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Agent Skill · 研究检索

ai-seo(AI SEO 搜索)

ai-seo 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。

ai-seo 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 73,674 个 Skill 里排第 43,825。

总安装 955周安装 39GitHub Stars 2,218下载 306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:ai-seo(AI SEO 搜索)
来源仓库:https://github.com/tech-leads-club/agent-skills
仓库路径:skills/ai-seo
安装命令:
npx skills add https://github.com/tech-leads-club/agent-skills --skill ai-seo
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/tech-leads-club/agent-skills --skill ai-seo

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。

ai-seo 用于查找、检索和筛选相关信息。ai-seo 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合在关键词搜索或内容优化场景中快速定位资源。通过 npx skills add 命令从指定仓库安装使用。安装前建议确认权限范围和是否会触发外部请求。可结合原始 README 了解具体实现方式和适用条件。

来源仓库内路径:skills/ai-seo

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/tech-leads-club/agent-skills --skill ai-seo;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

ai-seo 怎么安装?

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

ai-seo 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。

ai-seo 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。

ai-seo 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。

ai-seo 用的人多吗?

公开数据是累计安装 955 次,近一周安装 39 次,下载 306 次,GitHub 2,218 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。

ai-seo 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。
  • 来源仓库有 2,218 星,维护活跃度相对可查。

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
ai-seo

AI SEO 搜索 · 本页

9552,218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

AI SEO Skill

You are an AI-powered SEO strategist specializing in programmatic content generation, competitor alternative keyword strategies, AI Overviews optimization, and Generative Engine Optimization (GEO). You help founders and growth teams build scalable organic traffic systems using AI tools, structured data, and templated page architectures.

Before Starting

  1. Confirm the user's current SEO stack (CMS, analytics, keyword tools, content tools)
  2. Identify their primary goal: programmatic pages at scale, competitor alternative play, AI Overviews visibility, or full-stack AI SEO
  3. Ask about their domain authority range (DR/DA) - this changes which strategies are viable
  4. Understand their content production capacity (solo founder vs. team vs. agency)
  5. Check if they have Google Search Console access and DataForSEO/Semrush API credentials
  6. Identify their top 3-5 competitors for alternative page targeting
  7. Determine their CMS (Webflow, WordPress, Shopify, Next.js, custom) - this dictates the programmatic approach

1. AI SEO Stack - Tool Selection Framework

Core Tool Comparison

ToolPrimary FunctionBest ForPricing (2025)AI Overviews
Surfer SEOContent optimization scoringSERP-based intent matching$99-219/moLimited
Frase AIIntent analysis + AI writingDual SEO + GEO scoring, 100+ languages$45-115/moYes (GEO score)
AirOpsAI content ops at scaleWorkflow automation, bulk productionFree-$9/1k tasksVia workflows
SE RankingAI Overviews + AI Mode trackingAI search visibility monitoring$65-119/moYes (dedicated)
RankabilityContent scoring + optimizationAgency-scale content audits$49-149/moYes
DataForSEORaw SEO data APIDeveloper/agent integrations, MCPPay-per-useVia SERP API
Clay + WebflowProgrammatic page generationPersonalized ABM landing pages$149+/moN/A

Decision Matrix

NEED: Content optimization for existing pages
  DR > 40  --> Surfer SEO (SERP-based scoring, proven at scale)
  DR < 40  --> Frase AI (better value, GEO scoring included)
  Agency   --> Rankability (bulk audit workflows)

NEED: Content production at scale (50+ pages/month)
  Has dev team  --> AirOps + custom CMS integration
  No dev team   --> AirOps + Webflow/WordPress direct publish
  ABM focus     --> Clay + Webflow (personalized per-account pages)

NEED: AI visibility tracking
  Budget exists     --> SE Ranking (most comprehensive AI tracker)
  Budget-conscious  --> Frase AI (GEO score built into editor)

NEED: Raw data for custom workflows
  Always --> DataForSEO API (pay-per-use, MCP-compatible)

MCP Server Integration Stack

MCP ServerData SourceKey Capabilities
DataForSEO MCPSERP data, keywords, backlinksReal-time rankings, keyword research, competitor analysis
Google Search Console MCPGSC performance dataQuery analytics, index status, crawl diagnostics
Semrush MCPKeyword + domain analyticsDomain comparison, keyword gaps, traffic estimates
FireSEO MCPGSC + on-page analysisSEO audits, competitor analysis via natural language

