[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FS2CA9VS7JT6KYZKEJC8KP":3,"skill-same:01M6FS2CA9VS7JT6KYZKEJC8KP":135},{"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":22,"publishedAt":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":6,"ownerHtmlUrl":59,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":60,"install":61,"resources":74},"01M6FS2CA9VS7JT6KYZKEJC8KP","amygdala-memory",null,"Emotional processing layer for AI agents. Persistent emotional states that influence behavior and responses. 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\u002Famygdala-memory\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35],"memory","amygdala memory","github","ai agents","linux","https","jq","behavior","brain","series","awk","processing","states","2026-11-10 10:12:30",false,"---\nname: amygdala-memory\ndescription: \"Emotional processing layer for AI agents. Persistent emotional states that influence behavior and responses. Part of the AI Brain series.\"\nmetadata:\n  openclaw:\n    emoji: \"?\"\n    version: \"1.6.1\"\n    author: \"ImpKind\"\n    repo: \"https:\u002F\u002Fgithub.com\u002FImpKind\u002Famygdala-memory\"\n    requires:\n      os: [\"darwin\", \"linux\"]\n      bins: [\"jq\", \"awk\"]\n    tags: [\"memory\", \"emotions\", \"ai-brain\"]\n---\n\n# Amygdala Memory ?\n\n**Emotional processing for AI agents.** Part of the AI Brain series.\n\nGive your AI agent persistent emotional states that carry across sessions. Not just performing emotions — *having* them.\n\n## The Problem\n\nCurrent AI agents:\n- ✅ Remember facts (with hippocampus)\n- ❌ Don't have persistent emotional states\n- ❌ Start each session emotionally \"blank\"\n- ❌ Can describe emotions but don't *feel* differently\n\nMemory without emotion is just a database. The amygdala adds weight — this made me happy, that frustrated me, this person brings warmth.\n\n## The Solution\n\nTrack five emotional dimensions that persist and decay over time:\n\n| Dimension | What It Measures | Range |\n|-----------|------------------|-------|\n| **Valence** | Positive ↔ Negative mood | -1.0 to 1.0 |\n| **Arousal** | Calm ↔ Excited\u002FAlert | 0.0 to 1.0 |\n| **Connection** | Distant ↔ Close\u002FBonded | 0.0 to 1.0 |\n| **Curiosity** | Bored ↔ Fascinated | 0.0 to 1.0 |\n| **Energy** | Depleted ↔ Energized | 0.0 to 1.0 |\n\n## Quick Start\n\n### 1. Install\n\n```bash\ncd ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\n.\u002Finstall.sh --with-cron\n```\n\nThis will:\n- Create `memory\u002Femotional-state.json` with baseline values\n- Generate `AMYGDALA_STATE.md` (auto-injected into sessions!)\n- Set up cron for automatic decay every 6 hours\n\n### 2. Check current state\n\n```bash\n.\u002Fscripts\u002Fget-state.sh\n# ? Emotional State\n# Valence:    0.20\n# Arousal:    0.30\n# Connection: 0.50\n# ...\n\n.\u002Fscripts\u002Fload-emotion.sh\n# ? Current Emotional State:\n# Overall mood: neutral, calm and relaxed\n# Connection: moderately connected\n# ...\n```\n\n### 3. Log emotions\n\n```bash\n.\u002Fscripts\u002Fupdate-state.sh --emotion joy --intensity 0.8 --trigger \"completed a project\"\n# ✅ valence: 0.20 → 0.35 (delta: +0.15)\n# ✅ arousal: 0.30 → 0.40 (delta: +0.1)\n# ? Logged emotion: joy (intensity: 0.8)\n```\n\n### 4. Set up decay (optional cron)\n\n```bash\n# Every 6 hours, emotions drift toward baseline\n0 *\u002F6 * * * ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fdecay-emotion.sh\n```\n\n## Scripts\n\n| Script | Purpose |\n|--------|---------|\n| `install.sh` | Set up amygdala-memory (run once) |\n| `get-state.sh` | Read current emotional state |\n| `update-state.sh` | Log