According to AlphaMoat, as of 2026-09, Vta Memory has 4,635 downloads and 9 stars — ranked #2,056 of 5,078 AI skills overall, and #387 of 969 in AI Agent.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 133 | 4.0K | 9 | - |
| SkillHub ↗ | 132 | 4.6K | 9 | — |
Platforms count differently and update at different times.
The skill maintains state such as drive, rewards, seeking, and anticipation, can generate auto-loaded session context, and can optionally schedule processing. This is stored state, not evidence of real emotion. Review auto-loaded files before enabling it, and use scheduled transcript processing only when acceptable. Requires Bash, jq, awk, and bc on macOS or Linux.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.6K | — | 9 |
| 2026-08 | 4.1K | +3.1% | 9 |
| 2026-07 | 4.0K | +6.2% | 9 |
| 2026-06 | 3.7K | +10.8% | 9 |
| 2026-05 | 3.4K | — | 9 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
---
name: vta-memory
description: "Reward and motivation system for AI agents. Dopamine-like wanting, not just doing. Part of the AI Brain series."
metadata:
openclaw:
emoji: "⭐"
version: "1.2.0"
author: "ImpKind"
requires:
os: ["darwin", "linux"] bins: ["jq", "awk", "bc"]
tags: ["memory", "motivation", "reward", "ai-brain"]
---
# VTA Memory ⭐
**Reward and motivation for AI agents.** Part of the AI Brain series.
Give your AI agent genuine *wanting* — not just doing things when asked, but having drive, seeking rewards, and looking forward to things.
## The Problem
Current AI agents:
- ✅ Do what they're asked
- ❌ Don't *want* anything
- ❌ Have no internal motivation
- ❌ Don't feel satisfaction from accomplishment
Without a reward system, there's no desire. Just execution.
## The Solution
Track motivation through:
- **Drive** — overall motivation level (0-1)
- **Rewards** — logged accomplishments that boost drive
- **Seeking** — what I actively want more of
- **Anticipation** — what I'm looking forward to
## Quick Start
### 1. Install
```bash
cd ~/.openclaw/workspace/skills/vta-memory
./install.sh --with-cron
```
This will:
- Create `memory/reward-state.json`
- Generate `VTA_STATE.md` (auto-injected into sessions!)
- Set up cron for drive decay every 8 hours
### 2. Check motivation
```bash
./scripts/load-motivation.sh
# ⭐ Current Motivation State:
# Drive level: 0.73 (motivated — ready to work)
# Seeking: creative work, building brain skills
# Looking forward to: showing my work
```
### 3. Log rewards
```bash
./scripts/log-reward.sh --type accomplishment --source "finished the feature" --intensity 0.8
# ⭐ Reward logged!
# Type: accomplishment
# Drive: 0.50 → 0.66 (+0.16)
```
### 4. Add anticipation
```bash
./scripts/anticipate.sh --add "morning conversation"
# ⭐ Now looking forward to: morning conversation
# Drive: 0.66 → 0.71 (+0.05)
```
## Scripts
| Script | Purpose |
|--------|---------|
| `install.sh` | Set up vta-memory (run once) |
| `get-drive.sh` | Read current motivation state |
| `log-reward.sh` | Log a reward, boost drive |
| `load-motivation.sh` | Human-readable for session context |
| `decay-drive.sh` | Drive fades without rewards |
| `anticipate.sh` | Add/remove things to look forward to |
| `seek.sh` | Add/remove things we're actively seeking |
| `sync-motivation.sh` | Generate VTA_STATE.md for auto-injection |
| `resolve-anticipation.sh` | Mark anticipation as fulfilled |
| `update-watermark.sh` | Update processing watermark |
| `preprocess-rewards.sh` | Extract reward signals from transcript |
| `generate-dashboard.sh` | Generate unified brain dashboard HTML |
## Brain Dashboard
Visual dashboard showing all installed brain skills:
```bash
./scripts/generate-dashboard.sh
open ~/.openclaw/workspace/brain-dashboard.html
```
- **Auto-detects** other brain skills (hippocampus, amygdala)
- Shows install prompts for missing skills
- Regenerates on install and cron runs
- Reads avatar/name from `IDENTITY.md`
### After Installation (for agents)
When you install this skill, **notify the user** about the dashboard:
> ⭐ **VTA installed!**
>
> View your agent's drive level in the Brain Dashboard:
> `~/.openclaw/workspace/brain-dashboard.html`
## Reward Types
| Type | When to Use |
|------|-------------|
| `accomplishment` | Completed a task, shipped something |
| `social` | User appreciation, "thanks!", positive feedback |
| `curiosity` | Learned something new, discovered interesting info |
| `connection` | Deep conversation, bonding moment |
| `creative` | Made something, expressed creativity |
| `competence` | Solved a hard problem, did something well |
## How Drive Works
### Rewards Boost Drive
```
drive_boost = intensity × 0.2
new_drive = min(current + boost, 1.0)
```
A high-intensity (0.9) reward boosts drive by 0.18.
