Acquisition Strategist
M&A Playbook

M&A strategy for acquiring companies or being acquired. Due diligence, valuation, integration, and deal structure.
--- name: "ma-playbook" description: "M&A strategy for acquiring companies or being acquired. Due diligence, valuation, integration, and deal structure. Use when evaluating acquisitions, preparing for acquisition, M&A due diligence, integration planning, or deal negotiation." license: MIT metadata: version: 1.0.0 author: Alireza Rezvani category: c-level domain: ma-strategy updated: 2026-03-05 --- # M&A Playbook Frameworks for both sides of M&A: acquiring companies and being acquired. ## Keywords M&A, mergers and acquisitions, due diligence, acquisition, acqui-hire, integration, deal structure, valuation, LOI, term sheet, earnout
Overview
Frameworks for both sides of M&A: acquiring companies and being acquired.
Manual install (npx, ZIP)
npx skills add alirezarezvani/claude-skills --skill ma-playbook -g -a claude-codemkdir -p ~/.claude/skills && curl -sL https://codeload.github.com/alirezarezvani/claude-skills/tar.gz/19392f7a0826 \
| tar -xz -C ~/.claude/skills --strip-components=3 claude-skills-19392f7a0826/c-level-advisor/skills/ma-playbookNew-Item -ItemType Directory -Force "$HOME\.claude\skills" | Out-Null; Invoke-WebRequest "https://m.agentalley.io/zip/2065077294313dc20726/ma-playbook.zip" -OutFile "$env:TEMP\ma-playbook.zip"; Expand-Archive "$env:TEMP\ma-playbook.zip" -DestinationPath "$HOME\.claude\skills" -ForceConnects with Agent Alley MCP · agentalley.io/mcp
Files included
SKILL.md6.0 KBreferences/2 files · 10.4 KB
Read the files here
alirezarezvani/
Shared references4SKILL.md reads these from elsewhere in the repo. Not in the ZIP.
- ai_training_data_audit.pyc-level-advisor/skills/chief-data-officer-advisor/scripts/19.0 KB
- data_asset_valuator.pyc-level-advisor/skills/chief-data-officer-advisor/scripts/14.3 KB
- contract_risk_scanner.pyc-level-advisor/skills/general-counsel-advisor/scripts/16.4 KB
- term_sheet_analyzer.pyc-level-advisor/skills/general-counsel-advisor/scripts/16.5 KB
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M&A Playbook
Frameworks for both sides of M&A: acquiring companies and being acquired.
Keywords
M&A, mergers and acquisitions, due diligence, acquisition, acqui-hire, integration, deal structure, valuation, LOI, term sheet, earnout
Quick Start
Acquiring: Start with strategic rationale → target screening → due diligence → valuation → negotiation → integration.
Being Acquired: Start with readiness assessment → data room prep → advisor selection → negotiation → transition.
When You're Acquiring
Strategic Rationale (answer before anything else)
- Buy vs Build: Can you build this faster/cheaper? If yes, don't acquire.
- Acqui-hire vs Product vs Market: What are you really buying? Talent? Technology? Customers?
- Integration complexity: How hard is it to merge this into your company?
Due Diligence Checklist
| Domain | Key Questions | Red Flags |
|---|---|---|
| Financial | Revenue quality, customer concentration, burn rate | >30% revenue from 1 customer |
| Technical | Code quality, tech debt, architecture fit | Monolith with no tests |
| Legal | IP ownership, pending litigation, contracts | Key IP owned by individuals |
| People | Key person risk, culture fit, retention risk | Founders have no lockup/earnout |
| Market | Market position, competitive threats | Declining market share |
| Customers | Churn rate, NPS, contract terms | High churn, short contracts |
Valuation Approaches
The ranges below are illustrative, not current market data — always verify against current market comps before using them in a model or negotiation.
- Revenue multiple: Industry-dependent (illustrative range: 2-15x ARR for SaaS, varying with growth rate, NRR, and rate environment)
- Comparable transactions: What similar companies sold for — the most defensible anchor
- DCF: For profitable companies only (most startups: use multiples)
- Acqui-hire: Illustrative range: $1-3M per engineer in hot talent markets
Sources to verify against (check the latest edition): the SaaS Capital Index (private SaaS revenue multiples, updated monthly), Software Equity Group (SEG) Annual/Quarterly SaaS M&A Reports (transaction multiples), and Aventis Advisors' SaaS valuation multiples reports. Cross-check at least two before anchoring a price.
Integration Frameworks
See references/integration-playbook.md for the 100-day integration plan.