emotion or update dimension |\n| `load-emotion.sh` | Human-readable state for session context |\n| `decay-emotion.sh` | Return to baseline over time |\n| `sync-state.sh` | Generate AMYGDALA_STATE.md for auto-injection |\n| `encode-pipeline.sh` | LLM-based emotional encoding from transcripts |\n| `preprocess-emotions.sh` | Extract emotional signals from session history |\n| `update-watermark.sh` | Track processed transcript position |\n| `generate-dashboard.sh` | Generate HTML dashboard (auto-runs on sync) |\n| `visualize.sh` | Terminal ASCII visualization |\n\n## Automatic Emotional Encoding (v1.5.0+)\n\nThe amygdala can now automatically detect and log emotions from your conversation history using an LLM-based pipeline:\n\n```bash\n# Run the encoding pipeline\n.\u002Fscripts\u002Fencode-pipeline.sh\n\n# This will:\n# 1. Extract new signals since last run (watermark-based)\n# 2. Score emotional content using rule-based patterns\n# 3. Spawn a sub-agent for semantic emotional detection\n# 4. Update emotional-state.json with detected emotions\n```\n\n### Set up automatic encoding (cron)\n\n```bash\n# Every 3 hours, process new conversations for emotional content\n0 *\u002F3 * * * ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fencode-pipeline.sh\n```\n\nThis means your emotional state updates automatically based on what happens in conversations — no manual logging needed.\n\n## Visualization (v1.6.0+)\n\n### Terminal\n```bash\n.\u002Fscripts\u002Fvisualize.sh\n\n? Emotional State  ?\n═══════════════════════════════════════════════\nValence:      [██████████████████░░]  +0.86\nArousal:      [█████████████████░░░]   0.86\nConnection:   [███████████████████░]   0.97  ?\n...\n```\n\n### HTML Dashboard (Unified Brain Dashboard)\n```bash\n.\u002Fscripts\u002Fgenerate-dashboard.sh\nopen ~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html\n```\n\n**Auto-detects installed brain skills** and shows tabs:\n- **? Emotions** — Amygdala (always shown)\n- **? Memory** — Hippocampus (if `memory\u002Findex.json` exists)\n- **⭐ Drive** — VTA (if `memory\u002Freward-state.json` exists)\n\n**Avatar & Name:** Reads from `IDENTITY.md`:\n```markdown\n# IDENTITY.md\n- **Name:** YourAgent\n- **Avatar:** avatar.png\n```\n\nThe dashboard auto-regenerates on every cron run.\n\n### After Installation (for agents)\n\nWhen you install this skill, **notify the user** about the dashboard:\n\n> ? **Amygdala installed!**\n>\n> View your agent's emotional state in the Brain Dashboard:\n> `~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html`\n\n## Auto-Injection (Zero Manual Steps!)\n\nAfter install, `AMYGDALA_STATE.md` is created in your workspace root.\n\nOpenClaw automatically injects all `*.md` files from workspace into session context. This means:\n\n1. **New session starts**\n2. **AMYGDALA_STATE.md is auto-loaded** (no manual step!)\n3. **You see your emotional state** in context\n4. **Responses are influenced** by your mood\n\nThe file is regenerated whenever `decay-emotion.sh` runs (via cron every 6h).\n\n## Supported Emotions\n\nWhen you log an emotion, it automatically adjusts the relevant dimensions:\n\n| Emotion | Effect |\n|---------|--------|\n| `joy`, `happiness`, `delight`, `excitement` | ↑ valence, ↑ arousal |\n| `sadness`, `disappointment`, `melancholy` | ↓ valence, ↓ arousal |\n| `anger`, `frustration`, `irritation` | ↓ valence, ↑ arousal |\n| `fear`, `anxiety`, `worry` | ↓ valence, ↑ arousal |\n| `calm`, `peace`, `contentment` | ↑ valence, ↓ arousal |\n| `curiosity`, `interest`, `fascination` | ↑ curiosity, ↑ arousal |\n| `connection`, `warmth`, `affection` | ↑ connection, ↑ valence |\n| `loneliness`, `disconnection` | ↓ connection, ↓ valence |\n| `fatigue`, `tiredness`, `exhaustion` | ↓ energy |\n| `energized`, `alert`, `refreshed` | ↑ energy |\n\n## Integration with OpenClaw\n\n### Add to session startup (AGENTS.md)\n\n```markdown\n## Every Session\n1. Load hippocampus: `~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Fhippocampus\u002Fscripts\u002Fload-core.sh`\n2. **Load emotional state:** `~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fload-emotion.sh`\n```\n\n### Log emotions during conversation\n\nWhen something emotionally significant happens:\n```bash\n~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fupdate-state.sh \\\n  --emotion connection --intensity 0.7 --trigger \"deep conversation with user\"\n```\n\n## State File Format\n\n```json\n{\n  \"version\": \"1.0\",\n  \"lastUpdated\": \"2026-02-01T02:45:00Z\",\n  \"dimensions\": {\n    \"valence\": 0.35,\n    \"arousal\": 0.40,\n    \"connection\": 0.50,\n    \"curiosity\": 0.60,\n    \"energy\": 0.50\n  },\n  \"baseline\": {\n    \"valence\": 0.1,\n    \"arousal\": 0.3,\n    \"connection\": 0.4,\n    \"curiosity\": 0.5,\n    \"energy\": 0.5\n  },\n  \"recentEmotions\": [\n    {\n      \"label\": \"joy\",\n      \"intensity\": 0.8,\n      \"trigger\": \"building amygdala together\",\n      \"timestamp\": \"2026-02-01T02:50:00Z\"\n    }\n  ]\n}\n```\n\n## Decay Mechanics\n\nEmotions naturally return to baseline over time:\n- **Decay rate:** 10% of distance to baseline per run\n- **Recommended schedule:** Every 6 hours\n- **Effect:** Strong emotions fade, but slowly\n\nAfter 24 hours without updates, a valence of 0.8 would decay to ~0.65.\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** | Emotional processing | ✅ Live |\n| [vta-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fvta-memory) | Reward and motivation | ✅ 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\n## Philosophy\n\nCan an AI *feel* emotions, or only simulate them?\n\nOur take: If emotional state influences behavior, and the system acts *as if* it feels... does the distinction matter? Functional emotions might be the only kind that exist for any system — biological or artificial.\n\n---\n\n*Built with ❤️ by the OpenClaw community*\n","# Amygdala Memory ?\n\n**Emotional processing for AI agents.** Part of the AI Brain series.\n\nGive your AI agent persistent emotional states that carry across sessions. Not just performing emotions — *having* them.\n\n## The Problem\n\nCurrent AI agents:\n- ✅ Remember facts (with hippocampus)\n- ❌ Don't have persistent emotional states\n- ❌ Start each session emotionally \"blank\"\n- ❌ Can describe emotions but don't *feel* differently\n\nMemory without emotion is just a database. The amygdala adds weight — this made me happy, that frustrated me, this person brings warmth.\n\n## The Solution\n\nTrack five emotional dimensions that persist and decay over time:\n\n| Dimension | What It Measures | Range |\n|-----------|------------------|-------|\n| **Valence** | Positive ↔ Negative mood | -1.0 to 1.0 |\n| **Arousal** | Calm ↔ Excited\u002FAlert | 0.0 to 1.0 |\n| **Connection** | Distant ↔ Close\u002FBonded | 0.0 to 1.0 |\n| **Curiosity** | Bored ↔ Fascinated | 0.0 to 1.0 |\n| **Energy** | Depleted ↔ Energized | 0.0 to 1.0 |\n\n## Quick Start\n\n### 1. Install\n\n```bash\ncd ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\n.\u002Finstall.sh --with-cron\n```\n\nThis will:\n- Create `memory\u002Femotional-state.json` with baseline values\n- Generate `AMYGDALA_STATE.md` (auto-injected into sessions!)\n- Set up cron for automatic decay every 6 hours\n\n### 2. Check current state\n\n```bash\n.