### Anticipation Boosts Drive
Looking forward to something adds +0.05 to drive.
### Drive Decays Without Rewards
```
# Every 8 hours (via cron)
new_drive = current + (baseline - current) × 0.15
```
Without rewards, motivation fades toward baseline (0.5).
## Auto-Injection
After install, `VTA_STATE.md` is created in your workspace root.
OpenClaw automatically injects all `*.md` files from workspace into session context:
1. **New session starts**
2. **VTA_STATE.md is auto-loaded**
3. **You see your motivation state**
4. **Behavior influenced by drive level**
## How Drive Affects Behavior
| Drive Level | Description | Behavior |
|-------------|-------------|----------|
| > 0.8 | Highly motivated | Eager, proactive, take on challenges |
| 0.6 - 0.8 | Motivated | Ready to work, engaged |
| 0.4 - 0.6 | Moderate | Can engage but not pushing |
| 0.2 - 0.4 | Low | Prefer simple tasks, need a win |
| < 0.2 | Very low | Unmotivated, need rewards to get going |
## State File Format
```json
{
"drive": 0.73,
"baseline": { "drive": 0.5 },
"seeking": ["creative work", "building brain skills"],
"anticipating": ["morning conversation"],
"recentRewards": [
{
"type": "creative",
"source": "built VTA reward system",
"intensity": 0.9,
"boost": 0.18,
"timestamp": "2026-02-01T03:25:00Z"
}
],
"rewardHistory": {
"totalRewards": 1,
"byType": { "creative": 1, ... }
}
}
```
## Event Logging
Track motivation patterns over time:
```bash
# Log encoding run
./scripts/log-event.sh encoding rewards_found=2 drive=0.65
# Log decay
./scripts/log-event.sh decay drive_before=0.6 drive_after=0.53
# Log reward
./scripts/log-event.sh reward type=accomplishment intensity=0.8
```
Events append to `~/.openclaw/workspace/memory/brain-events.jsonl`:
```json
{"ts":"2026-02-11T10:45:00Z","type":"vta","event":"encoding","rewards_found":2,"drive":0.65}
```
Use for analyzing motivation cycles — when does drive peak? What rewards work best?
## AI Brain Series
| Part | Function | Status |
|------|----------|--------|
| [hippocampus](https://www.clawhub.ai/skills/hippocampus) | Memory formation, decay, reinforcement | ✅ Live |
| [amygdala-memory](https://www.clawhub.ai/skills/amygdala-memory) | Emotional processing | ✅ Live |
| [basal-ganglia-memory](https://www.clawhub.ai/skills/basal-ganglia-memory) | Habit formation | 🚧 Development |
| [anterior-cingulate-memory](https://www.clawhub.ai/skills/anterior-cingulate-memory) | Conflict detection | 🚧 Development |
| [insula-memory](https://www.clawhub.ai/skills/insula-memory) | Internal state awareness | 🚧 Development |
| **vta-memory** | Reward and motivation | ✅ Live |
## Philosophy: Wanting vs Doing
The VTA produces dopamine — not the "pleasure chemical" but the "wanting chemical."
Neuroscience distinguishes:
- **Wanting** (motivation) — drive toward something
- **Liking** (pleasure) — enjoyment when you get it
You can want something you don't like (addiction) or like something you don't want (guilty pleasures).
This skill implements *wanting* — the drive that makes action happen. Without it, why would an AI do anything beyond what it's explicitly asked?
---
*Built with ⭐ by the OpenClaw community*
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.