ascii-preview-generate
PDFページのレイアウトをAIで解析し、文字や図形をASCII文字で表現することで、HTML生成に適した構造化されたプレビューをテキスト形式で作成するSkill。
📜 元の英語説明(参考)
Use AI to create ASCII text-based preview of PDF page layout. Transforms visual and extracted data into structured ASCII representation for HTML generation.
🇯🇵 日本人クリエイター向け解説
PDFページのレイアウトをAIで解析し、文字や図形をASCII文字で表現することで、HTML生成に適した構造化されたプレビューをテキスト形式で作成するSkill。
※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。
下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o ascii-preview-generate.zip https://jpskill.com/download/16956.zip && unzip -o ascii-preview-generate.zip && rm ascii-preview-generate.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/16956.zip -OutFile "$d\ascii-preview-generate.zip"; Expand-Archive "$d\ascii-preview-generate.zip" -DestinationPath $d -Force; ri "$d\ascii-preview-generate.zip"
完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。
💾 手動でダウンロードしたい(コマンドが難しい人向け)
- 1. 下の青いボタンを押して
ascii-preview-generate.zipをダウンロード - 2. ZIPファイルをダブルクリックで解凍 →
ascii-preview-generateフォルダができる - 3. そのフォルダを
C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-18
- 取得日時
- 2026-05-18
- 同梱ファイル
- 1
📖 Skill本文(日本語訳)
※ 原文(英語/中国語)を Gemini で日本語化したものです。Claude 自身は原文を読みます。誤訳がある場合は原文をご確認ください。
ASCII Preview Generate Skill
目的
この Skill は、AI を使用して、PDF ページのレイアウトの意味のある ASCII テキストベースの表現を作成することを目的としています。AI は以下を行います。
- PDF ページの画像と抽出されたテキストデータの両方を分析します
- ページ構成を示す構造化された ASCII プレビューを作成します
- 見出しの階層、段落、リスト、およびテーブルを視覚的に表現します
- ダウンストリームの HTML 生成のための明確な構造的コンテキストを提供します
ASCII プレビューは、ページレイアウトの構造化された表現として機能し、ダウンストリームの AI-HTML ジェネレーターが視覚的なレイアウトとコンテンツ構造の両方を理解できるようにします。
実施事項
-
入力ファイルをロードする
02_page_XX.png(視覚的な参照) を読み込みます01_rich_extraction.json(メタデータ付きのテキストスパン) を読み込みます- 必要なフィールドがすべて存在することを確認します
-
AI を呼び出して分析および表現する
- PNG 画像を Claude に送信します (視覚的な参照)
- 抽出されたテキストデータ (JSON) を含めます
- ASCII レイアウト表現をリクエストします
- AI が構造と関係を決定します
-
AI が ASCII プレビューを生成する
- AI が抽出データから見出しの階層を分析します
- AI が段落とその関係を識別します
- AI がリストを適切なフォーマットで表現します
- AI がテーブルレイアウトが存在する場合は表示します
- AI が ASCII 文字を使用して視覚的な表現を作成します
-
ASCII 出力を検証する
- 出力が読み取り可能なテキストであることを確認します
- すべてのコンテンツ要素が表現されていることを確認します
- 構造が明確で論理的であることを確認します
-
永続的なファイルに保存する
- 保存先:
output/chapter_XX/page_artifacts/page_YY/03_page_XX_ascii.txt - メタデータ (ページ番号、章、タイムスタンプ) を含めます
- 保存先:
入力パラメータ
rich_extraction_file: <str> - 01_rich_extraction.json へのパス
page_png: <str> - 02_page_XX.png へのパス (オプション、視覚的な検証用)
output_file: <str> - ASCII プレビューの保存パス
book_page: <int> - 書籍のページ番号 (表示用)
chapter: <int> - 章番号 (表示用)
出力形式
ASCII プレビューの構造
ASCII プレビューは、次の構造を使用します。
================================================================================
PAGE XX ASCII LAYOUT PREVIEW
================================================================================
Book Page: YY | Chapter: Z | PDF Index: XX | Dimensions: 612x792px
--------------------------------------------------------------------------------
[ASCII アートと注釈付きのページコンテンツ]
STRUCTURE SUMMARY:
[要素の数と種類]
================================================================================
出力例
================================================================================
PAGE 16 ASCII LAYOUT PREVIEW
================================================================================
Book Page: 17 | Chapter: 2 | PDF Index: 16 | Dimensions: 612x792px
--------------------------------------------------------------------------------
┌─────────────────────────────────────────────────────────────────────────┐
│ │
│ [H1 Heading - 27pt Bold] │
│ ████████████████████████████████ │
│ █ Rights in Real Estate █ │
│ ████████████████████████████████ │
│ │
│ ───────────────────────────────────────────────────────────────── │
│ [Divider] │
│ │
│ [H2 Section Heading - 11pt Bold All-Caps] │
