Skill

Organization Design

Model departments, heads, headcounts and budgets as structured rows for an organization plan, then generate requested empty artifacts.


53
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out of 100
Updated 17 days ago
Source checked Oct 7, 2026
Version 19.0.1

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Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-organization-design | bash

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Overview

Organization Design

Model departments, heads, headcounts and budgets as structured rows for an organization plan, then generate requested empty artifacts. Requested empty artifacts share one field list. Use it for an organization chart template, department structure planner or headcount and budget plan.

What it does

Organization Design defines an organization structure as department records rather than a drawing. Each department has a head and an owner; the chart becomes a view of that data. Its recommended workflow moves through departments, owners, headcount and budget, a chart view and a quarterly refresh. Keeping rows as the maintained representation makes the chart regenerable when staffing plans change. The module fits the Foundation layer and Starter stage.

The default deliverable is a short recommendation. An explicit setup, build or conversion request produces artifacts after essential missing facts are resolved. Advice receives a direct answer, while a review works from the material provided. This keeps the size of the proposed setup tied to the requested outcome.

When to use - and when NOT to

Use it for an organization chart template, department structure planner or headcount and budget plan. It does not handle detailed reporting lines or dotted-line matrix structures; payroll calculation, tax filing and legal advice are outside scope.

This is an empty-template workflow, not processing of real employee or customer records. It does not compute payroll, tax, leave balances or KPIs. Automation, reminders and synchronization require the separate integration layer. Qualified human review is still required before the templates drive legal, tax or HR decisions.

Inputs and outputs

Intake covers department and business-unit structure, remote or on-site work, department heads, reporting lines, matrix versus simple ownership, team headcounts, annual budgets and cost centres. It also checks whether the current chart is stale and whether the result serves planning, hiring or budgeting. Questions are asked one at a time, excluding anything already answered in earlier messages. Unknown facts stay unknown. Intent, confirmed facts, open questions and requested formats remain internal unless the user asks to inspect them; no missing answer is invented.

The field model includes Department Name (text); Approved Headcount (number); Budget (Annual) (currency); Cost Center Code (text); Department Head (text); Department Type (select); Dept ID (id); Established Date (date); Headcount (number); Location (text); Notes (long_text); Parent Department (text); Status (select).

Department Type starts with Revenue, Delivery, Support, Finance, People, Admin, Engineering. Status starts with Proposed, Under Review, Approved, Implementing, Live, Superseded.

Requested CSV, SQL DDL, JSON Schema and Notion mappings derive from one field list. Display names remain identical across CSV and JSON, and normalized SQL identifiers are documented. Relation fields keep their relational meaning, dates remain dates and money remains currency. Machine-readable data is separated from explanation, with validation failures and limitations reported separately.

One supplied SQL example is:

CREATE INDEX idx_organization_design_status ON organization_design (status);

Excel-compatible CSV uses UTF-8 with a byte order mark. Because CSV has no column types, numeric, date and currency formatting is identified after the data. A CSV is not an .xlsx workbook; the latter is generated only when requested. Example rows require an explicit request and must be clearly synthetic. Sensitive identifiers are not unnecessarily repeated in a review, and generated templates remain empty.

Integrations

Notion output goes to notion-manual-import for the CSV, property mapping, import steps and verification checklist. Manual mappings require no connection. Requested workspace changes require verified tool access, the actual target and authorization; a claimed connection is insufficient evidence. Notion relation columns resolve only after both databases have been imported. Select options are an initial vocabulary that can be renamed to match the business. Real names, salaries, medical details and banking data are excluded from generated examples.

Source README

Works out the smallest useful Organization Design 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.

Discussion

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