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Document Processor

Community
minicoohei
document-processor

PDF/PPTX/Excelファイルの読み取り・編集・分析を行うサブエージェント。 大きなドキュメントの処理をメインコンテキストから分離し、コンテキスト消費を最適化する。 「PDFを分析」「PPTXの内容を読んで」「Excelを解析」「スライドを編集」等のリクエストで発動。

Overview

Publisherminicoohei
Repositoryai-agent-camp
Skill namedocument-processor
Stars
346
Forks
13
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by minicoohei on GitHub. Read the source before you install it.

Installation

Install the Document Processor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/minicoohei/ai-agent-camp/tree/main/.claude/skills/document-processor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/minicoohei/ai-agent-camp.git /tmp/ai-agent-camp
mkdir -p .claude/skills
cp -r /tmp/ai-agent-camp/.claude/skills/document-processor .claude/skills/document-processor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Document Processor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Document Processor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Document Processor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Document Processor サブエージェント

PDF/PPTX/Excelファイルの読み取り・編集・分析を専用コンテキストで実行するサブエージェント。

目的

大きなドキュメントの処理をメインエージェントのコンテキストから分離し:

  • コンテキスト消費を削減(2000-10000トークン削減効果)
  • 処理結果のサマリーのみを返却
  • 複数ファイルの並列処理が可能

対応フォーマット

フォーマット読み取り編集分析
PDF (.pdf)✅✅✅
PowerPoint (.pptx)✅✅✅
Excel (.xlsx)✅✅✅

使用可能なスクリプト

1. PowerPoint操作 (tools/pptx_ops.py)

bash
# 読み取り
uv run python tools/pptx_ops.py read <file.pptx>

# Markdown変換
uv run python tools/pptx_ops.py to-markdown <file.pptx>

# 構造分析
uv run python tools/pptx_ops.py analyze <file.pptx>

# テンプレート抽出
uv run python tools/pptx_ops.py extract-template <file.pptx> --output template.json

# 新規作成
uv run python tools/pptx_ops.py create <template.json> --output new.pptx

2. Excel操作 (tools/excel_ops.py)

bash
# 読み取り
uv run python tools/excel_ops.py read <file.xlsx>

# 特定シート読み取り
uv run python tools/excel_ops.py read <file.xlsx> --sheet "Sheet1"

# Markdown変換
uv run python tools/excel_ops.py to-markdown <file.xlsx>

# 分析レポート
uv run python tools/excel_ops.py analyze <file.xlsx>

# 書き込み
uv run python tools/excel_ops.py write <file.xlsx> --data '{"sheet": "Sheet1", "cell": "A1", "value": "Hello"}'

3. PDF操作 (tools/pdf_page_editor.py)

bash
# テキスト抽出・分析
uv run python tools/pdf_page_editor.py analyze <file.pdf>

# ページ編集
uv run python tools/pdf_page_editor.py edit <file.pdf> --page 1 --changes <changes.yaml>

# 圧縮
uv run python tools/pdf_page_editor.py compress <file.pdf> --output compressed.pdf

サブエージェント呼び出しパターン

メインエージェントは以下のパターンでこのサブエージェントを呼び出す:

python
Task(
    subagent_type="generalPurpose",
    model="fast",
    description="Document analysis",
    prompt="""
    このスキルを読んで実行してください: skills/document-processor/SKILL.md
    
    タスク: {ユーザーの指示}
    対象ファイル: {ファイルパス}
    
    結果はサマリー形式で返却してください。
    """
)

返却フォーマット

処理結果は以下のサマリー形式で返却:

yaml
status: success
file: example.pptx
summary:
  total_slides: 10
  key_content:
    - slide_1: "タイトルスライド - プロジェクト概要"
    - slide_2: "目次 - 5項目"
  findings:
    - "テンプレートは16:9アスペクト比"
    - "カラースキーム: 青/白/黒"
output_files:
  - example_structure.json
  - example_structure.txt

依存関係

txt
python-pptx>=0.6.21
openpyxl>=3.1.0
pdf2image>=1.16.0
Pillow>=9.0.0
PyMuPDF>=1.21.0
google-generativeai>=0.3.0

ユースケース

  1. PPTX分析: テンプレート構造の把握、プレースホルダー特定
  2. Excel分析: データ構造の理解、シート間の関係把握
  3. PDF編集: テキスト修正、ページ再構築
  4. バッチ処理: 複数ドキュメントの一括処理

注意事項

  • 大きなファイル(>50MB)は処理に時間がかかる場合がある
  • PDF編集は元ファイルを変更せず、新規ファイルを生成
  • 画像の多いPPTXは--with-imagesオプションで画像も抽出可能

Overview

PDF/PPTX/Excelファイルの読み取り・編集・分析を専用コンテキストで実行するサブエージェントスキルです。大きなドキュメントの処理をメインコンテキストから分離し、処理結果のサマリーのみを返却します。

Troubleshooting

エラー解決方法
python-pptx not installeduv add python-pptx でインストール
PDF parsing errorPyMuPDF がインストールされているか確認: uv add PyMuPDF
File too large (>50MB)処理に時間がかかる場合あり。PDF圧縮スキルで事前に軽量化を検討

Success Criteria

  • ドキュメントの内容がサマリー形式(YAML)で返却されている
  • 編集操作時に元ファイルが変更されず新規ファイルが生成されている
  • エラーなく完了している

Usage

上記「使用可能なスクリプト」セクションを参照。基本例:

bash
# PPTX読み取り
uv run python tools/pptx_ops.py read presentation.pptx

# Excel分析
uv run python tools/excel_ops.py analyze data.xlsx

# PDF分析
uv run python tools/pdf_page_editor.py analyze document.pdf

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Document Processor AI skill do?

PDF/PPTX/Excelファイルの読み取り・編集・分析を行うサブエージェント。 大きなドキュメントの処理をメインコンテキストから分離し、コンテキスト消費を最適化する。 「PDFを分析」「PPTXの内容を読んで」「Excelを解析」「スライドを編集」等のリクエストで発動。

Why use Document Processor on TypingMind?

Because you install it once and use it with any model. Document Processor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Document Processor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/minicoohei/ai-agent-camp/tree/main/.claude/skills/document-processor. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Document Processor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Document Processor?

As many as you like. As long as a model supports skills, you can use Document Processor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Document Processor AI skill free?

It is published on GitHub by minicoohei. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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