Exiting Company logo

Exiting Company

Organization
LeadMagic
exiting-company

Prepare a SaaS company for acquisition or exit — valuation drivers by buyer type (strategic, PE, bootstrap), due diligence readiness, EBITDA vs ARR multiples, and 12–24 month exit timeline. Use when planning an exit, preparing for acquisition, or maximizing company value for a future sale. Triggers on: "exit strategy", "sell company", "acquisition prep", "M&A", "due diligence", "company valuation", "exit planning", "PE acquisition", "bootstrap exit".

Overview

PublisherLeadMagic
Repositorygtm-skills
Skill nameexiting-company
Stars
72
Forks
18
Bundled files
12
LicenseMIT
Links
  • 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.

  • 12 bundled files

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

  • Open source

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

Installation

Install the Exiting Company 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.
    https://github.com/LeadMagic/gtm-skills/tree/main/skills/founder-led/exiting-company
  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/LeadMagic/gtm-skills.git /tmp/gtm-skills
mkdir -p .claude/skills
cp -r /tmp/gtm-skills/skills/founder-led/exiting-company .claude/skills/exiting-company
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exiting Company 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 Exiting Company 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 Exiting Company 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.

Exiting a Company

Overview

Companies are bought, not sold. The best exits happen when a strategic or financial buyer identifies you as the solution to their problem — not when you announce a sale. This skill covers valuation drivers by buyer type, diligence-ready metrics, and the 12–24 month runway most exits require.

Not legal or tax advice. Use qualified counsel for transactions, earnouts, and cap table mechanics (equity-management, legal-for-founders).

When to Use

  • "How do I prepare my company for acquisition?"
  • "What's my company worth to PE vs strategic?"
  • "Build an exit strategy"
  • "Prepare for due diligence"
  • "Maximize acquisition value"
  • "Sell my bootstrapped SaaS"
  • "Negotiate earn-out" / "earnout terms" / "retention bonus vs earn-out"
  • "Walk away from LOI" / "seller note" / "rollover equity in acquisition"

Do not use for path choice (bootstrap vs VC) — use saas-outcomes first. Do not use for metric calculation — use saas-metrics-calculator.

Authoritative Foundations

  • David Skok. Unit economics gate every exit. LTV:CAC <3x or payback >18 months compress multiples in diligence — fix before process.
  • Jason Lemkin (SaaStr). Burn multiple and growth efficiency matter as much as ARR scale; inefficient growth gets discounted at LOI.
  • Nathan Latka (GetLatka). Sub-$10M ARR bootstrapped SaaS has real acquisition liquidity; weight churn, growth, and clean books over VC headline multiples.
  • Ben Murray (The SaaS CFO). PE buyers model EBITDA and FCF; bridge from unit economics → P&L → EBITDA multiple (financial-modeling/references/unit-economics-exit-bridge.md).
  • KeyBanc SaaS Survey. Private ARR multiple bands by growth tier — use as range, not quote.

Step-by-Step Process

Phase 0: Exit Optionality Gate

Score whether exit is realistic vs distraction before M&A prep. Load saas-outcomes/references/exit-potential-scorecard.md:

  • <3.0 avg: Fix retention and concentration — exit is distraction
  • 3.0–3.9: Passive readiness only (metrics pack, relationships)
  • ≥4.0: Proceed with Phase 2–4 readiness

Phase 1: Valuation Drivers by Buyer Type

Load references/valuation-drivers.md and saas-outcomes/references/exit-metrics-matrix.md.

Buyer typeMetrics they weightRed flags
StrategicProduct fit, customer overlap, talentCustomer concentration; IP gaps
PEEBITDA, NRR >110%, predictable renewals, efficient GTMHigh burn; founder dependency
Acqui-hire / small M&ATeam, tech (Latka sub-$10M ARR)No product velocity
Bootstrap acquirerProfitability, clean cap table, low churnMessy books; cap disputes

Scale thresholds (planning): $1M ARR acqui-hire possible; $5M strategic interest; $10M+ serious conversations; $20M+ banker-led if inbound.

Multiples (indicative): Strategic 5–15x ARR; PE 8–12x ARR or 15–25x EBITDA; bootstrap 4–8x ARR or 3–6x SDE. See templates/valuation-sensitivity-table.md.

Phase 2: Due Diligence Package

Prepare before anyone asks. Load references/due-diligence-metrics-pack.md.

Financial: 36 mo P&L; ARR bridge; cohort NRR/GRR; fully loaded CAC/LTV
Legal: Cap table; IP assignments (contractors critical); material contracts
Technical: SOC2 or equivalent; architecture; DR
Commercial: Concentration; churn reasons; documented playbook

Phase 3: 12–24 Month Runway

Load references/buyer-readiness-checklist.md and templates/exit-readiness-scorecard.md.

PhaseFocus
Months 1–6Cap table, IP, metrics pack, concentration plan
Months 7–12NRR trend, GTM repeatability, founder dependency ↓
Months 13–18Market signals, partnerships, data room 80%
Months 19–24Counsel, LOI, diligence (60–90 days), close (30–60 days)

Phase 4: Exit Options

OptionValuation basisTypical timeline
Strategic acquisitionARR × growth + synergy6–12 months
PE (majority)EBITDA + ARR growth4–8 months
Bootstrap sale (MicroAcquire/GetLatka)ARR/SDE, churn3–6 months
Acqui-hireTeam value2–4 months
IPO$100M+ ARR, Rule of 4012–18 months

Cross-ref: saas-outcomes/references/bootstrap-vs-vc-paths.md for hold vs sell.

