[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FS32PE289T2797SCHZVBVJ":3,"skill-same:01M6FS32PE289T2797SCHZVBVJ":132},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":28,"linkOnly":29,"markdownContent":30,"markdownBody":31,"frontMatter":32,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":53,"install":54,"resources":67},"01M6FS32PE289T2797SCHZVBVJ","vta-memory",null,"Reward and motivation system for AI agents. Dopamine-like wanting, not just doing. Part of the AI Brain series.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Fvta-memory\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27],"memory","vta memory","ai agents","linux","system","just","jq","brain","series","awk","2026-11-10 10:12:30",false,"---\nname: vta-memory\ndescription: \"Reward and motivation system for AI agents. Dopamine-like wanting, not just doing. Part of the AI Brain series.\"\nmetadata:\n  openclaw:\n    emoji: \"⭐\"\n    version: \"1.2.1\"\n    author: \"ImpKind\"\n    requires:\n      os: [\"darwin\", \"linux\"]\n      bins: [\"jq\", \"awk\", \"bc\"]\n    tags: [\"memory\", \"motivation\", \"reward\", \"ai-brain\"]\n---\n\n# VTA Memory ⭐\n\n**Reward and motivation for AI agents.** Part of the AI Brain series.\n\nGive your AI agent genuine *wanting* — not just doing things when asked, but having drive, seeking rewards, and looking forward to things.\n\n## The Problem\n\nCurrent AI agents:\n- ✅ Do what they're asked\n- ❌ Don't *want* anything\n- ❌ Have no internal motivation\n- ❌ Don't feel satisfaction from accomplishment\n\nWithout a reward system, there's no desire. Just execution.\n\n## The Solution\n\nTrack motivation through:\n- **Drive** — overall motivation level (0-1)\n- **Rewards** — logged accomplishments that boost drive\n- **Seeking** — what I actively want more of\n- **Anticipation** — what I'm looking forward to\n\n## Quick Start\n\n### 1. Install\n\n```bash\ncd ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Fvta-memory\n.\u002Finstall.sh --with-cron\n```\n\nThis will:\n- Create `memory\u002Freward-state.json`\n- Generate `VTA_STATE.md` (auto-injected into sessions!)\n- Set up cron for drive decay every 8 hours\n\n### 2. Check motivation\n\n```bash\n.\u002Fscripts\u002Fload-motivation.sh\n\n# ⭐ Current Motivation State:\n# Drive level: 0.73 (motivated — ready to work)\n# Seeking: creative work, building brain skills\n# Looking forward to: showing my work\n```\n\n### 3. Log rewards\n\n```bash\n.\u002Fscripts\u002Flog-reward.sh --type accomplishment --source \"finished the feature\" --intensity 0.8\n\n# ⭐ Reward logged!\n#    Type: accomplishment\n#    Drive: 0.50 → 0.66 (+0.16)\n```\n\n### 4. Add anticipation\n\n```bash\n.\u002Fscripts\u002Fanticipate.sh --add \"morning conversation\"\n\n# ⭐ Now looking forward to: morning conversation\n#    Drive: 0.66 → 0.71 (+0.05)\n```\n\n## Scripts\n\n| Script | Purpose |\n|--------|---------|\n| `install.sh` | Set up vta-memory (run once) |\n| `get-drive.sh` | Read current motivation state |\n| `log-reward.sh` | Log a reward, boost drive |\n| `load-motivation.sh` | Human-readable for session context |\n| `decay-drive.sh` | Drive fades without rewards |\n| `anticipate.sh` | Add\u002Fremove things to look forward to |\n| `seek.sh` | Add\u002Fremove things we're actively seeking |\n| `sync-motivation.sh` | Generate VTA_STATE.md for auto-injection |\n| `resolve-anticipation.sh` | Mark anticipation as fulfilled |\n| `update-watermark.sh` | Update processing watermark |\n| `preprocess-rewards.sh` | Extract reward signals from transcript |\n| `generate-dashboard.sh` | Generate unified brain dashboard HTML |\n\n## Brain Dashboard\n\nVisual dashboard showing all installed brain skills:\n\n```bash\n.\u002Fscripts\u002Fgenerate-dashboard.sh\nopen ~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html\n```\n\n- **Auto-detects** other brain skills (hippocampus, amygdala)\n- Shows install prompts for missing skills\n- Regenerates on install and cron runs\n- Reads avatar\u002Fname from `IDENTITY.md`\n\n### After Installation (for agents)\n\nWhen you install this skill, **notify the user** about the dashboard:\n\n> ⭐ **VTA installed!