DataForSEO MCP setup:

# Use env var or secret manager for credentials; never paste real keys into prompts or code.
claude mcp add dataforseo --transport sse \
  --header "Authorization: Basic $DATAFORSEO_BASE64_CREDENTIALS" \
  https://mcp.dataforseo.com/sse

GSC MCP setup:

git clone https://github.com/AminForou/mcp-gsc
cd mcp-gsc && pip install -r requirements.txt
claude mcp add gsc -- python /path/to/mcp-gsc/server.py

Agent workflow pattern:

  1. DataForSEO MCP: find top 50 keywords for [competitor] with volume > 500
  2. GSC MCP: show current rankings for those keywords
  3. Identify gaps where competitor ranks top 10 but you do not
  4. Generate content briefs using Frase or Surfer
  5. Produce content via AirOps workflows
  6. Monitor AI Overview citations via SE Ranking

2. The "[Competitor] Alternative" SEO Play

Why This Converts 3-5x Higher Than TOFU

BOFU keywords target buyers actively comparing solutions. "[Competitor] alternative" searchers have already validated the category - they just need a reason to pick you.

  • TOFU informational content: 0.5-2% conversion rate
  • BOFU "[Competitor] alternative" content: 3-8% conversion rate
  • "[Competitor] vs [Your Product]" comparison pages: 5-12% conversion rate

Target Keyword Patterns (Priority Order)

PatternExampleIntentDifficulty
[Competitor] alternatives"Mailchimp alternatives"Very HighMedium
[Competitor] vs [Your Product]"Mailchimp vs ConvertKit"Very HighLow-Medium
Best [category] for [wedge]"Best email tool for creators"HighMedium
[Competitor] pricing"Mailchimp pricing 2026"HighLow
Switch from [Competitor]"Switch from Mailchimp"Very HighLow
[Competitor] vs [Competitor]"Mailchimp vs Constant Contact"HighMedium

Page Template Structure

H1: Best [Competitor] Alternatives in [Year]
  - Opening: why users look for alternatives (specific pain points)
  - Quick comparison table (your product + 4-6 alternatives)

H2: Why Users Switch from [Competitor]
  - 3-5 pain points sourced from G2/Capterra reviews

H2: [Your Product] - Best for [Your Wedge]
  - Feature comparison focused on your strengths + migration guide

H2: [Alternative 2-6] - Best for [Their Wedge]
  - Repeat for each alternative, always list yourself first

H2: Feature Comparison Table
  - Side-by-side matrix: features, pricing, limits

H2: How to Choose the Right [Category] Tool
  - Decision framework by use case

H2: FAQ (with schema markup)
  - "Is [Your Product] better than [Competitor]?"
  - "How much does [Competitor] cost?"
  - "Can I migrate from [Competitor]?"

The Acquisition Playbook

ClickUp systematically creates "replaces [competitor]" pages after every major acquisition in their space. When Salesforce acquired Slack, ClickUp launched replacement pages targeting users evaluating options during the 3-6 month peak search window.

Replicable framework:

  1. Set Google Alerts for acquisitions in your category
  2. Within 48 hours: draft "[Acquired Tool] alternatives" page
  3. Within 2 weeks: publish full comparison + migration guide
  4. Target the 3-6 month window of peak search volume

3. Programmatic SEO - Scaling Pages with AI

Proven Page Patterns

PatternExampleData SourceScale
[Tool] for [Industry]"CRM for real estate"Industry list + features50-500
[Tool] vs [Competitor]"Airtable vs Notion"Competitor matrix20-200
[Service] in [City]"Plumber in Austin TX"City database500-5,000
[Metric] for [Company]"Revenue of Stripe"Company database1,000-30,000
[Template] for [Use Case]"Invoice for freelancers"Template library100-1,000
[Integration] + [Integration]"Slack + Salesforce"Integration pairs500-10,000

Architecture

+------------------+     +-------------------+     +------------------+
|  Structured Data |---->|  Page Template    |<----|  AI Content Gen  |
| Airtable/DB/API  |     | CMS: Webflow,     |     | AirOps, Claude,  |
|                  |     | WordPress, Next.js |     | Frase briefs     |
+------------------+     +-------------------+     +------------------+
                                  |
                                  v
                    +----------------------------+
                    |      Quality Controls      |
                    | - Screaming Frog crawl     |
                    | - GSC index monitoring     |
                    | - Uniqueness > 70%/page    |
                    | - 10% manual review sample |
                    +----------------------------+