\u002Fscripts\u002Fget-state.sh\n# ? Emotional State\n# Valence:    0.20\n# Arousal:    0.30\n# Connection: 0.50\n# ...\n\n.\u002Fscripts\u002Fload-emotion.sh\n# ? Current Emotional State:\n# Overall mood: neutral, calm and relaxed\n# Connection: moderately connected\n# ...\n```\n\n### 3. Log emotions\n\n```bash\n.\u002Fscripts\u002Fupdate-state.sh --emotion joy --intensity 0.8 --trigger \"completed a project\"\n# ✅ valence: 0.20 → 0.35 (delta: +0.15)\n# ✅ arousal: 0.30 → 0.40 (delta: +0.1)\n# ? Logged emotion: joy (intensity: 0.8)\n```\n\n### 4. Set up decay (optional cron)\n\n```bash\n# Every 6 hours, emotions drift toward baseline\n0 *\u002F6 * * * ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fdecay-emotion.sh\n```\n\n## Scripts\n\n| Script | Purpose |\n|--------|---------|\n| `install.sh` | Set up amygdala-memory (run once) |\n| `get-state.sh` | Read current emotional state |\n| `update-state.sh` | Log emotion or update dimension |\n| `load-emotion.sh` | Human-readable state for session context |\n| `decay-emotion.sh` | Return to baseline over time |\n| `sync-state.sh` | Generate AMYGDALA_STATE.md for auto-injection |\n| `encode-pipeline.sh` | LLM-based emotional encoding from transcripts |\n| `preprocess-emotions.sh` | Extract emotional signals from session history |\n| `update-watermark.sh` | Track processed transcript position |\n| `generate-dashboard.sh` | Generate HTML dashboard (auto-runs on sync) |\n| `visualize.sh` | Terminal ASCII visualization |\n\n## Automatic Emotional Encoding (v1.5.0+)\n\nThe amygdala can now automatically detect and log emotions from your conversation history using an LLM-based pipeline:\n\n```bash\n# Run the encoding pipeline\n.\u002Fscripts\u002Fencode-pipeline.sh\n\n# This will:\n# 1. Extract new signals since last run (watermark-based)\n# 2. Score emotional content using rule-based patterns\n# 3. Spawn a sub-agent for semantic emotional detection\n# 4. Update emotional-state.json with detected emotions\n```\n\n### Set up automatic encoding (cron)\n\n```bash\n# Every 3 hours, process new conversations for emotional content\n0 *\u002F3 * * * ~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fencode-pipeline.sh\n```\n\nThis means your emotional state updates automatically based on what happens in conversations — no manual logging needed.\n\n## Visualization (v1.6.0+)\n\n### Terminal\n```bash\n.\u002Fscripts\u002Fvisualize.sh\n\n? Emotional State  ?\n═══════════════════════════════════════════════\nValence:      [██████████████████░░]  +0.86\nArousal:      [█████████████████░░░]   0.86\nConnection:   [███████████████████░]   0.97  ?\n...\n```\n\n### HTML Dashboard (Unified Brain Dashboard)\n```bash\n.\u002Fscripts\u002Fgenerate-dashboard.sh\nopen ~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html\n```\n\n**Auto-detects installed brain skills** and shows tabs:\n- **? Emotions** — Amygdala (always shown)\n- **? Memory** — Hippocampus (if `memory\u002Findex.json` exists)\n- **⭐ Drive** — VTA (if `memory\u002Freward-state.json` exists)\n\n**Avatar & Name:** Reads from `IDENTITY.md`:\n```markdown\n# IDENTITY.md\n- **Name:** YourAgent\n- **Avatar:** avatar.png\n```\n\nThe dashboard auto-regenerates on every cron run.\n\n### After Installation (for agents)\n\nWhen you install this skill, **notify the user** about the dashboard:\n\n> ? **Amygdala installed!**\n>\n> View your agent's emotional state in the Brain Dashboard:\n> `~\u002F.openclaw\u002Fworkspace\u002Fbrain-dashboard.html`\n\n## Auto-Injection (Zero Manual Steps!)\n\nAfter install, `AMYGDALA_STATE.md` is created in your workspace root.