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Ma Playbook

CommunityPopular
alirezarezvani
ma-playbook

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.

Overview

Publisheralirezarezvani
Repositoryclaude-skills
Skill namema-playbook
Stars
26.1K
Forks
3.7K
Bundled files
2
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Ma Playbook 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.
  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/alirezarezvani/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/c-level-advisor/skills/ma-playbook .claude/skills/ma-playbook
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ma Playbook 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 Ma Playbook 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 Ma Playbook 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.

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

DomainKey QuestionsRed Flags
FinancialRevenue quality, customer concentration, burn rate>30% revenue from 1 customer
TechnicalCode quality, tech debt, architecture fitMonolith with no tests
LegalIP ownership, pending litigation, contractsKey IP owned by individuals
PeopleKey person risk, culture fit, retention riskFounders have no lockup/earnout
MarketMarket position, competitive threatsDeclining market share
CustomersChurn rate, NPS, contract termsHigh 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)

  1. Clean up financials (audited if possible)
  2. Document all IP and contracts
  3. Reduce customer concentration
  4. Lock up key employees
  5. Build the data room
  6. Engage an M&A advisor

Negotiation Points

TermWhat to WatchYour Leverage
ValuationEarnout traps (unreachable targets)Multiple competing offers
EarnoutMilestone definitions, measurement periodCash-heavy vs earnout-heavy split
LockupDuration, conditionsYour replaceability
Rep & warrantiesScope of liabilityEscrow vs indemnification cap
Employee retentionWho gets offers, at what termsKey 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:

  1. 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.
  2. 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.
  3. Valuation math → cfo-advisor tools 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

RoleContribution to M&A
CEOStrategic rationale, negotiation lead
CFOValuation, deal structure, financing
GCLOI/term sheet review, contract risk scan, regulatory triggers
CDOData diligence: training-data rights, data-asset valuation
CTOTechnical due diligence, integration architecture
CHROPeople due diligence, retention planning
COOIntegration execution, process merge
CPOProduct roadmap impact, customer overlap

Resources

  • references/integration-playbook.md — 100-day post-acquisition integration plan
  • references/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

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 Ma Playbook AI skill do?

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.

Why use Ma Playbook on TypingMind?

Because you install it once and use it with any model. Ma Playbook 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 Ma Playbook in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/skills/ma-playbook. 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 Ma Playbook?

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 Ma Playbook?

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

Is the Ma Playbook AI skill free?

Yes. It is published on GitHub by alirezarezvani under the MIT license. 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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