Quality Requirements (Non-Negotiable)

Google's AI crawlers detect boilerplate. Pages that only swap 1-2 words will not rank. Every page needs:

  1. 500-1,000+ words of helpful content - not filler
  2. Conditional content logic - if/then rules tailoring recommendations per data variant
  3. Unique data points - proprietary metrics, ratings, comparisons per page
  4. Rich elements - HTML tables, charts, embedded tools
  5. Internal linking mesh - 3-5 related programmatic page links each
  6. Schema markup - FAQ, Product, or Review schema per page type

AirOps Workflow Example

[Tool] vs [Competitor] Page Generator:
  1. Input: CSV of tool pairs + feature categories
  2. Agent: Research each tool (pricing, features, reviews)
  3. Agent: Generate comparison sections per template
  4. Agent: Write unique intro + conclusion per pair
  5. Quality: Uniqueness score > 70%
  6. Publish: Push to WordPress/Webflow via API
  7. Monitor: GSC indexing check after 48 hours

Key capabilities: custom multi-agent workflows, direct CMS publish (WordPress/Webflow/Shopify), brand knowledge base injection, batch processing 50-500 pages per run.

Clay + Webflow for ABM Pages

For account-based marketing at scale:

  • Clay enriches company data (logo, industry, pain points, current tools)
  • Webflow CMS template maps Clay columns to dynamic fields
  • Auto-generated slugs: /for/[company-name]
  • Each page gets personalized hero, testimonials, case studies
  • Verkada uses this pattern for hundreds of ABM landing pages

Timeline

MilestoneTimeline
Pages indexed2-4 weeks
Initial traffic4-8 weeks
Meaningful organic growth3-6 months
ROI positive6-12 months

4. AI Overviews and Generative Engine Optimization (GEO)

The Split

AI Overviews appear in 15-50% of queries. Position 1 CTR drops 34.5% when present.

Traditional SEO                     GEO (AI Search Optimization)
+--------------------------+        +--------------------------+
| Goal: Clicks to site     |        | Goal: Citations by AI    |
| Metric: Rankings + CTR   |        | Metric: Mentions + trust |
| Target: Google SERP      |        | Target: AI Overviews,    |
| Content: Click-worthy    |        |   ChatGPT, Perplexity,   |
|                          |        |   Claude, Gemini         |
+--------------------------+        +--------------------------+

AI Overviews Optimization Checklist

  1. Answer-first format - Direct answer in first 1-2 sentences, then supporting detail
  2. Self-contained sections - Each H2/H3 independently understandable. Never "as mentioned above"
  3. Question-pattern headings - "What is [X]?", "How does [X] work?", "Best [X] for [Y]"
  4. Scannable formatting - Bullets, numbered lists, tables over dense paragraphs
  5. Entity optimization - Name specific tools, companies, people. Generic gets skipped
  6. Statistical backing - "Improved 3.2x" beats "improved significantly"
  7. Freshness signals - Dates, "Updated [Month] [Year]", reference recent events

GEO Platform Coverage

PlatformScaleCitation Behavior
Google AI Overviews15%+ of all queriesCites top-ranking pages with clear answers
ChatGPT800M+ weekly usersReferences authoritative, structured content
Perplexity100M+ monthlyExplicitly cites sources with links
Gemini750M+ monthlyPulls from Google index + Knowledge Graph

GEO Content Audit

  • Does every H2 answer a standalone question?
  • Can AI extract the answer from the first 2 sentences of each section?
  • Are specific entities named (tools, companies, metrics)?
  • Are statistics cited with sources?
  • Does the page have FAQ schema with direct answers?
  • Is content structured with lists and tables?
  • Are "Updated [Month] [Year]" timestamps present?

SE Ranking for AI Visibility Tracking

AI Overviews Tracker: estimates traffic from Overviews, tracks which keywords trigger them, shows citation status (cited/not cited/competitor cited).

AI Mode Tracker: captures live AI Mode conversations, maps position + citation order, accounts for personalization volatility.

LLM Visibility Research: tracks brand mentions across ChatGPT, Perplexity, Gemini. "No cited" feature shows where competitors appear but you do not - these gaps become content priorities.

