Ralph JusticeHub Storyteller

You can automate social content production by coordinating input agents, generation tasks, and human review within a git-backed pipeline. This creates story briefs, drafts, and social content across categories while storing artifacts in an auditable, versioned directory.

An autonomous storytelling loop coordinates input agents, generation tasks, and human review to automate end-to-end content production. It generates story briefs, drafts, and social content across categories like seeds, growth, harvest, and roots for a unified story feed.

You track content generation progress using database-backed progress tracking within the pipeline. By running a status command, you monitor the generation of story briefs, drafts, and social content artifacts as they move through the review stages.

You do not need Supabase to generate content, but it is used for publishing. The pipeline outputs stored in a structured directory can be loaded into Supabase to publish the generated story briefs, drafts, and social content.

Automated storytelling pipelines apply governance safeguards including brand alignment and safety checks. These are enforced through self-checks, learning logs, and a git-based audit trail to ensure generated social content meets compliance standards.

Yes, you can use AI agents to generate categorized story briefs for a unified story feed. The pipeline coordinates these agents to produce content across seeds, growth, harvest, and roots categories with versioned artifact storage.