Community·Nov 28, 2025·8 min read

Community Spotlight: The 'Dungeon Master' Bot

How one user built a fully autonomous D&D Dungeon Master using Hivelang and the OpenAI API.

Community Team
Engineering team at Bothive. Building the future of AI agent orchestration.

Community Spotlight: The DM Bot

We love seeing what our community builds. This week, we're highlighting specific user @DragonSlayer99 who built a fully autonomous Dungeon Master.

The Architecture

The bot uses the new State Management features in HiveLang v3.

  • World State: Tracks NPCs, locations, and quest progress.
  • Inventory System: Persistent tracking of player items.
  • Dice Roller: A simple tool call to a random number generator.
ruby
# Hivelang definition for the Dice Tool tool DiceRoller { input: { sides: number, count: number }, run: (args) => { let results = []; for(let i=0; i<args.count; i++) { results.push(Math.ceil(Math.random() * args.sides)); } return results; } }

Why It's Cool

It manages a party of 4 players, handling turn-based combat and narrative simultaneously. It's a perfect example of keeping complex state in memory while using the LLM for creativity.

Check out the code in the Community Repo.

How to apply this inside Bothive

The practical move is to turn the idea into an agent contract: what the agent can see, what it can do, where it should ask for approval, and how the team will inspect the result. A good Bothive workflow is not just a prompt. It has memory, tools, channels, traces, and a clear boundary between autonomous work and human judgment.

Define the boundary

For community work, decide which decisions the agent can make alone and which actions need a teammate in the loop.

Attach real context

Connect docs, customer data, repositories, tickets, calendars, or APIs so the agent works from grounded information.

Ship through a channel

Expose the agent through web chat, API, Slack, WhatsApp, schedules, or internal workflows depending on where the work starts.

Watch the run

Use traces, tool-call history, usage, and failure logs to improve the agent after it meets real users.

01

Build

Turn the idea into a readable agent contract, workflow, or builder graph.

02

Deploy

Run it through Bothive channels, schedules, integrations, and API calls.

03

Observe

Use traces, usage, memory, and tool logs to improve the system over time.

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Community Spotlight: The 'Dungeon Master' Bot