When You're Being Acquired
Readiness Signals
- Inbound interest from strategic buyers
- Market consolidation happening around you
- Fundraising becomes harder than operating
- Founder ready for a transition
Preparation (6-12 months before)
- Clean up financials (audited if possible)
- Document all IP and contracts
- Reduce customer concentration
- Lock up key employees
- Build the data room
- Engage an M&A advisor
Negotiation Points
| Term | What to Watch | Your Leverage |
|---|---|---|
| Valuation | Earnout traps (unreachable targets) | Multiple competing offers |
| Earnout | Milestone definitions, measurement period | Cash-heavy vs earnout-heavy split |
| Lockup | Duration, conditions | Your replaceability |
| Rep & warranties | Scope of liability | Escrow vs indemnification cap |
| Employee retention | Who gets offers, at what terms | Key person dependencies |
Red Flags (Both Sides)
- No clear strategic rationale beyond "it's a good deal"
- Culture clash visible during due diligence and ignored
- Key people not locked in before close
- Integration plan doesn't exist or is "we'll figure it out"
- Valuation based on projections, not actuals
Verification Loop (before any LOI or signature)
This skill frames the deal; two sibling skills verify it. Hand off — don't duplicate:
- Legal terms →
general-counsel-advisor: run the LOI/term sheet through../general-counsel-advisor/scripts/term_sheet_analyzer.py(12-dimension 0-100 score) and the definitive docs through../general-counsel-advisor/scripts/contract_risk_scanner.py(12 founder-killer patterns: earnout traps, uncapped indemnity, vague IP, etc.). Any 🔴 finding goes to outside counsel before signing. - Data diligence →
chief-data-officer-advisor: run../chief-data-officer-advisor/scripts/ai_training_data_audit.py(training-data rights, GDPR Art. 6 basis) and../chief-data-officer-advisor/scripts/data_asset_valuator.py(data-asset value, M&A multiplier with carve-out penalties) on the target's data estate. Undocumented consent provenance is a price-reduction or walk-away item. - Valuation math →
cfo-advisortools for the quantitative model; this playbook stays qualitative.
Loop the findings back into the negotiation-points table above before the next counter.
Integration with C-Suite Roles
| Role | Contribution to M&A |
|---|---|
| CEO | Strategic rationale, negotiation lead |
| CFO | Valuation, deal structure, financing |
| GC | LOI/term sheet review, contract risk scan, regulatory triggers |
| CDO | Data diligence: training-data rights, data-asset valuation |
| CTO | Technical due diligence, integration architecture |
| CHRO | People due diligence, retention planning |
| COO | Integration execution, process merge |
| CPO | Product roadmap impact, customer overlap |
Resources
references/integration-playbook.md— 100-day post-acquisition integration planreferences/due-diligence-checklist.md— comprehensive DD checklist by domain../general-counsel-advisor/SKILL.md— term sheet analyzer + contract risk scanner../chief-data-officer-advisor/SKILL.md— data diligence + data-asset valuation
| 1 | |
| 2 | name "ma-playbook" |
| 3 | description "M&A strategy for acquiring companies or being acquired. Due diligence, valuation, integration, and deal structure. Use when evaluating acquisitions, preparing for acquisition, M&A due diligence, integration planning, or deal negotiation." |
| 4 | license MIT |
| 5 | metadata |
| 6 | version 1.0.0 |
| 7 | author Alireza Rezvani |
| 8 | category c-level |
| 9 | domain ma-strategy |
| 10 | updated 2026-03-05 |
| 11 | |
| 12 | |
| 13 | # M&A Playbook |
| 14 | |
| 15 | Frameworks for both sides of M&A: acquiring companies and being acquired. |
| 16 | |
| 17 | ## Keywords |
| 18 | M&A, mergers and acquisitions, due diligence, acquisition, acqui-hire, integration, deal structure, valuation, LOI, term sheet, earnout |
| 19 | |
| 20 | ## Quick Start |
| 21 | |
| 22 | **Acquiring:** Start with strategic rationale → target screening → due diligence → valuation → negotiation → integration. |
| 23 | |
| 24 | **Being Acquired:** Start with readiness assessment → data room prep → advisor selection → negotiation → transition. |
| 25 | |
| 26 | ## When You're Acquiring |
| 27 | |
| 28 | ### Strategic Rationale (answer before anything else) |
| 29 | **Buy vs Build:** Can you build this faster/cheaper? If yes, don't acquire. |
| 30 | **Acqui-hire vs Product vs Market:** What are you really buying? Talent? Technology? Customers? |
| 31 | **Integration complexity:** How hard is it to merge this into your company? |
| 32 | |
| 33 | ### Due Diligence Checklist |
| 34 | | Domain | Key Questions | Red Flags | |
| 35 | |--------|--------------|-----------| |
| 36 | | Financial | Revenue quality, customer concentration, burn rate | >30% revenue from 1 customer | |
| 37 | | Technical | Code quality, tech debt, architecture fit | Monolith with no tests | |
| 38 | | Legal | IP ownership, pending litigation, contracts | Key IP owned by individuals | |
| 39 | | People | Key person risk, culture fit, retention risk | Founders have no lockup/earnout | |
| 40 | | Market | Market position, competitive threats | Declining market share | |