│ REAL PROPERTY RIGHTS │
│ │
│ [Paragraph 1 - 11pt Regular] │
│ Real property consists of physical land and the legal rights │
│ associated with ownership. These rights form what is commonly │
│ referred to as the "bundle of rights." │
│ │
│ [H4 Subsection - 11pt Bold] │
│ Physical characteristics. │
│ │
│ [Paragraph 2 - 11pt Regular] │
│ Land has unique physical characteristics that distinguish it from │
│ other types of assets. The most important characteristics include: │
│ │
│ [Bullet List - 3 items] │
│ ▶ Immobility - Land cannot be moved from one location to │
│ another. This fact has significant legal and economic │
│ implications. │
│ ▶ Indestructibility - Land is permanent and cannot be │
│ destroyed. Although structures on land can be destroyed, │
│ the land itself endures. │
│ ▶ Uniqueness - Each parcel of land is unique due to its │
│ location. "Not two parcels of land are exactly alike due to │
│ their geographic location." │
│ │
│ [H4 Subsection - 11pt Bold] │
│ Interdependence. │
│ │
│ [Paragraph 3 - 11pt Regular]
(原文がここで切り詰められています) 📜 原文 SKILL.md(Claudeが読む英語/中国語)を展開
ASCII Preview Generate Skill
Purpose
This skill uses AI to create a meaningful ASCII text-based representation of the PDF page layout. The AI:
- Analyzes both the PDF page image and extracted text data
- Creates a structured ASCII preview showing page organization
- Represents heading hierarchy, paragraphs, lists, and tables visually
- Provides clear structural context for downstream HTML generation
The ASCII preview serves as a structured representation of page layout, enabling the downstream AI-HTML generator to understand both visual layout and content structure.
What to Do
-
Load input files
- Read
02_page_XX.png(visual reference) - Read
01_rich_extraction.json(text spans with metadata) - Verify all required fields present
- Read
-
Invoke AI to analyze and represent
- Send PNG image to Claude (visual reference)
- Include extracted text data (JSON)
- Request ASCII layout representation
- AI determines structure and relationships
-
AI generates ASCII preview
- AI analyzes heading hierarchy from extraction data
- AI identifies paragraphs and their relationships
- AI represents lists with proper formatting
- AI shows table layouts if present
- AI creates visual representation using ASCII characters
-
Validate ASCII output
- Verify output is readable text
- Check that all content elements represented
- Confirm structure is clear and logical
-
Save to persistent file
- Save to:
output/chapter_XX/page_artifacts/page_YY/03_page_XX_ascii.txt - Include metadata (page number, chapter, timestamp)
- Save to:
Input Parameters
rich_extraction_file: <str> - Path to 01_rich_extraction.json
page_png: <str> - Path to 02_page_XX.png (optional, for visual validation)
output_file: <str> - Path to save ASCII preview
book_page: <int> - Book page number (for display)
chapter: <int> - Chapter number (for display)
Output Format
ASCII Preview Structure
The ASCII preview uses this structure:
================================================================================
PAGE XX ASCII LAYOUT PREVIEW
================================================================================
Book Page: YY | Chapter: Z | PDF Index: XX | Dimensions: 612x792px
--------------------------------------------------------------------------------
[PAGE CONTENT WITH ASCII ART AND ANNOTATIONS]
STRUCTURE SUMMARY:
[Element counts and types]
================================================================================
Example Output
================================================================================
PAGE 16 ASCII LAYOUT PREVIEW