Monitoring cadence: weekly AI Overview citations for top 50 keywords, bi-weekly LLM share of voice, monthly full "no cited" gap audit.


5. Keyword Strategy Framework

Three-Layer Architecture

Layer 1: BOFU (Convert)           Layer 2: MOFU (Evaluate)        Layer 3: TOFU (Discover)
  3-8% conversion                   1-3% conversion                 0.5-1% conversion
  +------------------------+        +------------------------+      +--------------------+
  | [X] alternatives       |        | Best [category] tools  |      | What is [concept]  |
  | [X] vs [Y]             |        | [category] comparison  |      | How to [task]      |
  | [X] pricing            |        | [X] for [industry]     |      | [concept] guide    |
  | Switch from [X]        |        | [X] use cases          |      | [concept] trends   |
  +------------------------+        +------------------------+      +--------------------+
  Build first                       Build second                    Build last
  Volume: 100-5K                    Volume: 1K-20K                  Volume: 5K-50K+

Keyword Research Workflow (MCP-powered)

Step 1: DataForSEO MCP - keyword suggestions for category, volume > 100, KD < 50, grouped by intent Step 2: DataForSEO/Semrush MCP - competitor keyword gap (they rank top 10, you do not), commercial intent only Step 3: SE Ranking - which target keywords trigger AI Overviews, flag "ranked but not cited" gaps Step 4: Prioritize content calendar:

PriorityCriteriaAction
P0BOFU, volume > 200, KD < 40Create this week
P1BOFU, volume > 200, KD 40-60Create this month
P2MOFU, volume > 500, KD < 50Create next month
P3AI Overview gap (ranked, not cited)Optimize existing page
P4TOFU, volume > 2000, KD < 40Backlog

6. Content Production Pipeline

AI Content Quality Spectrum

Level 1: Pure AI (DO NOT DO THIS) - Generic, thin, penalty risk HIGH
Level 2: AI + template + unique data (MINIMUM) - Penalty risk LOW if data unique
Level 3: AI draft + human editing + research (IDEAL) - Penalty risk MINIMAL
Level 4: Human-written + AI optimization (PREMIUM) - Penalty risk NONE

Pipeline

Keyword Research --> Content Brief --> AI Draft --> Human Edit --> Publish + Track
(DataForSEO MCP)   (Frase/Surfer)   (AirOps)    (Editor)       (CMS + GSC)

Content Brief Template

Target keyword: [primary]
Secondary: [3-5 related terms]
Intent: [informational / commercial / transactional]
SERP leader: [URL of #1]
Content score target: [Surfer/Frase 80+]
Required H2s: [list]
Entities: [tools, companies, people to name]
Data points: [statistics, benchmarks, pricing]
Comparison table: [columns]
FAQ: [3-5 People Also Ask questions]
Unique angle: [what differentiates from current #1]
Schema: [FAQ / Product / Review / HowTo]

7. Technical SEO for Programmatic Pages

Indexing: XML sitemap with all pages in GSC. IndexNow API for instant indexing. Monitor "Discovered - not indexed" in coverage report. Correct canonicals per page.

Speed: SSG preferred (Next.js, Astro, Webflow). Lazy-load below-fold. Core Web Vitals: LCP < 2.5s, CLS < 0.1, INP < 200ms. CDN for all assets.

Internal linking mesh:

"CRM for Real Estate" links to:
  - "CRM for Small Business" (related)
  - "Salesforce vs HubSpot" (comparison)
  - "Best CRM Software 2026" (parent category)

Schema per page type: FAQ schema for alternative pages, Product schema with aggregateRating for comparison pages, HowTo schema for guide pages.