| 41 | | Customers | Churn rate, NPS, contract terms | High churn, short contracts | |
| 42 | |
| 43 | ### Valuation Approaches |
| 44 | |
| 45 | The ranges below are **illustrative, not current market data** — always verify against current market comps before using them in a model or negotiation. |
| 46 | |
| 47 | **Revenue multiple:** Industry-dependent (illustrative range: 2-15x ARR for SaaS, varying with growth rate, NRR, and rate environment) |
| 48 | **Comparable transactions:** What similar companies sold for — the most defensible anchor |
| 49 | **DCF:** For profitable companies only (most startups: use multiples) |
| 50 | **Acqui-hire:** Illustrative range: $1-3M per engineer in hot talent markets |
| 51 | |
| 52 | **Sources to verify against (check the latest edition):** the SaaS Capital Index (private SaaS revenue multiples, updated monthly), Software Equity Group (SEG) Annual/Quarterly SaaS M&A Reports (transaction multiples), and Aventis Advisors' SaaS valuation multiples reports. Cross-check at least two before anchoring a price. |
| 53 | |
| 54 | ### Integration Frameworks |
| 55 | See `references/integration-playbook.md` for the 100-day integration plan. |
| 56 | |
| 57 | ## When You're Being Acquired |
| 58 | |
| 59 | ### Readiness Signals |
| 60 | Inbound interest from strategic buyers |
| 61 | Market consolidation happening around you |
| 62 | Fundraising becomes harder than operating |
| 63 | Founder ready for a transition |
| 64 | |
| 65 | ### Preparation (6-12 months before) |
| 66 | Clean up financials (audited if possible) |
| 67 | Document all IP and contracts |
| 68 | Reduce customer concentration |
| 69 | Lock up key employees |
| 70 | Build the data room |
| 71 | Engage an M&A advisor |
| 72 | |
| 73 | ### Negotiation Points |
| 74 | | Term | What to Watch | Your Leverage | |
| 75 | |------|--------------|---------------| |
| 76 | | Valuation | Earnout traps (unreachable targets) | Multiple competing offers | |
| 77 | | Earnout | Milestone definitions, measurement period | Cash-heavy vs earnout-heavy split | |
| 78 | | Lockup | Duration, conditions | Your replaceability | |
| 79 | | Rep & warranties | Scope of liability | Escrow vs indemnification cap | |
| 80 | | Employee retention | Who gets offers, at what terms | Key person dependencies | |
| 81 | |
| 82 | ## Red Flags (Both Sides) |
| 83 | |
| 84 | No clear strategic rationale beyond "it's a good deal" |
| 85 | Culture clash visible during due diligence and ignored |
| 86 | Key people not locked in before close |
| 87 | Integration plan doesn't exist or is "we'll figure it out" |
| 88 | Valuation based on projections, not actuals |
| 89 | |
| 90 | ## Verification Loop (before any LOI or signature) |
| 91 | |
| 92 | This skill frames the deal; two sibling skills verify it. Hand off — don't duplicate: |
| 93 | |
| 94 | **Legal terms** → `general-counsel-advisor`: run the LOI/term sheet through `../general-counsel-advisor/scripts/term_sheet_analyzer.py` (12-dimension 0-100 score) and the definitive docs through `../general-counsel-advisor/scripts/contract_risk_scanner.py` (12 founder-killer patterns: earnout traps, uncapped indemnity, vague IP, etc.). Any 🔴 finding goes to outside counsel before signing. |
| 95 | **Data diligence** → `chief-data-officer-advisor`: run `../chief-data-officer-advisor/scripts/ai_training_data_audit.py` (training-data rights, GDPR Art. 6 basis) and `../chief-data-officer-advisor/scripts/data_asset_valuator.py` (data-asset value, M&A multiplier with carve-out penalties) on the target's data estate. Undocumented consent provenance is a price-reduction or walk-away item. |
| 96 | **Valuation math** → `cfo-advisor` tools for the quantitative model; this playbook stays qualitative. |
| 97 | |
| 98 | Loop the findings back into the negotiation-points table above before the next counter. |
| 99 | |
| 100 | ## Integration with C-Suite Roles |
| 101 | |
| 102 | | Role | Contribution to M&A | |
| 103 | |------|-------------------| |
| 104 | | CEO | Strategic rationale, negotiation lead | |
| 105 | | CFO | Valuation, deal structure, financing | |
| 106 | | GC | LOI/term sheet review, contract risk scan, regulatory triggers | |
| 107 | | CDO | Data diligence: training-data rights, data-asset valuation | |
| 108 | | CTO | Technical due diligence, integration architecture | |
| 109 | | CHRO | People due diligence, retention planning | |
| 110 | | COO | Integration execution, process merge | |
| 111 | | CPO | Product roadmap impact, customer overlap | |
| 112 | |
| 113 | ## Resources |
| 114 | `references/integration-playbook.md` — 100-day post-acquisition integration plan |
| 115 | `references/due-diligence-checklist.md` — comprehensive DD checklist by domain |
| 116 | `../general-counsel-advisor/SKILL.md` — term sheet analyzer + contract risk scanner |
| 117 | `../chief-data-officer-advisor/SKILL.md` — data diligence + data-asset valuation |
| 118 |
Details
- Updated
- Aug 30, 2026
- License
- MIT
- Stars on the repo
- ★ 26,349
- Checked
- Source
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