================================================================================
Book Page: 17 | Chapter: 2 | PDF Index: 16 | Dimensions: 612x792px
--------------------------------------------------------------------------------
┌─────────────────────────────────────────────────────────────────────────┐
│ │
│ [H1 Heading - 27pt Bold] │
│ ████████████████████████████████ │
│ █ Rights in Real Estate █ │
│ ████████████████████████████████ │
│ │
│ ───────────────────────────────────────────────────────────────── │
│ [Divider] │
│ │
│ [H2 Section Heading - 11pt Bold All-Caps] │
│ REAL PROPERTY RIGHTS │
│ │
│ [Paragraph 1 - 11pt Regular] │
│ Real property consists of physical land and the legal rights │
│ associated with ownership. These rights form what is commonly │
│ referred to as the "bundle of rights." │
│ │
│ [H4 Subsection - 11pt Bold] │
│ Physical characteristics. │
│ │
│ [Paragraph 2 - 11pt Regular] │
│ Land has unique physical characteristics that distinguish it from │
│ other types of assets. The most important characteristics include: │
│ │
│ [Bullet List - 3 items] │
│ ▶ Immobility - Land cannot be moved from one location to │
│ another. This fact has significant legal and economic │
│ implications. │
│ ▶ Indestructibility - Land is permanent and cannot be │
│ destroyed. Although structures on land can be destroyed, │
│ the land itself endures. │
│ ▶ Uniqueness - Each parcel of land is unique due to its │
│ location. "Not two parcels of land are exactly alike due to │
│ their geographic location." │
│ │
│ [H4 Subsection - 11pt Bold] │
│ Interdependence. │
│ │
│ [Paragraph 3 - 11pt Regular] │
│ All land exists in relation to other land. Therefore, the value │
│ of land is dependent on the land around it... │
│ │
└─────────────────────────────────────────────────────────────────────────┘
STRUCTURE SUMMARY:
─────────────────
Page Type: Chapter Continuation
Total Elements: 12
Headings (3):
• H1: 1 instance (27pt, bold) - "Rights in Real Estate"
• H2: 1 instance (11pt, bold, all-caps) - "REAL PROPERTY RIGHTS"
• H4: 2 instances (11pt, bold) - "Physical characteristics", "Interdependence"
Paragraphs (3):
• Body text: 3 paragraphs total
• Average paragraph length: ~45 words
• Text flow: Top to bottom, left to right
Lists (1):
• Bullet list with 3 items
• Indentation: 2em from left margin
• Separator: "▶" character
Tables: 0
Images: 0
Font Summary:
• 27pt: 1 instance (heading)
• 11pt: 7 instances (body, subsections, lists)
• Total unique fonts: 2 (Arial-Bold, Times-Regular)
Confidence Assessment:
• Heading hierarchy: 100% confident
• Element types: 95% confident
• Content flow: 90% confident
• (Lower confidence = ambiguous or unusual formatting)
================================================================================
AI Prompt Template
The prompt sent to Claude to generate ASCII preview:
You are creating an ASCII text-based layout preview of a PDF page.
VISUAL REFERENCE (PDF Page):
[PNG Image Attached]
EXTRACTED TEXT DATA:
[JSON Attached]
TASK:
Generate an ASCII text representation of this page's layout and structure.
REQUIREMENTS:
1. ASCII Format:
- Use box drawing characters for visual clarity (┌─┐│└┘)
- Show page boundaries
- Use spacing to represent actual layout
2. Element Representation:
- Headings: Show in ASCII, mark with [H1], [H2], [H3], [H4]
- Paragraphs: Show first line, indicate continuation
- Lists: Use ▶ or • characters, maintain structure
- Tables: Show column alignment and structure
- Spacing: Represent actual gaps between elements
3. Annotations:
- Label each element type [Heading], [Paragraph], [List], etc.
- Show font size context (11pt, 27pt, etc.)
- Note text styling (Bold, All-Caps, etc.)
