Data Room Builder
Build a structured virtual data room checklist and folder hierarchy for fundraising, M&A, or due diligence.
About this skill
This AI agent skill, 'Data Room Builder', streamlines the complex process of preparing a virtual data room. It takes key information like company stage, industry, and deal type, then generates a robust plan encompassing a multi-category folder structure (e.g., Corporate, Financial, Legal, Product & Tech, HR & Team, Compliance). The skill also produces a prioritized document checklist, categorizing items as 'must-have', 'should-have', or 'nice-to-have' to clearly indicate urgency. Furthermore, it performs a gap analysis, highlighting missing documents and estimating production time, and offers valuable recommendations for access control based on document sensitivity. Users benefit from a structured, stage-appropriate roadmap to organize critical company records, ensuring thoroughness and professionalism when engaging with investors or acquirers. It helps save significant time and reduces the risk of overlooking essential documentation during high-stakes transactions.
Best use case
This skill is primarily used by startups, companies undergoing M&A, or those preparing for due diligence to systematically organize and identify necessary documentation. It benefits founders, finance teams, and legal departments by streamlining the laborious process of data room preparation, ensuring all critical documents are accounted for and presented professionally.
Build a structured virtual data room checklist and folder hierarchy for fundraising, M&A, or due diligence.
A customized, structured virtual data room plan including a folder hierarchy, a prioritized document checklist with urgency levels, a gap analysis, and access control recommendations.
Practical example
Example input
I'm a SaaS startup at the Seed stage, raising my first institutional round. We operate in the B2B FinTech industry. Investors have specifically asked for our churn metrics and customer retention data.
Example output
Generated a Seed stage data room plan for your B2B FinTech startup. Includes a 'Corporate', 'Financial', 'Legal', 'Commercial', 'Product & Tech', 'HR & Team', and 'Compliance' folder structure. A prioritized document checklist marks 'Articles of Incorporation' (🔴 Must-have) and 'Customer Contracts' (🟡 Should-have). Gap analysis noted '3 years audited financials' as not applicable for Seed. Access control suggests 'Board Minutes' require NDA.
When to use this skill
- Preparing to raise a funding round (Seed through Series C+)
- Selling a business or going through M&A due diligence
- Responding to investor or acquirer document requests
- Organizing company records for board governance
When not to use this skill
- If you already have a fully prepared data room with all documents organized.
- When seeking legal advice on document content rather than organizational structure.
- For general, non-deal-related file management tasks.
- To generate the actual legal or financial documents themselves.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/afrexai-data-room/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Data Room Builder Compares
| Feature / Agent | Data Room Builder | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
Build a structured virtual data room checklist and folder hierarchy for fundraising, M&A, or due diligence.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Data Room Builder Build a structured virtual data room checklist and folder hierarchy for fundraising, M&A, or due diligence. ## When to Use - Preparing to raise a funding round (Seed through Series C+) - Selling a business or going through M&A due diligence - Responding to investor or acquirer document requests - Organizing company records for board governance ## How It Works User provides: company stage, industry, round type (or M&A), and any specific investor requests. You generate: ### 1. Folder Structure A complete directory tree organized by category: - **Corporate** — Articles of incorporation, bylaws, board minutes, cap table, shareholder agreements - **Financial** — P&L (3 years + projections), balance sheet, cash flow, burn rate, revenue breakdown, tax returns - **Legal** — IP assignments, employment agreements, NDAs, litigation history, regulatory filings - **Commercial** — Customer contracts, pipeline, churn data, pricing history, partnership agreements - **Product & Tech** — Architecture docs, security audit, uptime history, roadmap, tech stack summary - **HR & Team** — Org chart, key employee bios, compensation summary, option pool, hiring plan - **Compliance** — Data privacy (GDPR/CCPA), insurance certificates, permits, audit reports ### 2. Document Checklist For each folder, a prioritized checklist: - 🔴 **Must-have** — Deal won't close without it - 🟡 **Should-have** — Expected, absence raises questions - 🟢 **Nice-to-have** — Shows maturity, not required ### 3. Gap Analysis Compare what the user has against the checklist. Flag missing documents with urgency level and estimated time to produce. ### 4. Access Control Recommendations - Which documents go in the "teaser" (pre-NDA) - Which require NDA - Which are management-presentation-only - Watermarking and download restrictions ## Rules - Tailor depth to company stage — don't ask a pre-seed startup for 3 years of audited financials - Flag documents that typically need legal review before sharing - Include estimated prep time for each missing document - Output as Markdown checklist (copy-paste into Notion, Google Docs, or actual data room platform) ## Output Format Markdown with nested checklists. Each item: `- [ ] Document Name` with priority tag and notes.
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