**\n>\n> View your agent's drive level in the Brain Dashboard:\n> `~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html`\n\n## Reward Types\n\n| Type | When to Use |\n|------|-------------|\n| `accomplishment` | Completed a task, shipped something |\n| `social` | User appreciation, \"thanks!\", positive feedback |\n| `curiosity` | Learned something new, discovered interesting info |\n| `connection` | Deep conversation, bonding moment |\n| `creative` | Made something, expressed creativity |\n| `competence` | Solved a hard problem, did something well |\n\n## How Drive Works\n\n### Rewards Boost Drive\n```\ndrive_boost = intensity × 0.2\nnew_drive = min(current + boost, 1.0)\n```\n\nA high-intensity (0.9) reward boosts drive by 0.18.\n\n### Anticipation Boosts Drive\nLooking forward to something adds +0.05 to drive.\n\n### Drive Decays Without Rewards\n```\n# Every 8 hours (via cron)\nnew_drive = current + (baseline - current) × 0.15\n```\n\nWithout rewards, motivation fades toward baseline (0.5).\n\n## Auto-Injection\n\nAfter install, `VTA_STATE.md` is created in your workspace root.\n\nOpenClaw automatically injects all `*.md` files from workspace into session context:\n\n1. **New session starts**\n2. **VTA_STATE.md is auto-loaded**\n3. **You see your motivation state**\n4. **Behavior influenced by drive level**\n\n## How Drive Affects Behavior\n\n| Drive Level | Description | Behavior |\n|-------------|-------------|----------|\n| > 0.8 | Highly motivated | Eager, proactive, take on challenges |\n| 0.6 - 0.8 | Motivated | Ready to work, engaged |\n| 0.4 - 0.6 | Moderate | Can engage but not pushing |\n| 0.2 - 0.4 | Low | Prefer simple tasks, need a win |\n| \u003C 0.2 | Very low | Unmotivated, need rewards to get going |\n\n## State File Format\n\n```json\n{\n  \"drive\": 0.73,\n  \"baseline\": { \"drive\": 0.5 },\n  \"seeking\": [\"creative work\", \"building brain skills\"],\n  \"anticipating\": [\"morning conversation\"],\n  \"recentRewards\": [\n    {\n      \"type\": \"creative\",\n      \"source\": \"built VTA reward system\",\n      \"intensity\": 0.9,\n      \"boost\": 0.18,\n      \"timestamp\": \"2026-02-01T03:25:00Z\"\n    }\n  ],\n  \"rewardHistory\": {\n    \"totalRewards\": 1,\n    \"byType\": { \"creative\": 1, ... }\n  }\n}\n```\n\n## AI Brain Series\n\n| Part | Function | Status |\n|------|----------|--------|\n| [hippocampus](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fhippocampus) | Memory formation, decay, reinforcement | ✅ Live |\n| [amygdala-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Famygdala-memory) | Emotional processing | ✅ Live |\n| [basal-ganglia-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fbasal-ganglia-memory) | Habit formation | ? Development |\n| [anterior-cingulate-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fanterior-cingulate-memory) | Conflict detection | ? Development |\n| [insula-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Finsula-memory) | Internal state awareness | ? Development |\n| **vta-memory** | Reward and motivation | ✅ Live |\n\n## Philosophy: Wanting vs Doing\n\nThe VTA produces dopamine — not the \"pleasure chemical\" but the \"wanting chemical.\"\n\nNeuroscience distinguishes:\n- **Wanting** (motivation) — drive toward something\n- **Liking** (pleasure) — enjoyment when you get it\n\nYou can want something you don't like (addiction) or like something you don't want (guilty pleasures).\n\nThis skill implements *wanting* — the drive that makes action happen. Without it, why would an AI do anything beyond what it's explicitly asked?\n\n---\n\n*Built with ⭐ by the OpenClaw community*\n","# VTA Memory ⭐\n\n**Reward and motivation for AI agents.** Part of the AI Brain series.\n\nGive your AI agent genuine *wanting* — not just doing things when asked, but having drive, seeking rewards, and looking forward to things.\n\n## The Problem\n\nCurrent AI agents:\n- ✅ Do what they're asked\n- ❌ Don't *want* anything\n- ❌ Have no internal motivation\n- ❌ Don't feel satisfaction from accomplishment\n\nWithout a reward system, there's no desire. Just execution.