  --keywords "project management,team collaboration,remote work tools" \
  --url example.com \
  --frequency daily

/serp-monitor \
  --keyword-file keywords.csv \
  --alert-on-drop 3 \
  --ctr-optimization

每日排名追踪，包含波动提醒和CTR优化。

使用方式：

bash

/serp-monitor \
  --keywords "project management,team collaboration,remote work tools" \
  --url example.com \
  --frequency daily

/serp-monitor \
  --keyword-file keywords.csv \
  --alert-on-drop 3 \
  --ctr-optimization

/link-prospecting

/link-prospecting

Quality backlink prospect identification with DA/DR filters and outreach templates.

Usage:

bash

/link-prospecting \
  --topic "sustainable fashion" \
  --min-da 30 \
  --max-results 100 \
  --with-contact-info

/link-prospecting \
  --topic "AI marketing tools" \
  --competitor-backlinks competitor.com \
  --generate-outreach-templates

高质量反向链接潜在合作方识别，包含DA/DR筛选和外联模板。

使用方式：

bash

/link-prospecting \
  --topic "sustainable fashion" \
  --min-da 30 \
  --max-results 100 \
  --with-contact-info

/link-prospecting \
  --topic "AI marketing tools" \
  --competitor-backlinks competitor.com \
  --generate-outreach-templates

/page-speed-seo

/page-speed-seo

Page speed analysis mapped to SEO ranking impact.

Usage:

bash

/page-speed-seo https://example.com/page

/page-speed-seo https://example.com \
  --check-lcp \
  --check-cls \
  --check-fid \
  --render-blocking-analysis

页面速度分析，映射至SEO排名影响。

使用方式：

bash

/page-speed-seo https://example.com/page

/page-speed-seo https://example.com \
  --check-lcp \
  --check-cls \
  --check-fid \
  --render-blocking-analysis

/local-seo

/local-seo

Local SEO audit including NAP consistency, Google Business Profile optimization, and citations.

Usage:

bash

/local-seo \
  --business-name "Acme Coffee Shop" \
  --location "Seattle, WA" \
  --check-nap \
  --check-gbp \
  --citation-audit

/local-seo \
  --business-name "Tech Repair Store" \
  --location "Austin, TX" \
  --competitors competitor1.com,competitor2.com

本地SEO审核，包含NAP一致性、Google Business Profile优化和引用检查。

使用方式：

bash

/local-seo \
  --business-name "Acme Coffee Shop" \
  --location "Seattle, WA" \
  --check-nap \
  --check-gbp \
  --citation-audit

/local-seo \
  --business-name "Tech Repair Store" \
  --location "Austin, TX" \
  --competitors competitor1.com,competitor2.com

/content-calendar

/content-calendar

Data-driven editorial calendar based on search demand and seasonality.

Usage:

bash

/content-calendar \
  --topics "fitness,nutrition,wellness" \
  --duration 90 \
  --include-seasonality

/content-calendar \
  --keyword-file topics.csv \
  --duration 180 \
  --publishing-frequency 3 \
  --format json

基于搜索需求和季节性的数据驱动型编辑日历。

使用方式：

bash

/content-calendar \
  --topics "fitness,nutrition,wellness" \
  --duration 90 \
  --include-seasonality

/content-calendar \
  --keyword-file topics.csv \
  --duration 180 \
  --publishing-frequency 3 \
  --format json

Workflows (Multi-Step)

工作流（多步骤）

full-seo-sprint

full-seo-sprint

12-step comprehensive SEO audit and implementation workflow.

Usage:

bash

/workflows:full-seo-sprint example.com --scope full

/workflows:full-seo-sprint example.com \
  --scope full \
  --include-content-plan \
  --include-technical-fixes \
  --timeline 30

Workflow Steps:

① Technical audit
② Keyword research
③ Competitor analysis
④ Content audit
⑤ Backlink profile analysis
⑥ Keyword mapping
⑦ Content gap identification
⑧ Priority technical fixes
⑨ Content creation plan
⑩ Link building strategy
⑪ Implementation roadmap
⑫ Measurement framework

12步全面SEO审核与实施工作流。

使用方式：

bash

/workflows:full-seo-sprint example.com --scope full

/workflows:full-seo-sprint example.com \
  --scope full \
  --include-content-plan \
  --include-technical-fixes \
  --timeline 30

工作流步骤：

① 技术审核
② 关键词研究
③ 竞品分析
④ 内容审核
⑤ 反向链接分析
⑥ 关键词映射
⑦ 内容差距识别
⑧ 优先级技术修复
⑨ 内容创作计划
⑩ 外链建设策略
⑪ 实施路线图
⑫ 衡量框架

launch-seo

launch-seo

Pre-launch SEO checklist and validation.