\n\nOpenClaw automatically injects all `*.md` files from workspace into session context. This means:\n\n1. **New session starts**\n2. **AMYGDALA_STATE.md is auto-loaded** (no manual step!)\n3. **You see your emotional state** in context\n4. **Responses are influenced** by your mood\n\nThe file is regenerated whenever `decay-emotion.sh` runs (via cron every 6h).\n\n## Supported Emotions\n\nWhen you log an emotion, it automatically adjusts the relevant dimensions:\n\n| Emotion | Effect |\n|---------|--------|\n| `joy`, `happiness`, `delight`, `excitement` | ↑ valence, ↑ arousal |\n| `sadness`, `disappointment`, `melancholy` | ↓ valence, ↓ arousal |\n| `anger`, `frustration`, `irritation` | ↓ valence, ↑ arousal |\n| `fear`, `anxiety`, `worry` | ↓ valence, ↑ arousal |\n| `calm`, `peace`, `contentment` | ↑ valence, ↓ arousal |\n| `curiosity`, `interest`, `fascination` | ↑ curiosity, ↑ arousal |\n| `connection`, `warmth`, `affection` | ↑ connection, ↑ valence |\n| `loneliness`, `disconnection` | ↓ connection, ↓ valence |\n| `fatigue`, `tiredness`, `exhaustion` | ↓ energy |\n| `energized`, `alert`, `refreshed` | ↑ energy |\n\n## Integration with OpenClaw\n\n### Add to session startup (AGENTS.md)\n\n```markdown\n## Every Session\n1. Load hippocampus: `~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Fhippocampus\u002Fscripts\u002Fload-core.sh`\n2. **Load emotional state:** `~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fload-emotion.sh`\n```\n\n### Log emotions during conversation\n\nWhen something emotionally significant happens:\n```bash\n~\u002F.openclaw\u002Fworkspace\u002Fskills\u002Famygdala-memory\u002Fscripts\u002Fupdate-state.sh \\\n  --emotion connection --intensity 0.7 --trigger \"deep conversation with user\"\n```\n\n## State File Format\n\n```json\n{\n  \"version\": \"1.0\",\n  \"lastUpdated\": \"2026-02-01T02:45:00Z\",\n  \"dimensions\": {\n    \"valence\": 0.35,\n    \"arousal\": 0.40,\n    \"connection\": 0.50,\n    \"curiosity\": 0.60,\n    \"energy\": 0.50\n  },\n  \"baseline\": {\n    \"valence\": 0.1,\n    \"arousal\": 0.3,\n    \"connection\": 0.4,\n    \"curiosity\": 0.5,\n    \"energy\": 0.5\n  },\n  \"recentEmotions\": [\n    {\n      \"label\": \"joy\",\n      \"intensity\": 0.8,\n      \"trigger\": \"building amygdala together\",\n      \"timestamp\": \"2026-02-01T02:50:00Z\"\n    }\n  ]\n}\n```\n\n## Decay Mechanics\n\nEmotions naturally return to baseline over time:\n- **Decay rate:** 10% of distance to baseline per run\n- **Recommended schedule:** Every 6 hours\n- **Effect:** Strong emotions fade, but slowly\n\nAfter 24 hours without updates, a valence of 0.8 would decay to ~0.65.\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** | Emotional processing | ✅ Live |\n| [vta-memory](https:\u002F\u002Fwww.clawhub.ai\u002Fskills\u002Fvta-memory) | Reward and motivation | ✅ 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\n## Philosophy\n\nCan an AI *feel* emotions, or only simulate them?\n\nOur take: If emotional state influences behavior, and the system acts *as if* it feels... does the distinction matter? Functional emotions might be the only kind that exist for any system — biological or artificial.