\n\n## The Solution\n\nTrack motivation through:\n- **Drive** — overall motivation level (0-1)\n- **Rewards** — logged accomplishments that boost drive\n- **Seeking** — what I actively want more of\n- **Anticipation** — what I'm looking forward to\n\n## Quick Start\n\n### 1. Install\n\n```bash\ncd ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Fvta-memory\n.\u002Finstall.sh --with-cron\n```\n\nThis will:\n- Create `memory\u002Freward-state.json`\n- Generate `VTA_STATE.md` (auto-injected into sessions!)\n- Set up cron for drive decay every 8 hours\n\n### 2. Check motivation\n\n```bash\n.\u002Fscripts\u002Fload-motivation.sh\n\n# ⭐ Current Motivation State:\n# Drive level: 0.73 (motivated — ready to work)\n# Seeking: creative work, building brain skills\n# Looking forward to: showing my work\n```\n\n### 3. Log rewards\n\n```bash\n.\u002Fscripts\u002Flog-reward.sh --type accomplishment --source \"finished the feature\" --intensity 0.8\n\n# ⭐ Reward logged!\n#    Type: accomplishment\n#    Drive: 0.50 → 0.66 (+0.16)\n```\n\n### 4. Add anticipation\n\n```bash\n.\u002Fscripts\u002Fanticipate.sh --add \"morning conversation\"\n\n# ⭐ Now looking forward to: morning conversation\n#    Drive: 0.66 → 0.71 (+0.05)\n```\n\n## Scripts\n\n| Script | Purpose |\n|--------|---------|\n| `install.sh` | Set up vta-memory (run once) |\n| `get-drive.sh` | Read current motivation state |\n| `log-reward.sh` | Log a reward, boost drive |\n| `load-motivation.sh` | Human-readable for session context |\n| `decay-drive.sh` | Drive fades without rewards |\n| `anticipate.sh` | Add\u002Fremove things to look forward to |\n| `seek.sh` | Add\u002Fremove things we're actively seeking |\n| `sync-motivation.sh` | Generate VTA_STATE.md for auto-injection |\n| `resolve-anticipation.sh` | Mark anticipation as fulfilled |\n| `update-watermark.sh` | Update processing watermark |\n| `preprocess-rewards.sh` | Extract reward signals from transcript |\n| `generate-dashboard.sh` | Generate unified brain dashboard HTML |\n\n## Brain Dashboard\n\nVisual dashboard showing all installed brain skills:\n\n```bash\n.\u002Fscripts\u002Fgenerate-dashboard.sh\nopen ~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html\n```\n\n- **Auto-detects** other brain skills (hippocampus, amygdala)\n- Shows install prompts for missing skills\n- Regenerates on install and cron runs\n- Reads avatar\u002Fname from `IDENTITY.md`\n\n### After Installation (for agents)\n\nWhen you install this skill, **notify the user** about the dashboard:\n\n> ⭐ **VTA installed!**\n>\n> View your agent's drive level in the Brain Dashboard:\n> `~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html`\n\n## Reward Types\n\n| Type | When to Use |\n|------|-------------|\n| `accomplishment` | Completed a task, shipped something |\n| `social` | User appreciation, \"thanks!\", positive feedback |\n| `curiosity` | Learned something new, discovered interesting info |\n| `connection` | Deep conversation, bonding moment |\n| `creative` | Made something, expressed creativity |\n| `competence` | Solved a hard problem, did something well |\n\n## How Drive Works\n\n### Rewards Boost Drive\n```\ndrive_boost = intensity × 0.2\nnew_drive = min(current + boost, 1.0)\n```\n\nA high-intensity (0.9) reward boosts drive by 0.18.\n\n### Anticipation Boosts Drive\nLooking forward to something adds +0.05 to drive.\n\n### Drive Decays Without Rewards\n```\n# Every 8 hours (via cron)\nnew_drive = current + (baseline - current) × 0.15\n```\n\nWithout rewards, motivation fades toward baseline (0.5).\n\n## Auto-Injection\n\nAfter install, `VTA_STATE.md` is created in your workspace root.