4. Summary Statistics:
- Count headings by level (h1, h2, h3, h4)
- Count paragraphs
- Count lists and items
- Note any tables or images
5. Readability:
- Keep lines under 80 characters
- Use clear visual separation
- Make structure obvious at a glance
OUTPUT:
================================================================================ PAGE XX ASCII LAYOUT PREVIEW
Book Page: YY | Chapter: Z | PDF Index: XX
[ASCII representation with visual structure]
STRUCTURE SUMMARY: [Element counts and types]
VALIDATION:
- ASCII must be readable text
- All major content elements must be represented
- Structure must be clear and logical
- Total elements count must match data
AI Generation Process
-
Load inputs
02_page_XX.png- Visual reference01_rich_extraction.json- Text spans with metadata
-
Invoke Claude API
- Send image as multi-modal input
- Include extracted data in prompt
- Request ASCII layout preview
-
Extract and validate output
- Parse ASCII from response
- Verify readability
- Check element representation
-
Save to file
- Write to
output/chapter_XX/page_artifacts/page_YY/03_page_XX_ascii.txt
- Write to
Quality Checks
Before declaring ASCII preview complete:
-
File output
- [ ] Output file created and readable
- [ ] File is valid text (UTF-8 encoding)
- [ ] File size meaningful (> 500 bytes)
-
Content representation
- [ ] All major page elements represented
- [ ] Heading hierarchy shown clearly
- [ ] Paragraphs indicated and readable
- [ ] Lists properly formatted with bullets/markers
- [ ] Tables (if present) shown with alignment
-
Accuracy against source data
- [ ] Structure matches rich_extraction.json
- [ ] Element counts reasonable
- [ ] Text content accurate (no changes)
- [ ] Layout represents visual (PNG) appearance
-
Readability and format
- [ ] ASCII art is clear and clean
- [ ] Line length reasonable (< 100 chars)
- [ ] Box drawing characters render properly
- [ ] Annotations are clear and helpful
- [ ] Summary section present and accurate
Output Metadata
{
"preview_file": "03_page_16_ascii.txt",
"page": 16,
"book_page": 17,
"chapter": 2,
"generated_at": "2025-11-08T14:31:00Z",
"source_file": "01_rich_extraction.json",
"elements_detected": {
"headings": 4,
"paragraphs": 3,
"lists": 1,
"tables": 0,
"images": 0
},
"confidence_scores": {
"overall": 0.93,
"heading_hierarchy": 1.0,
"element_types": 0.95,
"content_flow": 0.90
}
}
Use in Downstream Processing
The ASCII preview is used by Skill 3 (ai-html-generate) as one of three inputs:
02_page_XX.png- Visual reference (pixel data)01_rich_extraction.json- Parsed text with metadata03_page_XX_ascii.txt- Structural representation ← This skill creates
Together, these three inputs give the AI complete context for accurate HTML generation.
Error Handling
If PNG image fails to load:
- Fall back to text-only analysis using rich_extraction.json
- AI still generates ASCII but without visual reference
- Note in metadata: "Image unavailable"
- Proceed (text data is sufficient for structure)
If rich_extraction.json is invalid:
- Use PNG image and AI visual analysis
- Attempt ASCII generation from visual alone
- Log warning about missing text data
- Proceed with AI best judgment
If AI response is not valid text:
- Validate encoding and line breaks
- Retry request if necessary
- Escalate if repeated failures
If ASCII structure seems incomplete:
- AI may have missed elements due to image quality
- Downstream HTML generation has visual reference for verification
- Quality gates will catch if output is insufficient
Success Criteria
✓ ASCII preview file created successfully ✓ File contains all page elements in structured format ✓ Heading hierarchy is clear and logical ✓ All text content included and readable ✓ Summary statistics accurate ✓ File is well-formatted and unambiguous ✓ Ready for AI HTML generation with complete context
Next Steps
Once ASCII preview is complete:
- Skill 3 (ai-html-generate) uses this + PNG + extraction for HTML
- AI has maximum context: visual (PNG) + text (extraction) + structure (ASCII)
- Result is accurate, semantically correct HTML
Troubleshooting
ASCII preview is incomplete: Check source rich_extraction.json has all text spans Heading hierarchy looks wrong: Verify font sizes in extraction data Lists not detected: Check for bullet character encoding issues Spacing is off: Ensure coordinate system matches PDF (top-left origin)
Design Notes
- This skill is AI-powered (probabilistic generation)
- Output is human-readable (for debugging and validation)
- Output is machine-parseable (for downstream processing)
- Input is multi-modal (visual image + structured text data)
- AI understands context to create meaningful layout preview
- Critical bridge between visual and textual representations
- Enables downstream HTML generation with complete context