Usage:

bash

/workflows:launch-seo https://staging.example.com

/workflows:launch-seo https://staging.example.com \
  --check-canonical \
  --check-hreflang \
  --validate-sitemap \
  --check-robots-txt

上线前SEO检查清单与验证。

使用方式：

bash

/workflows:launch-seo https://staging.example.com

/workflows:launch-seo https://staging.example.com \
  --check-canonical \
  --check-hreflang \
  --validate-sitemap \
  --check-robots-txt

content-refresh

content-refresh

Identify and refresh underperforming content.

Usage:

bash

/workflows:content-refresh example.com \
  --ranking-drop 5 \
  --time-period 90

/workflows:content-refresh example.com \
  --min-impressions 1000 \
  --max-ctr 2 \
  --priority high

识别并刷新表现不佳的内容。

使用方式：

bash

/workflows:content-refresh example.com \
  --ranking-drop 5 \
  --time-period 90

/workflows:content-refresh example.com \
  --min-impressions 1000 \
  --max-ctr 2 \
  --priority high

authority-building

authority-building

End-to-end digital PR and link-building campaign.

Usage:

bash

/workflows:authority-building \
  --topic "sustainable technology" \
  --target-dr-increase 15 \
  --duration 180

/workflows:authority-building \
  --niche "B2B SaaS" \
  --competitor-analysis \
  --outreach-automation

端到端数字PR与外链建设活动。

使用方式：

bash

/workflows:authority-building \
  --topic "sustainable technology" \
  --target-dr-increase 15 \
  --duration 180

/workflows:authority-building \
  --niche "B2B SaaS" \
  --competitor-analysis \
  --outreach-automation

ai-content-pipeline

ai-content-pipeline

Automated content creation pipeline from keyword to publish.

Usage:

bash

/workflows:ai-content-pipeline \
  --keywords-file keywords.csv \
  --publishing-schedule weekly \
  --auto-optimize

/workflows:ai-content-pipeline \
  --topic "digital marketing trends 2024" \
  --content-type blog \
  --word-count 2000 \
  --include-images

从关键词到发布的自动化内容创作流程。

使用方式：

bash

/workflows:ai-content-pipeline \
  --keywords-file keywords.csv \
  --publishing-schedule weekly \
  --auto-optimize

/workflows:ai-content-pipeline \
  --topic "digital marketing trends 2024" \
  --content-type blog \
  --word-count 2000 \
  --include-images

Configuration

配置

Create a configuration file at

~/.claude/skills/voltagent-seo-skills/config.yml

yaml

undefined

在

~/.claude/skills/voltagent-seo-skills/config.yml

创建配置文件：

yaml

undefined

SEO API credentials (use env vars in production)

SEO API凭证（生产环境使用环境变量）

api: seo_api_key: ${SEO_API_KEY} search_console_credentials: ${GOOGLE_SEARCH_CONSOLE_JSON} analytics_key: ${GOOGLE_ANALYTICS_KEY}

Default settings

默认设置

defaults: country: US language: en user_agent: "SEO-Agent/1.0" crawl_delay: 1.0 max_pages: 10000

Output preferences

输出偏好

output: format: markdown include_charts: true export_csv: true progress_bars: true

Thresholds

阈值

thresholds: min_word_count: 300 thin_content: 300 max_keyword_difficulty: 70 min_domain_rating: 30 core_web_vitals_lcp: 2.5 core_web_vitals_fid: 100 core_web_vitals_cls: 0.1

Workflows

工作流

workflows: full_seo_sprint_steps: 12 content_refresh_lookback_days: 90 authority_building_duration_days: 180


Load configuration programmatically:

```python
import os
import yaml
from pathlib import Path

config_path = Path.home() / ".claude/skills/voltagent-seo-skills/config.yml"

with open(config_path) as f:
    config = yaml.safe_load(f)

workflows: full_seo_sprint_steps: 12 content_refresh_lookback_days: 90 authority_building_duration_days: 180


通过代码加载配置：