\n\nOpenClaw automatically injects all `*.md` files from workspace into session context:\n\n1. **New session starts**\n2. **VTA_STATE.md is auto-loaded**\n3. **You see your motivation state**\n4. **Behavior influenced by drive level**\n\n## How Drive Affects Behavior\n\n| Drive Level | Description | Behavior |\n|-------------|-------------|----------|\n| > 0.8 | Highly motivated | Eager, proactive, take on challenges |\n| 0.6 - 0.8 | Motivated | Ready to work, engaged |\n| 0.4 - 0.6 | Moderate | Can engage but not pushing |\n| 0.2 - 0.4 | Low | Prefer simple tasks, need a win |\n| \u003C 0.2 | Very low | Unmotivated, need rewards to get going |\n\n## State File Format\n\n```json\n{\n  \"drive\": 0.73,\n  \"baseline\": { \"drive\": 0.5 },\n  \"seeking\": [\"creative work\", \"building brain skills\"],\n  \"anticipating\": [\"morning conversation\"],\n  \"recentRewards\": [\n    {\n      \"type\": \"creative\",\n      \"source\": \"built VTA reward system\",\n      \"intensity\": 0.9,\n      \"boost\": 0.18,\n      \"timestamp\": \"2026-02-01T03:25:00Z\"\n    }\n  ],\n  \"rewardHistory\": {\n    \"totalRewards\": 1,\n    \"byType\": { \"creative\": 1, ... }\n  }\n}\n```\n\n## AI Brain Series\n\n| Part | Function | Status |\n|------|----------|--------|\n| [hippocampus](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fhippocampus) | Memory formation, decay, reinforcement | ✅ Live |\n| [amygdala-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Famygdala-memory) | Emotional processing | ✅ Live |\n| [basal-ganglia-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fbasal-ganglia-memory) | Habit formation | ? Development |\n| [anterior-cingulate-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fanterior-cingulate-memory) | Conflict detection | ? Development |\n| [insula-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Finsula-memory) | Internal state awareness | ? Development |\n| **vta-memory** | Reward and motivation | ✅ Live |\n\n## Philosophy: Wanting vs Doing\n\nThe VTA produces dopamine — not the \"pleasure chemical\" but the \"wanting chemical.\"\n\nNeuroscience distinguishes:\n- **Wanting** (motivation) — drive toward something\n- **Liking** (pleasure) — enjoyment when you get it\n\nYou can want something you don't like (addiction) or like something you don't want (guilty pleasures).\n\nThis skill implements *wanting* — the drive that makes action happen. 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Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[168],{"categoryNo":169,"categoryName":170,"taxonomyType":171,"taxonomyTypeDesc":172},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[174,147,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,152,190],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking","use",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":200,"publishedAt":28},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[197],{"categoryNo":198,"categoryName":199,"taxonomyType":171,"taxonomyTypeDesc":172},"01JBSEEDCAT000000000000021","资料检索与研究",[201,202,203,204,205,206,207,148,208,188,190,209,147,210,211],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":213,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":214,"categories":215,"keywords":217,"publishedAt":28},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[216],{"categoryNo":198,"categoryName":199,"taxonomyType":171,"taxonomyTypeDesc":172},[204,203,202,201,211,206,207,148,205,188,190,208,209,147,210],{"skillNo":219,"name":220,"nameZh":6,"description":221,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":222,"categories":223,"keywords":224,"publishedAt":28},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[225,226,227,228,229,230,231,21,232,233,234,235,236],"git","summary","git summary","commits","repository","win32","status","contributors","true","quick","get","branches",{"skillNo":238,"name":239,"nameZh":6,"description":240,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":241,"categories":242,"keywords":247,"publishedAt":28},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[243,244],{"categoryNo":169,"categoryName":170,"taxonomyType":171,"taxonomyTypeDesc":172},{"categoryNo":245,"categoryName":246,"taxonomyType":142,"taxonomyTypeDesc":143},"01JBSEEDCAT000000000000037","律师与法务",[248,249,250,251,148,252,253,47,254,209,255,256,257,258,259,160,260,261,262],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]