Publication Schema
The magazine behind read.
What it stores
The magazine behind read.purposeforwardtech.com — articles and the categories, authors, and series they belong to, plus lightweight reading analytics.
Owned by the Publication agent. Lives in the Public Pages database · public schema.
The tables
Friendly names first, with the real table name underneath. Key fields only.
Articlesblog_posts
Every article — content, hero imagery, SEO, layout, and reading time.
| Column | Type |
|---|---|
slug | Text |
title | Text |
statusdraft, published, archived | Choice |
layout_modestandard or immersive | Choice |
reading_timeMinutes | Number |
published_at | Date & time |
Relationships
- one-to-one
blog_categories. Sits in one category - one-to-one
blog_authors. Has one author - one-to-one
blog_series. May belong to a series
Categoriesblog_categories
The topic categories articles are filed under.
| Column | Type |
|---|---|
name | Text |
slug | Text |
description | Text |
Relationships
- one-to-many
blog_posts. Groups many articles
Authorsblog_authors
Author profiles.
| Column | Type |
|---|---|
name | Text |
title | Text |
bio | Text |
social_links | Structured |
Relationships
- one-to-many
blog_posts. Writes many articles
Seriesblog_series
Multi-part series that group related articles.
| Column | Type |
|---|---|
name | Text |
description | Text |
statusactive, complete, archived | Choice |
Relationships
- one-to-many
blog_posts. Contains ordered parts
Reading Analyticsblog_analytics
View and clap events per article.
| Column | Type |
|---|---|
event_typeview or clap | Choice |
created_at | Date & time |
Relationships
- one-to-one
blog_posts. Counts toward one article
You don't need all of this to start
Most of what these agents rely on has a simpler equivalent. Anywhere we use a database, you can usually start with a spreadsheet or a document — whatever you're comfortable with. Anywhere we built a custom MCP server, you can reach for a prebuilt AI connector instead of building your own.
We go further because it's where our experience pays off. Years of hands-on database work make a custom data layer feasible for us, and purpose-built MCP servers let us hand each agent a short, sharp instruction file and exactly the tools it needs — custom descriptions, only the endpoints we want, and the occasional extra gate — instead of a long manifesto or playbook. Nothing more, nothing less.
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