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vta-memoryvta 内存

Agent Skill

vta-memory 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

93,472

周安装

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GitHub Stars

9

下载量

32,731
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:vta-memory(vta 内存)
来源仓库:https://github.com/impkind/vta-memory
安装命令:
openclaw skills install vta-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install vta-memory

简介

AI Agent的奖励和激励系统。多巴胺般的渴望,而不仅仅是做。人工智能大脑系列的一部分。

SKILL.md

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

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

./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

./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

./scripts/anticipate.sh --add "morning conversation"

# ⭐ Now looking forward to: morning conversation
#    Drive: 0.66 → 0.71 (+0.05)

Scripts

ScriptPurpose
install.shSet up vta-memory (run once)
get-drive.shRead current motivation state
log-reward.shLog a reward, boost drive
load-motivation.shHuman-readable for session context
decay-drive.shDrive fades without rewards
anticipate.shAdd/remove things to look forward to
seek.shAdd/remove things we're actively seeking
sync-motivation.shGenerate VTA_STATE.md for auto-injection
resolve-anticipation.shMark anticipation as fulfilled
update-watermark.shUpdate processing watermark
preprocess-rewards.shExtract reward signals from transcript
generate-dashboard.shGenerate unified brain dashboard HTML

Brain Dashboard

Visual dashboard showing all installed brain skills:

./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

TypeWhen to Use
accomplishmentCompleted a task, shipped something
socialUser appreciation, "thanks!", positive feedback
curiosityLearned something new, discovered interesting info
connectionDeep conversation, bonding moment
creativeMade something, expressed creativity
competenceSolved 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 LevelDescriptionBehavior
> 0.8Highly motivatedEager, proactive, take on challenges
0.6 - 0.8MotivatedReady to work, engaged
0.4 - 0.6ModerateCan engage but not pushing
0.2 - 0.4LowPrefer simple tasks, need a win
< 0.2Very lowUnmotivated, need rewards to get going

State File Format

{
  "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:

# 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:

{"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

PartFunctionStatus
hippocampusMemory formation, decay, reinforcement✅ Live
amygdala-memoryEmotional processing✅ Live
basal-ganglia-memoryHabit formation🚧 Development
anterior-cingulate-memoryConflict detection🚧 Development
insula-memoryInternal state awareness🚧 Development
vta-memoryReward 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*

适合场景

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02

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03

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能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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74.42%
按下载量换算24,358

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需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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