Cowork Data Room Builder logo

Cowork Data Room Builder

Organization
OneWave-AI
cowork-data-room-builder

Prepare YOUR data room for a fundraise, acquisition, or bank diligence -- builds the checklist for your deal stage, sweeps your folders for what you already have, produces a gap report, and organizes everything into the structure buyers and investors expect. The sell-side complement to cowork-deal-room.

Overview

PublisherOneWave-AI
Repositoryclaude-skills
Skill namecowork-data-room-builder
Stars
293
Forks
49
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by OneWave-AI on GitHub. Read the source before you install it.

Installation

Install the Cowork Data Room Builder 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/OneWave-AI/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/cowork-data-room-builder .claude/skills/cowork-data-room-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cowork Data Room Builder 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 Cowork Data Room Builder 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 Cowork Data Room Builder 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.

Cowork Data Room Builder

Prepare a data room the way a banker's analyst does: know what the other side's diligence team will ask for before they ask, find it or flag it, and present it in the structure they expect. Inputs: the deal type (seed/Series A/growth round, acquisition, loan) and one or more folders of company documents.

Workflow

  1. Build the request list. Generate the diligence checklist for the stated deal type and stage: corporate records, cap table and securities, financials, material contracts, IP, employment, tax, insurance, litigation, and (for later stages) customer concentration and compliance. Present it for approval -- the user may know their acquirer's quirks.
  2. Sweep. Walk the provided folders and match every document to a checklist item. Classify each match FINAL (executed/signed), DRAFT, or STALE (superseded or older than the period requested). One file can satisfy multiple items.
  3. Gap report. Output the checklist with status per item: HAVE, HAVE-BUT-DRAFT, HAVE-BUT-STALE, MISSING. Rank the missing items by how early diligence will hit them (corporate formation docs and cap table before customer contracts). This report is the deliverable that saves the deal timeline.
  4. Organize. On approval, build the data room folder structure (numbered top-level sections matching the checklist), copy -- never move -- documents in with clean names (3.2-msa-acme-corp-executed-2025.pdf), and write INDEX.md mapping every checklist item to its file.
  5. Red-flag pass. Before anything is shared, list documents that need a decision: unsigned versions where an executed copy should exist, contracts with change-of-control or assignment clauses the deal will trigger, documents containing employee compensation or customer-identifying data that may warrant redaction or a later disclosure phase.

Rules

  • Copy, never move. The data room is a curated export; source folders stay untouched.
  • Never place a draft where a final belongs without labeling it DRAFT in the filename and index.
  • Never redact or exclude documents silently -- list redaction candidates and let counsel decide.
  • The gap report states what was searched, so "MISSING" means "not in the provided folders," not "does not exist."
  • Stage-appropriate depth: do not demand SOC 2 reports from a pre-seed company; do not omit them for a growth round.
  • This is preparation support, not legal or securities advice. Frame judgment calls for counsel.

Quick Commands

  • "Build the checklist for [deal type]" -- step 1 only
  • "What am I missing?" -- steps 1-3, the gap report
  • "Assemble the room from [folders]" -- full workflow
  • "Red-flag check" -- step 5 against an existing data room

Frequently asked questions

What does the Cowork Data Room Builder AI skill do?

Prepare YOUR data room for a fundraise, acquisition, or bank diligence -- builds the checklist for your deal stage, sweeps your folders for what you already have, produces a gap report, and organizes everything into the structure buyers and investors expect. The sell-side complement to cowork-deal-room.

Why use Cowork Data Room Builder on TypingMind?

Because you install it once and use it with any model. Cowork Data Room Builder 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 Cowork Data Room Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OneWave-AI/claude-skills/tree/main/cowork-data-room-builder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cowork Data Room Builder?

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 Cowork Data Room Builder?

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

Is the Cowork Data Room Builder AI skill free?

Yes. It is published on GitHub by OneWave-AI 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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