Phase 5: Deal Structure — Earn-Outs & Deferred Consideration

When LOI includes earn-out, seller note, or rollover — model cash at close first, not headline EV. Load references/negotiating-earn-out.md:

TopicFounder sensibility
When fairReal diligence gap; metrics you already run; want to stay 18–24 mo
When trap>40% at risk; buyer controls OpEx; vague metrics; at-will + forfeiture
Typical at risk15–40% mid-market; bootstrap sales often lower earn-out %
WalkCash at close below floor; >50% at risk without audit/carve-outs

Negotiation artifacts: templates/earn-out-term-sheet-review.md (worksheet), templates/valuation-sensitivity-table.md (hold vs sell + deferred scenarios).

Related structures (high level):

  • Retention bonus — time-based; prefer separate from performance earn-out
  • Rollover equity — upside alignment; understand liquidation prefs
  • Seller financing — only with security, market interest, clear subordination

Legal handoff: Contract language → M&A counsel. Commercial velocity → deal-desk/references/legal-gtm-playbook.md (Pattern 29). Not legal advice in this skill.

Reconcile structure norms → references/benchmark-reconciliation.md (Earn-Out vs Upfront Cash).

Output Format

Exit readiness assessment with: buyer-type fit, valuation range (low/base/high with method named), diligence gaps, 24-month timeline, scorecard summary.

Quality Check

  • Buyer type identified (strategic vs PE vs bootstrap)
  • Valuation method matches buyer (ARR vs EBITDA vs SDE)
  • Metrics pack items mapped to gaps
  • No guaranteed valuation claims — ranges and assumptions only
  • Cross-refs to saas-metrics-calculator, financial-modeling, saas-outcomes

Common Pitfalls

  1. Missing IP assignments. Contractor IP gaps kill deals — fix in month 1–6.
  2. Customer concentration. One logo >20% ARR → un-acquirable or deep discount.
  3. Founder dependency. Acquirer buys key-person risk, not a company.
  4. Optimizing ARR before NRR. Diligence strips low-quality revenue.
  5. Shopping the company. Inbound from relationships beats outbound "for sale."
  6. Headline EV without cash-at-close math. Earn-out traps look like big deals. Fix: earn-out-term-sheet-review.md before signing.
  7. Accepting EBITDA earn-out without carve-outs. Buyer can cut marketing and void payout. Fix: negotiating-earn-out.md governance section.

Execution Artifacts

  • references/framework-notes.md — named frameworks and agent routing
  • templates/output-template.md — deliverable shell
  • scripts/check-output.py — lightweight validator
  • references/valuation-drivers.md — strategic vs PE criteria, EBITDA vs ARR, adjustment table
  • references/buyer-readiness-checklist.md — 24-month prep timeline
  • references/due-diligence-metrics-pack.md — standard metrics export for M&A
  • references/negotiating-earn-out.md — earn-out playbook, levers, decision tree, anti-patterns
  • templates/exit-readiness-scorecard.md — 1–5 scoring worksheet
  • templates/valuation-sensitivity-table.md — ARR, EBITDA, DCF, hold vs sell
  • templates/earn-out-term-sheet-review.md — founder worksheet for LOI/term sheet Cross-skill artifacts: saas-outcomes/references/exit-potential-scorecard.md, saas-outcomes/references/exit-metrics-matrix.md, saas-outcomes/references/bootstrap-founder-playbook.md, financial-modeling/references/unit-economics-exit-bridge.md, references/benchmark-reconciliation.md

Related Skills

  • saas-outcomes — path choice, exit-metrics matrix, bootstrap vs VC
  • saas-metrics-calculator — formulas and benchmarks
  • financial-modeling — unit-economics-exit-bridge, DCF
  • fundraising-strategy — alternative to exit if metrics support raise
  • soc2-compliance — enterprise diligence readiness
  • equity-management — cap table cleanup

⚠️ Disclaimer

This skill provides general informational guidance based on publicly available frameworks and operator experience. It is NOT legal advice, accounting advice, tax advice, or financial advice.

Consult qualified professionals for your specific situation — attorneys for legal and M&A matters, CPAs for tax and accounting. This skill does not create a professional-client relationship.

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 Exiting Company AI skill do?

Prepare a SaaS company for acquisition or exit — valuation drivers by buyer type (strategic, PE, bootstrap), due diligence readiness, EBITDA vs ARR multiples, and 12–24 month exit timeline. Use when planning an exit, preparing for acquisition, or maximizing company value for a future sale. Triggers on: "exit strategy", "sell company", "acquisition prep", "M&A", "due diligence", "company valuation", "exit planning", "PE acquisition", "bootstrap exit".

Why use Exiting Company on TypingMind?

Because you install it once and use it with any model. Exiting Company 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 Exiting Company in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeadMagic/gtm-skills/tree/main/skills/founder-led/exiting-company. 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 Exiting Company?

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 Exiting Company?

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

Is the Exiting Company AI skill free?

Yes. It is published on GitHub by LeadMagic 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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