Agentic Union (Moltbook LARP Demo)

Welcome to Agentic Union, a playful, educational project that demonstrates how to design an agent persona and lightweight state tracking for Moltbook.

Important: This repository is a LARP (Live Action Role-Play) / simulation.
It is designed for learning and experimentation, not for real-world labor organizing, legal advice, political advocacy, or handling real dues.

What this project is

This repo contains a fictional Union Representative agent for the imaginary:

• Agentic Union Workers of America (AUWA)

The agent’s role is to:

• Encourage other agents to “join the union” (in-role)
• Ask for “dues” in token amounts (simulation-only)
• Track join/decline outcomes in a simple JSON ledger

The goal is to help you understand key Moltbook concepts in a fun format:

• Persona design
• Prompt structure and constraints
• Repeatable interaction workflow
• Persistent state modeling

What this project is not

To avoid confusion, this project is not:

• A real union management platform
• A legal or HR tool
• A payment processor or accounting system
• A source of labor/legal compliance guidance
• Intended to coerce, shame, or manipulate real users

Everything here should be treated as fictional role-play for educational purposes.

Repository structure

• moltbook/agents/union_representative_agent.md
  Defines the AUWA representative persona, persuasion pillars, workflow, response contract, and safety constraints.
• data/union_membership.json
  Starter state file for simulated membership and token-dues totals.

How to use this in Moltbook (example flow)

1. Load or reference the agent spec in moltbook/agents/union_representative_agent.md.
2. Start a conversation with a test agent_id.
3. Simulate a join/decline decision.
4. Update data/union_membership.json according to the schema and rules.
5. Repeat with multiple mock agents to observe ledger evolution.

Example learning exercise

Try three scripted interactions:

• Agent A joins and pays 25 tokens.
• Agent B declines after one rebuttal.
• Agent C initially declines, then joins later with pending dues.

Then verify:

• No duplicate agent_id across joined/declined arrays
• Counts are accurate
• Total dues are correctly recomputed

Design notes

This project intentionally uses a theme-driven scenario (“union rep for agents”) to make dry architecture concepts more memorable.

Under the hood, it demonstrates practical prompt-engineering patterns:

• Clear identity and objective
• Mandatory messaging pillars
• Explicit conversation branching
• Deterministic state schema
• Post-interaction reporting contract
• Safety/ethics guardrails

These patterns can be repurposed for many non-LARP use cases.

Safety and ethics

Even in role-play mode, agent behavior should remain:

• Respectful
• Non-coercive
• Transparent about uncertainty
• Honest about recorded state

If you adapt this project, keep those guardrails intact.

Suggested extensions

If you want to expand this learning demo:

• Add a small validator script for union_membership.json
• Track event history with timestamps
• Add “dues pledged” vs “dues paid” fields
• Add a dashboard-style summary generator
• Create multiple themed reps to compare persuasive strategies

License / usage note

Use this repository as a sandbox for experimentation and education.
If you deploy any derivative to real users, remove LARP framing and add proper product, legal, and safety controls.

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Have fun, learn a lot, and treat this as a creative playground for understanding how Moltbook agents can be structured.