```python
import os
import yaml
from pathlib import Path

config_path = Path.home() / ".claude/skills/voltagent-seo-skills/config.yml"

with open(config_path) as f:
    config = yaml.safe_load(f)

Expand environment variables

展开环境变量

for key in config['api']: if isinstance(config['api'][key], str) and config['api'][key].startswith('${'): env_var = config['api'][key][2:-1] config['api'][key] = os.getenv(env_var)

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for key in config['api']: if isinstance(config['api'][key], str) and config['api'][key].startswith('${'): env_var = config['api'][key][2:-1] config['api'][key] = os.getenv(env_var)

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Common Patterns

常见使用模式

Pattern 1: Complete Site Audit

模式1：完整站点审核

bash

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bash

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Step 1: Technical audit

步骤1：技术审核

/technical-seo https://example.com --check-core-web-vitals

Step 2: Content audit

步骤2：内容审核

/content-audit --scope full --check-duplicates

Step 3: Keyword research

步骤3：关键词研究

/keyword-research "main topic" --depth deep

Step 4: Competitor analysis

步骤4：竞品分析

/competitor-gap
--my-site example.com
--competitors competitor1.com,competitor2.com

Step 5: Backlink prospecting

步骤5：外链潜在合作方挖掘

/link-prospecting --topic "your niche" --min-da 30

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/link-prospecting --topic "your niche" --min-da 30

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Pattern 2: New Content Creation

模式2：新内容创作

bash

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bash

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Step 1: Research keyword

步骤1：关键词研究

/keyword-research "target topic" --output json

Step 2: Generate brief

步骤2：生成内容简报

/content-brief "target keyword"
--word-count 2000
--include-nlp-terms
--competitor-analysis

Step 3: Add to calendar

步骤3：添加到内容日历

/content-calendar --topics "target topic" --duration 30

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/content-calendar --topics "target topic" --duration 30

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Pattern 3: Rank Recovery

模式3：排名恢复

bash

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bash

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Step 1: Identify drops

步骤1：识别排名下降

/serp-monitor --alert-on-drop 5 --time-period 30

Step 2: Run content refresh workflow

步骤2：执行内容刷新工作流

/workflows:content-refresh example.com
--ranking-drop 5
--time-period 30
--priority high

Step 3: Monitor improvements

步骤3：监控排名提升

/serp-monitor --frequency daily --ctr-optimization

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/serp-monitor --frequency daily --ctr-optimization

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Pattern 4: Programmatic Batch Processing

模式4：批量程序化处理

python

from seo_skills import KeywordResearch, ContentBrief, ContentCalendar
import pandas as pd

python

from seo_skills import KeywordResearch, ContentBrief, ContentCalendar
import pandas as pd

Load keyword list

加载关键词列表

keywords = pd.read_csv('seed_keywords.csv')

Initialize tools

初始化工具

kr = KeywordResearch(api_key=os.getenv("SEO_API_KEY")) cb = ContentBrief(api_key=os.getenv("SEO_API_KEY")) cc = ContentCalendar()

Process each keyword

处理每个关键词

briefs = [] for keyword in keywords['keyword']: # Research keyword opportunities research = kr.analyze(keyword, depth="deep")

# Generate brief for top opportunity
top_kw = research.top_opportunities[0]
brief = cb.create(
    target_keyword=top_kw.term,
    word_count_target=2000,
    include_nlp_terms=True
)
briefs.append(brief)

briefs = [] for keyword in keywords['keyword']: # 研究关键词机会 research = kr.analyze(keyword, depth="deep")

# 为最优机会生成简报
top_kw = research.top_opportunities[0]
brief = cb.create(
    target_keyword=top_kw.term,
    word_count_target=2000,
    include_nlp_terms=True
)
briefs.append(brief)

Create content calendar

创建内容日历

calendar = cc.generate( briefs=briefs, duration_days=90, publishing_frequency=3, include_seasonality=True )

Export

导出

calendar.to_csv('content_calendar.csv')

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calendar.to_csv('content_calendar.csv')

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Troubleshooting

故障排除

Issue: API Rate Limiting

问题：API速率限制

Symptom:

RateLimitError: API quota exceeded

Solution:

python

from seo_skills import KeywordResearch
import time

kr = KeywordResearch(
    api_key=os.getenv("SEO_API_KEY"),
    rate_limit_delay=2.0  # Add 2 second delay between requests
)

症状：

RateLimitError: API quota exceeded

解决方案：

python

from seo_skills import KeywordResearch
import time

kr = KeywordResearch(
    api_key=os.getenv("SEO_API_KEY"),
    rate_limit_delay=2.0  # 请求间添加2秒延迟
)

Or implement exponential backoff

或实现指数退避

from tenacity import retry, wait_exponential, stop_after_attempt

@retry(wait=wait_exponential(min=1, max=60), stop=stop_after_attempt(5)) def research_with_retry(keyword): return kr.analyze(keyword)

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from tenacity import retry, wait_exponential, stop_after_attempt

@retry(wait=wait_exponential(min=1, max=60), stop=stop_after_attempt(5)) def research_with_retry(keyword): return kr.analyze(keyword)

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Issue: Incomplete Crawl Results

问题：抓取结果不完整

Symptom: Content audit missing pages

Solution:

bash

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症状： 内容审核遗漏页面

解决方案：

bash

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Increase crawl depth and timeout

增加抓取深度和超时时间

/content-audit
--scope full
--max-depth 10
--timeout 300
--follow-redirects
--include-noindex


Or programmatically:

```python
from seo_skills import ContentAudit

audit = ContentAudit(
    max_depth=10,
    timeout=300,
    follow_redirects=True,
    respect_robots_txt=True,
    include_noindex=True,
    max_pages=50000
)

/content-audit
--scope full
--max-depth 10
--timeout 300
--follow-redirects
--include-noindex


或通过代码实现：

```python
from seo_skills import ContentAudit

audit = ContentAudit(
    max_depth=10,
    timeout=300,
    follow_redirects=True,
    respect_robots_txt=True,
    include_noindex=True,
    max_pages=50000
)

Issue: Missing Environment Variables

问题：缺少环境变量

Symptom:

EnvironmentError: SEO_API_KEY not found

Solution:

Create

.env

file:

bash

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症状：

EnvironmentError: SEO_API_KEY not found

解决方案：

创建

.env

文件：

bash

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.env

SEO_API_KEY=your_api_key_here GOOGLE_SEARCH_CONSOLE_JSON=/path/to/credentials.json GOOGLE_ANALYTICS_KEY=your_ga_key_here


Load in your script:

```python
from dotenv import load_dotenv
import os

load_dotenv()

SEO_API_KEY=your_api_key_here GOOGLE_SEARCH_CONSOLE_JSON=/path/to/credentials.json GOOGLE_ANALYTICS_KEY=your_ga_key_here


在脚本中加载：

```python
from dotenv import load_dotenv
import os

load_dotenv()

Now environment variables are available

现在可访问环境变量

api_key = os.getenv("SEO_API_KEY")

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api_key = os.getenv("SEO_API_KEY")

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Issue: Keyword Research Returns No Results

问题：关键词研究无结果

Symptom: Empty keyword list for seed term

Solution:

bash

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症状： 种子关键词返回空列表

解决方案：

bash

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Broaden search parameters

放宽搜索参数

/keyword-research "narrow topic"
--depth deep
--min-volume 10
--include-related
--include-questions
--language en
--country US

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/keyword-research "narrow topic"
--depth deep
--min-volume 10
--include-related
--include-questions
--language en
--country US

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Issue: Schema Validation Failures

问题：Schema验证失败

Symptom: Multiple schema errors in technical audit

Solution:

python

from seo_skills import TechnicalSEO

audit = TechnicalSEO()
results = audit.validate_schema(
    url='https://example.com',
    schema_types=['Product', 'Article', 'Organization'],
    strict_mode=False  # Use lenient validation first
)

症状： 技术审核中出现多个Schema错误

解决方案：

python

from seo_skills import TechnicalSEO

audit = TechnicalSEO()
results = audit.validate_schema(
    url='https://example.com',
    schema_types=['Product', 'Article', 'Organization'],
    strict_mode=False  # 先使用宽松验证
)

Review specific errors

查看具体错误

for error in results.errors: print(f"Path: {error.path}") print(f"Issue: {error.message}") print(f"Fix: {error.recommendation}")

