DEI Dashboard

What it is: Diversity & inclusion.

Overview

Works out the smallest useful DEI Dashboard setup for the business in front of it, then builds it only when asked. The default output is a short recommendation, not a spreadsheet. Artifacts - CSV, SQL DDL, JSON Schema, Notion mapping - are produced on request, from one field list so they cannot drift apart.

Layer: Layer 6: Engage. Fits: Scale stage. Table code: n/a.

When to Use This Skill

• dei dashboard
• diversity reporting
• workforce diversity metrics
• inclusion tracker

Also use it when the user says "diversity & inclusion", or describes the same process happening in a spreadsheet, a document or someone inboxes.

Do not use it for: payroll calculation, tax filing, or legal advice. This skill produces empty templates only - it never holds or processes real employee or customer data.

How It Works

Follow the shared execution contract. The module-specific rules below define only domain fields, decisions, calculations, and safety constraints.

Step 1 - Identify intent

Read the request and pick the intent before asking anything.

• "set up" or "build" or "create" -> the user wants artifacts; go to Step 2.
• "our process is ..." or "it is in a sheet" -> the user wants to move an existing process; capture it, then Step 2.
• "is this right" or "review" or "audit" -> the user wants a check, not a build; answer from what they share.
• "how do I ..." -> advice question; answer directly and offer the build only if it helps.

Ask only if this is the highest-value missing fact; otherwise proceed without an opener:

Q: Which stages of hiring do you want to look at?

Step 2 - Ask only what is missing

Skip anything the user already answered, in any earlier message. Ask the rest one at a time, and stop as soon as the remaining answers would not change the output.

• Scope - Hiring, progression or both? / Which stages? / By department or overall?
• Data - What data exists today? / Voluntary self-ID? / Anonymised?
• Baselines - Compare against what? / External benchmark? / Internal target?
• Current process - Anything tracked now? / HRIS or a sheet? / Is it anonymised?
• Outcome - What do you need? / A metric set or a dashboard view?

Never invent an answer. If the user does not know, record it as unknown and carry on.

Step 3 - Hold the internal context

Hold the answers in this shape. It stays internal - it is not shown to the user unless they ask, and it never carries a value the user did not give.

module: dei-dashboard
intent: null            # setup | advice | review | fix | build | convert | export
scale: null             # Starter | Growth | Scale, only if the answer changes it
areas:
  "Scope": null
  "Data": null
  "Baselines": null
  "Current process": null
  "Outcome": null
requested_outputs: []   # csv | sql | json | notion | xlsx - requested formats only
confirmed_facts: []     # only what the user actually said
open_questions: []      # the unanswered ones, in the order worth asking

Step 4 - Recommend the smallest workflow

If an artifact was requested, build it after resolving essential missing facts. Otherwise give a short recommendation and offer the relevant artifact.

Recommended approach: Use voluntary, anonymised data and aggregate to groups large enough to protect people. Skip any breakdown that would identify someone.

Why this one: Diversity data is easy to collect and easy to misuse. Anonymity and minimum group size are conditions of doing it at all, not nice-to-haves.

Workflow: Voluntary data → Anonymised aggregation → Stage metrics → Review → Action

Step 5 - Build only on request

Once the user asks for it, derive the fields from the confirmed context and emit the requested artifacts. For machine-readable text, keep prose outside the data; for files, provide a usable link. Report material validation failures or limitations separately.

A selected Notion output is rendered by notion-manual-import, so route the Notion step there. When the user selects Notion, hand that step to @notion-manual-import: it holds the CSV, the property mapping, the import steps and the verification checklist, and it renders the Field Reference below instead of defining a table of its own. Do not restate the mapping here and do not improvise the import steps. Manual CSV and mapping outputs need no

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