A red-team M&A diligence skill that simulates an acquirer's internal review, estimates price chips, and prioritizes fixes or disclosures before a sale.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install acquirer-red-team
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install acquirer-red-team using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Acquirer Red Team?
Acquirer Red Team is an M&A stress-test in Openclaw Skills that mimics the buyer's internal deal team, not the polite data-room reviewer. It scans the business for the issues most likely to compress valuation: revenue quality, customer concentration, key-person risk, technology and IP transferability, and legal or compliance exposure.
For each finding, it turns the concern into a price mechanism and a defensible chip estimate, then finishes with an out-of-character debrief that tells the seller what is fixable, what should be pre-disclosed, and what is structural. The result is a practical pre-diligence memo you can use to sharpen negotiations and protect credibility before a real process begins.
Acquirer Red Team Use Cases
- Preparing for a sale and wanting to see how an acquirer will attack valuation
- Running a pre-diligence audit before banker outreach or IOI/SOI collection
- Identifying what DD will likely find in revenue quality, concentration, or tech debt
- Stress-testing founder dependency, contractor IP assignment, or customer consent issues
- Comparing how a strategic buyer versus a PE buyer will retrade price
- Turning sensitive skeletons into a fix-first or disclose-first action plan in Openclaw Skills
How Acquirer Red Team Works
- Gather the minimum facts: recurring versus one-time revenue, growth, team size, customer count and concentration, stack age, known sensitive issues, and the likely buyer frame.
- Interpret the transaction lens: default to a strategic acquirer unless the user specifies PE, because the chip mechanism and retrade logic differ.
- Evaluate the five hunting grounds: revenue quality, concentration, key-person risk, tech and IP, and legal and compliance.
- For each issue, request the evidence a deal team would ask for and assign a price mechanism such as multiple compression, holdback, earnout shift, or retention carve-out.
- Produce the internal memo with a summary box, a findings table, and the exact retrade script the corp-dev lead would use on the call.
- Switch out of character for the debrief and rank issues by fixability, time-to-fix, and whether they should be pre-disclosed before a real process begins in Openclaw Skills.
Acquirer Red Team Setup
No local installation is required. Openclaw Skills works by supplying the business facts and deal context directly in the prompt.
Prepare a concise diligence brief with the required inputs so the skill can price each finding accurately:
cat > diligence-brief.md <<'EOF'
Business:
Revenue mix (recurring vs one-time):
Growth:
Team size:
Customer count:
Customer concentration:
Stack age:
Known sensitive issues:
Deal frame (strategic or PE):
Rough multiple expectation:
Skeletons / concerns you hope nobody asks about:
EOF
Then paste the brief into the Openclaw Skills request and ask for an acquirer red-team memo. If you know the buyer type, include it; if not, let the skill default to a strategic acquirer. Review the output with M&A counsel and your banker before using it in a real process.
Acquirer Red Team Data Schema & Taxonomy
Default output is a single structured memo; no auxiliary files are generated unless you export or save the report yourself.
| Layer | Fields | Purpose |
|---|---|---|
| Input brief | business, revenue mix, growth, team size, customer count, concentration, stack age, sensitive issues, deal frame, multiple expectation, skeletons | Raw evidence base for the red-team simulation |
| Project header | codename, simulation notice, asking frame | Context for the memo |
| Summary box | current view, total identified chips, walk-away risks | Fast executive readout |
| Finding record | category, finding, evidence requested, price mechanism, chip estimate, assumptions | One row per red flag |
| Retrade script | exact buyer-facing sentence for the largest issue | Models the internal negotiation move |
| Debrief record | fixable pre-process, fix and time-to-fix, pre-disclose guidance | Separates remediation from concealment |
Metadata taxonomy used by Openclaw Skills:
- Category taxonomy: revenue quality, concentration, key-person risk, tech and IP, legal and compliance
- Mechanism taxonomy: multiple compression, holdback, earnout shift, retention carve-out, escrow, walk-away
- Assumption labels: explicit assumptions must be called out when data is incomplete
- Severity logic: issues are ranked by valuation impact and deal-breaker risk, with revenue quality examined first and hardest
- Evidence standard: every finding must trace to supplied facts or a clearly labeled assumption
Acquirer Red Team Advanced Features
- Five-hunting-grounds red-team framework tailored to M&A diligence
- Buyer-frame sensitivity for strategic versus PE retrade behavior
- Mechanism-based pricing chips instead of vague risk flags
- Exact retrade script generation for the largest valuation issue
- Out-of-character debrief that cleanly separates fix, pre-disclose, and structural risk
- Assumption labeling so Openclaw Skills never invents skeletons beyond the supplied facts
- Built-in quality checks that enforce evidence tracing and price mechanisms
- Retention-package and holdback awareness so seller-proceeds impact is explicit
SKILL.md
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