본문으로 건너뛰기
cccskills
무료GitHub에 공개

"algo-seo-content"

"Execute content SEO strategy from keyword research through content planning, writing, and on-page optimization. Use this skill when the user needs to create SEO-optimized content, perform keyword research, identify content gaps, or improve existing content rankings — even if they say 'content strategy', 'keyword research', or 'how to rank for this topic'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

실행 점수 미검증

설치 방법 보기

포함된 파일(4)

  • SKILL.md4.5 KB
  • examples/sample_scenario.md6.9 KB
  • references/content-brief-template.md10.0 KB
  • references/keyword-clustering.md6.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Content SEO Strategy

Overview

Content SEO is the systematic process of creating and optimizing content to match search intent and rank organically. The pipeline: keyword research → intent mapping → content creation → on-page optimization → performance monitoring. Success depends on intent match, not keyword density.

When to Use

Trigger conditions:

  • Planning new content to capture organic search traffic
  • Optimizing existing underperforming content
  • Conducting keyword research and content gap analysis

When NOT to use:

  • When the issue is technical (page speed, crawlability) — use technical SEO
  • When the issue is off-page (backlinks, authority) — use backlink analysis

Algorithm

IRON LAW: Content Must Match SEARCH INTENT
A perfectly optimized page targeting the wrong intent will NOT rank.
Four intent types:
1. Informational — wants to learn ("how to", "what is")
2. Navigational — wants a specific site ("github login")
3. Commercial — comparing options ("best CRM 2025")
4. Transactional — wants to buy/do ("buy iPhone 16 case")
Check SERP results to determine actual intent before writing.

Phase 1: Input Validation

Define target topic/niche. Gather seed keywords from brainstorming, competitor analysis, and tools (Ahrefs, SEMrush, Google Keyword Planner). Gate: Seed keyword list with search volume and difficulty estimates.

Phase 2: Core Algorithm

  1. Keyword clustering: Group related keywords by intent and topic
  2. SERP analysis: Check top 10 results for each cluster — identify intent, content format, and depth
  3. Content gap analysis: Find keywords competitors rank for that you don't
  4. Content brief: Define: target keyword, intent, format (guide/list/comparison), word count benchmark, required subtopics from SERP analysis
  5. On-page optimization: Title tag (keyword front-loaded), meta description, H1/H2 structure, internal links, image alt text

Phase 3: Verification

Check: title contains primary keyword, intent matches SERP, all key subtopics covered, internal links to related content. Gate: Content matches identified intent and covers SERP-derived subtopics.

Phase 4: Output

Return content brief and optimization checklist.

Output Format

{
  "content_brief": {"primary_keyword": "...", "intent": "informational", "format": "how-to guide", "target_word_count": 2000, "subtopics": ["...", "..."]},
  "optimization": {"title": "...", "meta_description": "...", "h2_structure": ["...", "..."], "internal_links": 5},
  "metadata": {"search_volume": 2400, "keyword_difficulty": 35}
}

Examples

Sample I/O

Input: Topic "email marketing automation", target market: Taiwan SMBs Expected: Primary KW: "email行銷自動化", intent: commercial investigation, format: comparison guide, 2500 words

Edge Cases

InputExpectedWhy
Zero search volume keywordConsider if it's emerging or nonexistentMay be worth targeting if topically relevant
KD > 80 for new siteTarget long-tail variants firstNew sites can't compete on high-KD terms
Mixed intent SERPCreate content matching dominant intentDon't try to serve all intents in one page

Gotchas

  • Keyword density is dead: There's no optimal keyword density. Write naturally. Forced keyword insertion hurts readability and may trigger spam signals.
  • Search volume ≠ traffic: A #1 ranking for a 10K volume keyword won't bring 10K visits. Click-through rates vary by SERP features (ads, featured snippets, PAA).
  • Content freshness: Some queries demand fresh content (e.g., "best laptop 2025"). Outdated content drops rankings even if it once ranked #1.
  • Cannibalization: Multiple pages targeting the same keyword compete with each other. One strong page outperforms three mediocre ones.
  • E-E-A-T: For YMYL topics (health, finance), Google requires demonstrated Experience, Expertise, Authority, and Trust. Anonymous content won't rank.

References

  • For keyword clustering methodology, see references/keyword-clustering.md
  • For content brief templates, see references/content-brief-template.md

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

"Implement and select ad bidding strategies from manual CPC to automated target-CPA and target-ROAS. Use this skill when the user needs to choose a bidding strategy, set up automated bidding, or optimize bid parameters — even if they say 'what bidding strategy should I use', 'target CPA setup', or 'smart bidding configuration'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

charlieviettq/awesome-agent-skill262026년 7월 20일 업데이트

"Optimize advertising budget allocation across campaigns using marginal returns analysis. Use this skill when the user needs to distribute budget across multiple campaigns, optimize spend pacing, or maximize overall ROAS under budget constraints — even if they say 'how to split my ad budget', 'campaign budget optimization', or 'diminishing returns on ad spend'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

charlieviettq/awesome-agent-skill262026년 7월 20일 업데이트

"Build CTR prediction models for estimating ad click-through rates from features. Use this skill when the user needs to predict click probability, build an ad ranking model, or evaluate ad creative performance — even if they say 'predict click rate', 'ad relevance scoring', or 'which ad will get more clicks'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

charlieviettq/awesome-agent-skill262026년 7월 20일 업데이트

"Implement Generalized Second Price auction for ad slot allocation and pricing. Use this skill when the user needs to understand search ad auctions, compute ad positions and costs-per-click, or analyze bidding dynamics — even if they say 'how does Google Ads auction work', 'ad rank calculation', or 'second price auction for ads'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

charlieviettq/awesome-agent-skill262026년 7월 20일 업데이트

"Implement VCG mechanism for incentive-compatible ad slot allocation with truthful bidding. Use this skill when the user needs to design a truthful auction mechanism, compute externality-based payments, or understand why platforms may prefer GSP over VCG — even if they say 'truthful auction design', 'VCG payments', or 'incentive-compatible mechanism'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

charlieviettq/awesome-agent-skill262026년 7월 20일 업데이트

"Explain blockchain fundamentals including distributed ledger architecture, consensus mechanisms, and block structure. Use this skill when the user needs to understand blockchain concepts, evaluate whether blockchain fits a use case, or design a blockchain-based solution — even if they say 'how does blockchain work', 'do I need blockchain', or 'distributed ledger'.".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

charlieviettq/awesome-agent-skill262026년 7월 20일 업데이트

charlieviettq의 스킬 모두 보기

이 스킬의 문제 신고