Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsBlogPro
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges
  • Chrome Extension
  • Skill Manager

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Merger Model

ASecurity

Build M&A accretion/dilution workbooks in Excel.

5 stars
0 votes
0 copies
0 views
Added 10/4/2026
ai-agentspythongogit

Works with

mcp

Security Analysis

A100/100

Scanned 10/4/2026

$npx -y skills add openamer/openamer --skill merger-model --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Merger Model?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Merger Model
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/openamer-merger-model/badge)](https://www.skillsdirectory.com/skills/openamer-merger-model)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
Files
SKILL.md
---
name: merger-model
description: Build M&A accretion/dilution workbooks in Excel.
version: 1.0.0
author: Anthropic (adapted by the OpenAmer project)
license: Apache-2.0
platforms: [linux, macos, windows]
metadata:
  openamer:
    tags: [finance, m-and-a, merger, accretion-dilution, excel, openpyxl, modeling, investment-banking]
    related_skills: [excel-author, pptx-author, dcf-model, 3-statement-model]
---

## Environment

This skill assumes **headless openpyxl** — you are producing an .xlsx file on disk.
Follow the `excel-author` skill's conventions for cell coloring, formulas, named ranges, and sensitivity tables.
Recalculate before delivery: `python /path/to/excel-author/scripts/recalc.py ./out/model.xlsx`.

# Merger Model

Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms.

## Workflow

### Step 1: Gather Inputs

**Acquirer:**
- Company name, current share price, shares outstanding
- LTM and NTM EPS (GAAP and adjusted)
- P/E multiple
- Pre-tax cost of debt, tax rate
- Cash on balance sheet, existing debt

**Target:**
- Company name, current share price, shares outstanding (if public)
- LTM and NTM EPS or net income
- Enterprise value or equity value

**Deal Terms:**
- Offer price per share (or premium to current)
- Consideration mix: % cash vs. % stock
- New debt raised to fund cash portion
- Expected synergies (revenue and cost) and phase-in timeline
- Transaction fees and financing costs
- Expected close date

### Step 2: Purchase Price Analysis

| Item | Value |
|------|-------|
| Offer price per share | |
| Premium to current | |
| Equity value | |
| Plus: net debt assumed | |
| Enterprise value | |
| EV / EBITDA implied | |
| P/E implied | |

### Step 3: Sources & Uses

| Sources | $ | Uses | $ |
|---------|---|------|---|
| New debt | | Equity purchase price | |
| Cash on hand | | Refinance target debt | |
| New equity issued | | Transaction fees | |
| | | Financing fees | |
| **Total** | | **Total** | |

### Step 4: Pro Forma EPS (Accretion / Dilution)

Calculate year-by-year (Year 1-3):

| | Standalone | Pro Forma | Accretion/(Dilution) |
|---|-----------|-----------|---------------------|
| Acquirer net income | | | |
| Target net income | | | |
| Synergies (after tax) | | | |
| Foregone interest on cash (after tax) | | | |
| New debt interest (after tax) | | | |
| Intangible amortization (after tax) | | | |
| Pro forma net income | | | |
| Pro forma shares | | | |
| **Pro forma EPS** | | | |
| **Accretion / (Dilution) %** | | | |

### Step 5: Sensitivity Analysis

**Accretion/Dilution vs. Synergies and Offer Premium:**

| | $0M syn | $25M syn | $50M syn | $75M syn | $100M syn |
|---|---------|----------|----------|----------|-----------|
| 15% premium | | | | | |
| 20% premium | | | | | |
| 25% premium | | | | | |
| 30% premium | | | | | |

**Accretion/Dilution vs. Cash/Stock Mix:**

| | 100% cash | 75/25 | 50/50 | 25/75 | 100% stock |
|---|-----------|-------|-------|-------|------------|
| Year 1 | | | | | |
| Year 2 | | | | | |

### Step 6: Breakeven Synergies

Calculate the minimum synergies needed for the deal to be EPS-neutral in Year 1.

### Step 7: Output

- Excel workbook with:
  - Assumptions tab
  - Sources & uses
  - Pro forma income statement
  - Accretion/dilution summary
  - Sensitivity tables
  - Breakeven analysis
- One-page merger consequences summary for pitch book

## Important Notes

- Always show both GAAP and adjusted (cash) EPS where relevant
- Stock deals: use acquirer's current price for exchange ratio, note dilution from new shares
- Include purchase price allocation — goodwill and intangible amortization matter for GAAP EPS
- Synergy phase-in is critical — Year 1 is often only 25-50% of run-rate synergies
- Don't forget foregone interest income on cash used and new interest expense on debt raised
- Tax rate on synergies and interest adjustments should match the acquirer's marginal rate


## Data sources — MCP first, web fallback

Many passages below say "use the S&P Kensho MCP / Daloopa MCP / FactSet MCP". Those are commercial financial-data MCPs from the original Cowork plugin context. In OpenAmer:

- **If you have any structured financial-data MCP configured** (OpenAmer supports MCP — see `native-mcp` skill), prefer it for point-in-time comps, precedent transactions, and filings.
- **Otherwise**, fall back to:
  - `web_search` / `web_extract` against SEC EDGAR (`https://www.sec.gov/cgi-bin/browse-edgar`) for US filings
  - Company IR pages for press releases, earnings decks
  - `browser_navigate` for interactive data portals
  - User-provided data (explicitly ask when the context doesn't have it)
- **Never fabricate**. If a multiple, precedent, or filing number can't be sourced, flag the cell as `[UNSOURCED]` and surface it to the user.

## Attribution

This skill is adapted from Anthropic's Claude for Financial Services plugin suite (Apache-2.0). The Office-JS / Cowork live-Excel paths have been removed; this version targets headless openpyxl via the `excel-author` skill's conventions. Original: https://github.com/anthropics/financial-services

Attribution

openameropenamer
View sourceSee grades on GitHubMore from openamer →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Terse caveman voice: answer first, fluff gone, every technical fact kept. Use for /caveman, "caveman mode", "talk like caveman", "be brief", "less tokens". Stays on until "stop caveman" or "normal mode".

1100021 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

698461 votes

Writing Skills

Create and manage Claude Code skills in HASH repository following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns), UserPromptSubmit hook, and the 500-line rule. Includes validation and debugging with SKILL_DEBUG. Examples include rust-error-stack, cargo-dep...

3931 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3421 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Amp, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Grok Build, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

741 votes
View all in ai-agents →