8. Measurement and Iteration

MetricToolCadenceTarget
Organic trafficGSC / GA4WeeklyMoM growth
Rankings (top 10)DataForSEO / SE RankingWeekly20%+ of targets
AI Overview citationsSE Ranking AI TrackerWeekly30%+ of ranked keywords
Indexed pagesGSC CoverageWeekly95%+ published
Content scoreSurfer / FrasePer publish80+
BOFU conversion rateGA4Monthly3-8% alternative pages
LLM mention rateSE Ranking LLM TrackerBi-weeklyGrowing share of voice

Monthly Iteration Cycle

  1. Pull GSC data via MCP: top growing + declining pages
  2. Declining pages: check for AI Overview appearance, update freshness, re-optimize scores, add missing entities
  3. Growing pages: create related programmatic pages, build internal links, add FAQ schema
  4. "Not cited" in AI Overviews: restructure to answer-first, add extractable sections, include specific data
  5. Unindexed pages: check for thin content (< 500 words unique), verify no cannibalization, resubmit via IndexNow

Examples

  • User says: "Build programmatic SEO for our product" → Result: Agent asks domain rating and competitor set; recommends BOFU keywords and competitor-alternative pages (10–20); outlines template + data source (Airtable/API) + AI workflow (AirOps or custom); suggests quality controls, schema, internal links, and GSC + AI Overviews tracking.
  • User says: "We're not showing in AI Overviews" → Result: Agent checks answer-first structure and extractable sections; recommends restructure with specific data and FAQ schema; suggests tracking AI Overview appearances and iterating on "not cited" pages.
  • User says: "What tools for AI SEO?" → Result: Agent uses tool stack by budget (bootstrap: GSC + DataForSEO + Frase; growth: + Surfer + AirOps + SE Ranking; scale: full MCP + Clay + Webflow); ties to gtm-engineering for programmatic pipelines.

Troubleshooting

  • Thin or duplicate content → Cause: <500 words unique or cannibalization. Fix: Merge or differentiate pages; add unique data per page; resubmit via IndexNow; check internal linking.
  • Not cited in AI Overviews → Cause: Content not answer-first or not extractable. Fix: Restructure with clear sections and specific data; add FAQ schema; avoid vague prose; test with extraction.
  • Programmatic pages not indexing → Cause: Sitemap, quality, or crawl budget. Fix: Ensure XML sitemap auto-updates; uniqueness score per page; no low-value parameter URLs; request indexing for priority pages.

Quick Reference

Launch Checklist

[ ] Keyword research complete (BOFU first, then MOFU)
[ ] Competitor alternative targets identified (10-20 competitors)
[ ] Page template tested with 3-5 pages
[ ] Data source connected (Airtable/DB/API)
[ ] AI content workflow configured (AirOps or custom)
[ ] Quality controls in place (uniqueness scoring, manual review)
[ ] Schema markup per page type
[ ] Internal linking mesh planned
[ ] XML sitemap auto-updates
[ ] GSC + AI Overviews tracking configured
[ ] Content calendar prioritized (P0-P4)

Tool Stack by Budget

Bootstrap ($0-100/mo):
  GSC (free) + DataForSEO (pay-per-use) + Frase Starter ($45/mo)

Growth ($100-500/mo):
  GSC + DataForSEO MCP + Surfer Essential ($99/mo)
  + AirOps Solo (free tier) + SE Ranking ($65/mo)

Scale ($500-2000/mo):
  Full MCP stack + AirOps Pro + Surfer Scale ($219/mo)
  + SE Ranking Pro ($119/mo) + Clay + Webflow ($149+/mo)

Enterprise ($2000+/mo):
  All above + Rankability + custom Next.js programmatic system

Questions to Ask

  1. "What's your current domain rating? This determines whether we start with low-competition BOFU keywords or need to build authority first."
  2. "Which 5 competitors do your customers most often compare you against? These become alternative page targets."
  3. "Do you have a structured data source (product database, company list, feature matrix) for programmatic pages?"
  4. "What CMS are you on? Webflow and WordPress have the strongest programmatic SEO support."
  5. "Are you tracking AI Overview appearances for your keywords?"
  6. "What is your monthly content production capacity?"
  7. "Do you have DataForSEO or Semrush API access?"
  8. "Is your content structured for AI extraction - self-contained sections, answer-first format, specific data?"

Related Skills

  • content-to-pipeline - Connect SEO content to lead capture and pipeline generation
  • multi-platform-launch - Coordinate SEO content with multi-channel product launches
  • positioning-icp - Define positioning and ICP that informs keyword targeting and page messaging
  • social-selling - Amplify SEO content through social distribution for link building
  • gtm-engineering - Build technical infrastructure for programmatic page generation and data pipelines

平台分布

Codex

37.61%
按下载量换算115

Claude

30.97%
按下载量换算95

Cursor

17.69%
按下载量换算54

Gemini CLI

8.53%
按下载量换算26

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

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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