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for error in results.errors: print(f"路径: {error.path}") print(f"问题: {error.message}") print(f"修复建议: {error.recommendation}")

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Advanced Usage

高级用法

Custom Scoring Algorithm

自定义评分算法

python

from seo_skills import KeywordResearch

class CustomKeywordScoring(KeywordResearch):
    def calculate_opportunity_score(self, keyword):
        """Custom scoring based on your business priorities"""
        volume_score = min(keyword.volume / 10000, 1.0) * 40
        difficulty_score = (100 - keyword.difficulty) / 100 * 30
        intent_score = self.intent_multiplier(keyword.intent) * 20
        trend_score = keyword.trend_direction * 10
        
        return volume_score + difficulty_score + intent_score + trend_score
    
    def intent_multiplier(self, intent):
        # Prioritize commercial intent
        multipliers = {
            'transactional': 1.0,
            'commercial': 0.9,
            'informational': 0.6,
            'navigational': 0.3
        }
        return multipliers.get(intent, 0.5)

python

from seo_skills import KeywordResearch

class CustomKeywordScoring(KeywordResearch):
    def calculate_opportunity_score(self, keyword):
        """基于业务优先级的自定义评分"""
        volume_score = min(keyword.volume / 10000, 1.0) * 40
        difficulty_score = (100 - keyword.difficulty) / 100 * 30
        intent_score = self.intent_multiplier(keyword.intent) * 20
        trend_score = keyword.trend_direction * 10
        
        return volume_score + difficulty_score + intent_score + trend_score
    
    def intent_multiplier(self, intent):
        # 优先考虑商业意图
        multipliers = {
            'transactional': 1.0,
            'commercial': 0.9,
            'informational': 0.6,
            'navigational': 0.3
        }
        return multipliers.get(intent, 0.5)

Use custom scorer

使用自定义评分器

kr = CustomKeywordScoring(api_key=os.getenv("SEO_API_KEY")) results = kr.analyze("project management software")

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kr = CustomKeywordScoring(api_key=os.getenv("SEO_API_KEY")) results = kr.analyze("project management software")

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Integration with CI/CD

与CI/CD集成

yaml

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yaml

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.github/workflows/seo-monitoring.yml

name: SEO Monitoring

on: schedule: - cron: '0 0 * * *' # Daily at midnight

jobs: seo-audit: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3

  - name: Setup Python
    uses: actions/setup-python@v4
    with:
      python-version: '3.11'
  
  - name: Install dependencies
    run: |
      pip install voltagent-seo-skills pyyaml
  
  - name: Run daily SEO checks
    env:
      SEO_API_KEY: ${{ secrets.SEO_API_KEY }}
    run: |
      python scripts/daily_seo_check.py
  
  - name: Create issue if problems found
    if: failure()
    uses: actions/github-script@v6
    with:
      script: |
        github.rest.issues.create({
          owner: context.repo.owner,
          repo: context.repo.repo,
          title: 'SEO Issues Detected',
          body: 'Daily SEO audit found issues. Check workflow logs.'
        })

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name: SEO Monitoring

on: schedule: - cron: '0 0 * * *' # 每日午夜执行

jobs: seo-audit: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3

  - name: 设置Python环境
    uses: actions/setup-python@v4
    with:
      python-version: '3.11'
  
  - name: 安装依赖
    run: |
      pip install voltagent-seo-skills pyyaml
  
  - name: 执行每日SEO检查
    env:
      SEO_API_KEY: ${{ secrets.SEO_API_KEY }}
    run: |
      python scripts/daily_seo_check.py
  
  - name: 发现问题时创建Issue
    if: failure()
    uses: actions/github-script@v6
    with:
      script: |
        github.rest.issues.create({
          owner: context.repo.owner,
          repo: context.repo.repo,
          title: '检测到SEO问题',
          body: '每日SEO审核发现问题，请查看工作流日志。'
        })

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Resources

资源

Source repository: https://github.com/VoltAgent/awesome-agent-skills
Documentation: See README.md in skill directory
Issues: Report at repository issues page

License: MIT

源代码仓库: https://github.com/VoltAgent/awesome-agent-skills
文档: 查看技能目录中的README.md
问题反馈: 在仓库的issues页面提交

许可证: MIT