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seo-content-factory

Generate fully SEO-optimized blog posts and articles with keyword research, competitor analysis, and SERP-aware content. Use when creating SEO content, blog posts, articles, or content for clients.

DeepseekModel キュレーション済みスキル 品質 良好 · 64 v1.0.0

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https://deepseekmodel.com/api/download.php?id=modbender-skill-library-mcp-data-seo-content-factory-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name seo-content-factory description Generate fully SEO-optimized blog posts and articles with keyword research, competitor analysis, and SERP-aware content. Use when creating SEO content, blog posts, articles, or content for clients. argument-hint [keyword-or-topic] [word-count] allowed-tools Read, Write, Grep, Glob, Bash, WebFetch, WebSearch SEO Content Factory End-to-end SEO content pipeline: from keyword to publish-ready article. Produces content that ranks. How to Use /seo-content-factory "best project management tools for freelancers" 2000 /seo-content-factory "how to start a dropshipping business" /seo-content-factory batch keywords.txt $ARGUMENTS[0] = Target keyword or topic (or "batch" for multiple) $ARGUMENTS[1] = Word count (default: 1,500) For batch mode, provide a file with one keyword per line Content Generation Pipeline Phase 1: Keyword Intelligence For the target keyword $ARGUMENTS[0] : Search the keyword to understand current SERP landscape Identify : Search intent (informational, transactional, navigational, commercial) Content format that ranks (listicle, how-to, comparison, guide, review) Average word count of top 5 results Common subtopics and questions covered Related keywords and LSI terms Generate a keyword cluster : Primary keyword 3-5 secondary keywords 5-10 long-tail variations 3-5 related questions (People Also Ask style) Phase 2: Competitor Content Analysis Analyze top 5 SERP results for the target keyword: Content gaps : What do ALL top results miss? This is our opportunity. Common structure : How are they organized? (H2/H3 patterns) Unique angles : What perspective hasn't been covered? Content freshness : Are top results outdated? Can we provide 2026 data? Backlink bait : What makes content in this niche linkable? Phase 3: Content Architecture Build the article structure BEFORE writing: Title: [Primary keyword + compelling modifier] Meta Description: [150-160 chars, includes primary keyword, has CTA] URL Slug: [primary-keyword-short-form] H1: [Title] Introduction (100-150 words) - Hook with statistic or question - Promise what the reader will learn - Include primary keyword naturally H2: [Section based on search intent] H3: [Subsection] H3: [Subsection] H2: [Section covering competitor gap] H3: [Subsection] H2: [Unique angle section] H2: [FAQ section - from People Also Ask] H3: [Question 1] H3: [Question 2] H3: [Question 3] Conclusion (100-150 words) - Summarize key takeaways - Clear CTA Phase 4: Content Writing Write the article following these SEO content rules: Keyword Placement (non-negotiable): Primary keyword in: title, H1, first 100 words, 1-2 H2s, last 100 words, meta description Keyword density: 1-2% (natural, never forced) Secondary keywords: 1-2 uses each, spread throughout Long-tail variations: use naturally in body and H3s Readability : Flesch-Kincaid grade level: 6-8 (accessible to all readers) Sentences: max 20 words average Paragraphs: max 3-4 sentences Use bullet points and numbered lists liberally Include a table or comparison if the topic allows Break up text with H2 every 200-300 words Engagement : Open with a hook (statistic, question, bold claim) Use "you" and "your" throughout (conversational tone) Include specific numbers and data points Add actionable takeaways (not just information) End sections with transitions to the next E-E-A-T Signals (Experience, Expertise, Authoritativeness, Trustworthiness): Include first-person experience markers ("In my experience...", "When I tested...") Reference specific tools, processes, or methodologies by name Cite statistics with implied sources Provide nuanced opinions, not just generic advice Phase 5: On-Page SEO Elements Generate these alongside the article: title_tag: "[Primary Keyword] - [Modifier] | [Brand]" (50-60 chars) meta_description: "[Benefit statement with primary keyword and CTA]" (150-160 chars) url_slug: "[primary-keyword]" primary_keyword: "[keyword]" secondary_keywords: [ "kw1" , "kw2" , "kw3" ] word_count: [ actual count ] reading_time: "[X] min read" content_type: "[listicle|how-to|guide|comparison|review]" search_intent: "[informational|transactional|commercial|navigational]" Internal linking suggestions : 3-5 recommended internal link anchor texts and target topics External linking suggestions : 2-3 authoritative sources to cite Image suggestions : 3-5 image descriptions with recommended alt text containing keywords Schema markup : Provide appropriate schema (Article, FAQ, HowTo) in JSON-LD format Phase 6: Output Format Deliver the final article in TWO formats: Clean Markdown — for CMS systems, Ghost, Hugo, Jekyll WordPress-ready HTML — with proper heading tags, schema markup embedded, and meta tags as HTML comments at the top <!-- SEO Meta Title: [title tag] Description: [meta description] Slug: [url-slug] Keywords: [primary], [secondary1], [secondary2] --> < article > < h1 > ... </ h1 > ... </ article > < script type = "application/ld+json" > {schema markup} </ script > Batch Mode When $ARGUMENTS[0] is "batch", read the keyword file from $ARGUMENTS[1] and generate articles for each keyword. For each article: Run the full pipeline above Save each article as output/[url-slug].md and output/[url-slug].html Generate an index file output/batch-summary.md with: All articles generated Primary and secondary keywords for each Word counts Suggested publishing order (based on keyword difficulty — easier first) Internal linking map between the articles Quality Checks Before delivering, verify: Primary keyword appears in title, H1, first 100 words, meta description Keyword density is 1-2% (not stuffed) All H2/H3 headings are descriptive (not "Introduction" or "Conclusion") FAQ section uses actual questions people search for Article is longer than average competing content At least one table, list, or visual element per 500 words Schema markup is valid JSON-LD Meta description is 150-160 characters Title tag is 50-60 characters No fluff paragraphs — every paragraph earns its place
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
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.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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