M And A Advisor

M&Aアドバイザリー支援スキル。デューデリジェンス（DD）実施、企業価値評価（バリュエーション）、 シナジー分析、PMI（Post Merger Integration）計画策定を包括的に支援。 Use when conducting M&A due diligence (Financial, Legal, IT, HR), company valuation (DCF, Comparable Companies, Precedent Transactions), synergy analysis, or post-merger integration planning. Triggers: “M&A”, “デューデリジェンス”, “DD”, “バリュエーション”, “企業価値評価”, “DCF”, “comparable”, “類似企業”, “先行取引”, “PMI”, “統合計画”, “シナジー分析”, “買収”, “合併”

No API Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

M&Aアドバイザリー業務を包括的に支援するスキル。デューデリジェンス（DD）の実施から企業価値評価、シナジー分析、PMI計画策定まで、M&Aプロセス全体をカバー。

主要機能:

  1. デューデリジェンス（DD） - 財務/法務/IT/HR の4領域 + 業種別DD
  2. バリュエーション - DCF/類似企業比較/先行取引分析の3手法
  3. シナジー分析 - コスト/収益シナジーの定量化
  4. PMI計画 - 統合計画の策定と実行支援

2. Prerequisites

  • API Key: None required
  • Python 3.9+ recommended

3. Quick Start 

□ 財務DD (Financial Due Diligence)
□ 法務DD (Legal Due Diligence)
□ IT DD (IT/Technology Due Diligence)
□ 人事DD (HR Due Diligence)
□ 業種別DD (Industry-Specific DD)

4. How It Works

Step 1.1: DDスコープ定義

対象領域の特定:

□ 財務DD (Financial Due Diligence)
□ 法務DD (Legal Due Diligence)
□ IT DD (IT/Technology Due Diligence)
□ 人事DD (HR Due Diligence)
□ 業種別DD (Industry-Specific DD)

業種別DD選択:

  • IT・ソフトウェア業 → references/dd-industry/it_software_dd.md
  • 製造業 → references/dd-industry/manufacturing_dd.md
  • 金融・保険業 → references/dd-industry/financial_services_dd.md
  • 小売・消費財 → references/dd-industry/retail_consumer_dd.md

Step 1.2: 各領域のDD実施

財務DD (references/dd-checklists/financial_dd_checklist.md):

  1. 財務諸表分析（過去3-5年）
  2. 収益性・成長性分析
  3. 運転資本・キャッシュフロー分析
  4. 税務リスク評価

See the skill’s SKILL.md for the full end-to-end workflow.

5. Usage Examples

  • Use M And A Advisor when you need a structured workflow rather than an ad-hoc answer.
  • Start with a small representative input before applying the workflow to production data or assets.
  • Review the helper scripts and reference guides to tailor the output format to your project.

6. Understanding the Output

  • A structured response or artifact aligned to the skill’s workflow.
  • Reference support from 2 guide file(s).
  • Script-assisted execution using 1 helper command(s) where applicable.
  • Reusable output that can be reviewed, refined, and incorporated into a wider project workflow.

7. Tips & Best Practices

  • Begin with the smallest realistic sample input so you can validate the workflow before scaling up.
  • Keep skills/m-and-a-advisor/SKILL.md open while working; it remains the authoritative source for the full procedure.
  • Review the most relevant reference files first instead of scanning every guide: synergy_analysis_guide.md, pmi_framework.md.
  • Run helper scripts on test data before using them on final assets or production-bound inputs: valuation_calculator.py.
  • Preserve intermediate outputs so you can explain assumptions, diffs, and follow-up actions clearly.

8. Combining with Other Skills

  • Combine this skill with adjacent skills in the same category when the work spans planning, implementation, and review.
  • Browse the broader category for neighboring workflows: category index.
  • Use the English skill catalog when you need to chain this workflow into a larger end-to-end process.

9. Troubleshooting

  • Re-check prerequisites first: missing runtime dependencies and unsupported file formats are the most common failures.
  • If a helper script is involved, run it with a minimal sample input before applying it to a full dataset or repository.
  • Compare your input shape against the reference files to confirm expected fields, sections, or metadata are present.
  • Confirm the expected Python version and required packages are installed in the active environment.
  • When output looks incomplete, inspect the script arguments and rerun with explicit input/output paths.

10. Reference

References:

  • skills/m-and-a-advisor/references/pmi_framework.md
  • skills/m-and-a-advisor/references/synergy_analysis_guide.md

Scripts:

  • skills/m-and-a-advisor/scripts/valuation_calculator.py