Scale Data Inventory

• Source: Built by Jonathan Kvarfordt. Standalone bundle v0.2.
• Frameworks applied: Step 2. Chart

It covers a job one of the eight revenue seats has to finish, and it states its process, decision rules, and output format clearly enough for an agent to follow.

1. 1.Copy the SKILL.md text below, or download the raw file.
2. 2.Create a folder named exactly scale-data-inventory in your agent's skills directory.
3. 3.Save the file inside that folder as SKILL.md.
4. 4.Ask the agent one of the trigger requests below.
5. 5.Check the output against what you already know before it leaves your desk.

• data inventory
• who owns our data
• is our data ready for AI

---
name: scale-data-inventory
description: Documents who owns each data source, where it lives, how it's collected, and how good it is, then flags what will break an AI deployment. Use when the user says "data inventory", "who owns our data", "is our data ready for AI", "where does our data live", "data quality check", or after scale-opportunity-matrix.
---

# scale-data-inventory

Produce `artifacts/scale-data-inventory.md` and update `context/stack.md`. This is the step people skip and regret.

## Preflight (every run)
1. Confirm `GTM-AI-OS/` is accessible. If not: "I need access to your GTM-AI-OS folder. Select it in Cowork's folder picker, or run `os-install` from the core plugin." Stop until it is.
2. Read `CLAUDE.md`, `INDEX.md`, and the last 20 lines of `signals/log.md`.
3. Check the prerequisites below. For anything missing, ask the cold-start questions and offer: (a) run the earlier skill now, or (b) fast path: answer the questions and this skill writes a minimal version of the missing artifact marked `status: draft (fast path)`.
4. On finish, update the artifact row in `INDEX.md` and append one line to `signals/log.md`: `<date> | <skill> | <produced> | <human changed> | <open question>`.

## Prerequisites
- `context/stack.md` at draft or better (from os-install).
Cold-start: "Name your CRM, your call recorder, and where email and enrichment data live." Write to `stack.md` and continue.

## Step 1: Sources
For every system in the friction map's workflow: what data it holds, who owns it (RevOps, IT, GTM engineering, enablement, a vendor), where it flows next, and whether it's reachable by API or MCP.

## Step 2: Collection
For each key field: is it entered by a human, synced, or generated? Apply the 5% rule: of what humans used to enter, about 5% still needs a human. List which fields those are and why.

## Step 3: Quality
Score key fields on complete, accurate, accessible, timely (1 to 5 each). If `~~crm` is connected, offer to sample field completion on the last 200 closed deals.

## Step 4: Blockers
Flag: no named owner; data trapped in a tool with no export; conflicting records across two systems; PII or regulated data with no policy (feeds Module 5 governance).

## Step 5: Write
Write the inventory. Set `context/stack.md` to `status: verified` if the user confirms.

## Hand off
Say: "Now pull the evidence for your ICP. Run `os-win-loss-extract`."

What does the Scale Data Inventory skill do?

Documents who owns each data source, where it lives, how it's collected, and how good it is, then flags what will break an AI deployment.

Where does the Scale Data Inventory skill come from?

Built by Jonathan Kvarfordt. Standalone bundle v0.2.. The source and included files are shown on this page and in the package download.

Why was the Scale Data Inventory skill chosen for this library?

It covers a job one of the eight revenue seats has to finish, and it states its process, decision rules, and output format clearly enough for an agent to follow.

When should the Scale Data Inventory skill not be used?

Use it only for the job named above. A skill applied outside its scope produces confident output on the wrong question.

How do I install the Scale Data Inventory SKILL.md file?

Download the file, create a folder named exactly scale-data-inventory inside your agent's skills directory, and save the file inside it as SKILL.md. The agent loads it when a request matches the description.