merger-model skill
Build M&A accretion/dilution workbooks in Excel.
Is the merger-model skill safe?
Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-10-25.
No findings.
Install the merger-model skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/NousResearch/hermes-agent.git /tmp/hermes-agent mkdir -p ~/.claude/skills cp -r /tmp/hermes-agent/optional-skills/finance/merger-model ~/.claude/skills/merger-model
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
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
Step 3: Sources & Uses
Step 4: Pro Forma EPS (Accretion / Dilution)
Calculate year-by-year (Year 1-3):
Step 5: Sensitivity Analysis
Accretion/Dilution vs. Synergies and Offer Premium:
Accretion/Dilution vs. Cash/Stock Mix:
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 Hermes:
- If you have any structured financial-data MCP configured (Hermes supports MCP — see native-mcp skill), prefer it for point-in-time comps, precedent transactions, and filings.
- Otherwise, fall back to:
- websearch / webextract against SEC EDGAR (https://www.sec.gov/cgi-bin/browse-edgar) for US filings
- Company IR pages for press releases, earnings decks
- browser_exec 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
More skills from NousResearch/hermes-agent
- A1passwordSet up op CLI, sign in, and read or inject secrets.
- A3-statement-modelBuild integrated IS/BS/CF financial workbooks in Excel.
- AaccelerateRun PyTorch training across GPUs with minimal changes.
- Cactual-setupSet up Actual Computer (actual.inc) inference in Hermes.
- Aadversarial-ux-testRoleplay a hostile user to find and triage UX pain points.
- Aagent-merge-conflict-arbiterNeutral arbiter for merge conflicts between two agents.
- AagentmailUse when an agent needs AgentMail CLI email inboxes.
- Aai-presenter-videoMake a verified AI presenter video from script + image.
- AairtableAirtable REST API via curl. Records CRUD, filters, upserts.
- AanatomyExplain an idea as an interactive isometric machine figure.
- Cantigravity-cliOperate the Antigravity CLI (agy): plugins, auth, sandbox.
- Aapple-notesManage Apple Notes via memo CLI: create, search, edit.