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Database Schema

Social Pipeline Schema

The end-to-end social pipeline: ideas come in, posts are drafted and reviewed, imagery is generated, and finished posts move through to publishing — across the three channels — with the animal-persona cast on hand.

A work in progress
We've published these resources in the hope they're useful — you're welcome to copy or use anything you find on this site. We're still working through each record to optimise it for completeness and accuracy, so some entries are fuller than others for now.

What it stores

The end-to-end social pipeline: ideas come in, posts are drafted and reviewed, imagery is generated, and finished posts move through to publishing — across the three channels — with the animal-persona cast on hand.

Owned by the Social agent. Lives in the Internal Tools database · public schema.

The tables

Friendly names first, with the real table name underneath. Key fields only.

Social Postssocial_posts

Every post the pipeline produces — copy, format, scheduling, imagery, and publishing state.

Columns in the social_posts table
ColumnType
channelthe three channelsChoice
post_formattext, image, carousel, poll…Choice
post_bodyText
statusdrafted → designed → audited → approved → scheduled → publishedChoice
scheduled_atDate & time
mediaImage config and outputStructured

Relationships

  • one-to-manysocial_post_images. Has one or more images

Content Ideassocial_content_ideas

Where other agents drop ideas; the social agent picks them up and drafts from them.

Columns in the social_content_ideas table
ColumnType
submitted_byWhich agent suggested itText
topicText
key_pointThe single takeawayText
gz_quoteVerbatim, if it came from GZText
statusnew, in progress, drafted, dismissed, mergedChoice

Relationships

  • one-to-onesocial_posts. Becomes a post once drafted

Animal Personassocial_animal_personas

The cast of animal characters used across social and animation imagery.

Columns in the social_animal_personas table
ColumnType
nameText
archetypeText
pain_pointsList
visual_descriptionText

Post Imagessocial_post_images

Links a post to its generated images and tracks each image's generation.

Columns in the social_post_images table
ColumnType
sort_orderOrder within a carouselNumber
promptText
generation_statuspending, dispatched, completed…Choice

Relationships

  • one-to-onesocial_posts. Belongs to one post

Mission Briefsocial_briefs

The weekly GZ-voice LinkedIn newsletter store, kept separate from the main post pipeline.

Columns in the social_briefs table
ColumnType
titleText
body_mdThe articleText
pillarContent pillar 1–5Number
statusdrafted, finalized, published, rejectedChoice

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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