---
name: advertisement
description: Objects announce what they can do — The Sims style
allowed-tools:
  - read_file
  - write_file
  - list_dir
tier: 1
protocol: ADVERTISEMENT
related: [card, object, society-of-mind, room, action-queue, coherence-engine, needs, task]
tags: [moollm, game, interaction, sims, behavior, autonomy]
---

# Advertisement

> *"Objects don't wait to be used — they announce what they can do."*

---

## What Is It?

**Advertisement** is The Sims-style object interaction: every object in a room broadcasts its available actions, scored by relevance to the current context.

Instead of the user memorizing commands, objects **advertise** what's possible:

```
You approach the workbench.

Available actions (sorted by relevance):
  ⭐ CRAFT tool (you have materials)
  • EXAMINE blueprints
  • ORGANIZE parts
  • MORE options...
```

---

## The Sims Connection

In **The Sims**, objects have "advertisements" — each interaction scores based on:
- The Sim's current needs (hunger, fun, social)
- Object properties (a fridge scores high for hunger)
- Context (can't use stove if broken)

This extensible object architecture was **key to The Sims' massive success**:
- **User-created objects** — anyone could make new furniture, appliances, characters
- **Expansion packs** — just drop in new objects with their advertisements
- **No code changes** — objects self-describe their behaviors
- **Infinite variety** — the community created millions of objects

The same YAML file that defines what an object *is* also defines what it *can do*. Plug-in architecture for free.

MOOLLM applies this to **any object**:

```yaml
# workbench.yml
type: object
advertisements:
  - action: CRAFT
    score_if: "has_materials AND has_skill"
    satisfies: [productivity, creativity]
    
  - action: EXAMINE
    score_if: "always"
    satisfies: [curiosity]
    
  - action: MORE
    score_if: "always"
    satisfies: [exploration]
```

---

## How It Works

### 1. Objects Broadcast

Every object in the room has an `advertisements` list:

```yaml
advertisements:
  - action: USE
    description: "Activate this tool"
    preconditions: [in_inventory, charged]
    score: 80
    
  - action: EXAMINE
    description: "Look closely"
    preconditions: []  # always available
    score: 50
```

### 2. Context Scores

Scores adjust based on:
- **Character needs** — hungry character scores FOOD higher
- **Current goals** — research goal scores EXAMINE higher
- **Environment** — dark room scores LIGHT higher

### 3. Pie Menu Appears

Top actions surface in the [PIE-MENU](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/room):

```
    [CRAFT]
       ⭐
[ORGANIZE] • [EXAMINE]
       •
    [MORE]
```

Center = highest score = default action.

---

## Autonomous Selection

For **autonomous agents**, advertisements enable self-direction:

```
Agent evaluates all objects in room:
  workbench: CRAFT (85), EXAMINE (50)
  bookshelf: READ (70), ORGANIZE (30)
  door: EXIT (40)
  
Agent selects: CRAFT at workbench (score 85)
```

No hardcoded behavior. Objects define possibilities. Agent selects based on goals.

---

## Example: Smart Room

```yaml
# research-lab/ROOM.yml
objects:
  - microscope:
      advertisements:
        - action: ANALYZE_SAMPLE
          score_if: "has_sample"
          score: 90
        - action: CALIBRATE
          score_if: "accuracy < 0.9"
          score: 60
          
  - notebook:
      advertisements:
        - action: WRITE_NOTES
          score_if: "has_observations"
          score: 75
        - action: REVIEW
          score: 40
          
  - coffee_maker:
      advertisements:
        - action: BREW
          score_if: "fatigue > 0.3"
          score: 65
        - action: CLEAN
          score_if: "uses > 5"
          score: 30
```

Agent enters, sees:
```
Top actions:
  1. ANALYZE_SAMPLE at microscope (90) — you have a sample!
  2. WRITE_NOTES at notebook (75) — observations pending
  3. BREW at coffee_maker (65) — you're a bit tired
```

---

## SimAntics Heritage

This is **SimAntics** — The Sims' behavioral engine:

| SimAntics | MOOLLM |
|-----------|--------|
| Object advertisement | `advertisements:` list in YAML |
| Motive scores | Context-based scoring |
| Autonomous selection | Agent picks highest-scored action |
| Pie menu | [PIE-MENU](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/room) for user interaction |

Don Hopkins worked on SimAntics. This is that tradition, for LLM agents.

---

## HyperCard-Style Event Bubbling

When you click an advertised action, it triggers a **symbolic event** that bubbles up:

```
Click CRAFT on workbench

Event path:
  1. workbench (object)     → handles CRAFT? no, pass up
  2. workshop/ (room)       → handles CRAFT? no, pass up  
  3. building/ (parent)     → handles CRAFT? no, pass up
  4. world/ (root)          → handles CRAFT? no, check inheritance
  5. workbench-prototype    → handles CRAFT? YES → execute
```

Just like HyperCard: events bubble from button → card → background → stack.

### Containment Tree (Spatial)

Events bubble **up** the room hierarchy:

```
object in room in parent-room in world
   ↑         ↑              ↑        ↑
              event bubbles up
```

### Inheritance Graph (Prototype)

If no handler in containment tree, check the **prototype chain**:

```
workbench
   ↓ inherits from
furniture-prototype  
   ↓ inherits from
object-prototype     → has default CRAFT handler!
```

### Combined Path

```yaml
# Event resolution order:
1. The object itself
2. Parent room
3. Grandparent room
4. ... up to world root
5. Object's prototype
6. Prototype's prototype
7. ... up to root prototype
```

First handler that responds wins. Unhandled events can:
- Log a warning
- Trigger POSTEL (charitable interpretation)
- Invoke a default handler

### Example: Custom Behavior

```yaml
# workshop/ROOM.yml
handles:
  CRAFT: |
    # Room-level craft handler
    Check if character has required skill.
    Check if materials available in room.
    If conditions met, delegate to object.
    Otherwise, suggest where to get materials.
```

The room intercepts CRAFT before it reaches the object, adding room-specific logic.

---

## Dovetails With

- [Room](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/room) — Where objects live and advertise
- [PIE-MENU](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/room) — How advertisements surface to users
- [SNAP-CURSOR](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/room) — Context-aware object interaction
- [Coherence Engine](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/coherence-engine) — Evaluates and selects actions
- [Trading Card](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/card) — Cards can advertise too
- [Rubric](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/rubric) — **Scoring criteria** for advertisement evaluation
- [Scoring](https://github.com/SimHacker/moollm/tree/b38fddeee4512e9111afe056cee4348097e54a3f/skills/scoring) — How scores are calculated and valued

---

## Protocol Symbols

```
ADVERTISEMENT        — Objects announce available actions
AUTONOMOUS-SELECTION — Agent picks based on scores
SIMANTICS            — The Sims behavioral model
PIE-MENU             — Radial display of options
FLY-UNDER-RADAR      — Normalize through defaults
PROCEDURAL-RHETORIC  — Rules carry ideology
```

See: [PROTOCOLS.yml](references/upstream/e063d93edfc830e6-PROTOCOLS.yml)

---

## The Deep Insight

From [SIMANTICS](references/upstream/e063d93edfc830e6-PROTOCOLS.yml):

> *"The Sims' AI isn't centralized — it's distributed throughout objects."*
> *"A refrigerator knows it offers food. A bed knows it offers sleep."*
> *"The Sim chooses from what's advertised nearby."*

This IS MOOLLM's architecture. Objects self-describe. The coherence engine orchestrates. Intelligence is **distributed** throughout the world.

The advertisements ARE the AI.


---
Source attribution: SimHacker
Original project: https://github.com/SimHacker/moollm/blob/b38fddeee4512e9111afe056cee4348097e54a3f/skills/advertisement/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Don Hopkins

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: SimHacker
Original project: https://github.com/SimHacker/moollm/blob/b38fddeee4512e9111afe056cee4348097e54a3f/skills/advertisement/SKILL.md
Attribution basis: Recovered original package and original project license at a pinned revision

Fields of work: Design, Development & Engineering, Product Management
Roles: Game Developer, Product Manager, UX Designer
Specialties: API
Tools: Moollm
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 506a7824a9d710ffcb48a1fac9caa4298f250e540966aa9ee87b9f776d988c5b
Metadata reviewed: 2026-10-27
This metadata supersedes earlier Dave AI catalog attribution. Original instruction and supporting files are preserved.