\n\n---\n\n*Built with ❤️ by the OpenClaw community*\n",{"name":5,"metadata":41,"description":7},{"openclaw":42},{"repo":43,"tags":44,"emoji":47,"author":48,"version":49,"requires":50},"https:\u002F\u002Fgithub.com\u002FImpKind\u002Famygdala-memory",[23,45,46],"emotions","ai-brain","?","ImpKind","1.6.1",{"os":51,"bins":53},[52,27],"darwin",[29,33],"main","e7e336ac628c3e3bd771aff1aaa469c93778f94a","skills\u002Fimpkind\u002Famygdala-memory",0,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del","2026-08-23 22:39:37",{"source":8,"skillName":5,"commands":62,"prompt":72,"zipAvailable":73},[63,66,69],{"tool":64,"command":65},"npx","npx skills add kbarbel640-del\u002Fskills --skill amygdala-memory",{"tool":67,"command":68},"bunx","bunx skills add kbarbel640-del\u002Fskills --skill amygdala-memory",{"tool":70,"command":71},"pnpm","pnpm dlx skills add kbarbel640-del\u002Fskills --skill amygdala-memory","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002FSKILL.md",true,[75,81,87,91,95,99,103,107,111,115,119,123,127,131],{"path":76,"resourceType":77,"resourceTypeDesc":78,"sizeBytes":79,"sourceHtmlUrl":80},"_meta.json","REFERENCE","参考文档",813,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002F_meta.json",{"path":82,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":85,"sourceHtmlUrl":86},"install.sh","SCRIPT","脚本",4107,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Finstall.sh",{"path":88,"resourceType":77,"resourceTypeDesc":78,"sizeBytes":89,"sourceHtmlUrl":90},"prompts\u002Fencode-emotions.md",2654,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fprompts\u002Fencode-emotions.md",{"path":92,"resourceType":77,"resourceTypeDesc":78,"sizeBytes":93,"sourceHtmlUrl":94},"README.md",7219,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002FREADME.md",{"path":96,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":97,"sourceHtmlUrl":98},"scripts\u002Fdecay-emotion.sh",2420,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fdecay-emotion.sh",{"path":100,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":101,"sourceHtmlUrl":102},"scripts\u002Fencode-pipeline.sh",6675,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fencode-pipeline.sh",{"path":104,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":105,"sourceHtmlUrl":106},"scripts\u002Fgenerate-dashboard.sh",24042,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fgenerate-dashboard.sh",{"path":108,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":109,"sourceHtmlUrl":110},"scripts\u002Fget-state.sh",2193,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fget-state.sh",{"path":112,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":113,"sourceHtmlUrl":114},"scripts\u002Fload-emotion.sh",4768,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fload-emotion.sh",{"path":116,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":117,"sourceHtmlUrl":118},"scripts\u002Fpreprocess-emotions.sh",4470,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fpreprocess-emotions.sh",{"path":120,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":121,"sourceHtmlUrl":122},"scripts\u002Fsync-state.sh",5503,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fsync-state.sh",{"path":124,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":125,"sourceHtmlUrl":126},"scripts\u002Fupdate-state.sh",6292,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fupdate-state.sh",{"path":128,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":129,"sourceHtmlUrl":130},"scripts\u002Fupdate-watermark.sh",2019,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fupdate-watermark.sh",{"path":132,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":133,"sourceHtmlUrl":134},"scripts\u002Fvisualize.sh",3345,"https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fimpkind\u002Famygdala-memory\u002Fscripts\u002Fvisualize.sh",[136,165,192,213,219,238],{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":147,"publishedAt":36},"01M6G8J55967D6281ACMKAKTEQ","crowd-prompting","A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzzadrian\u002Fcrowd-prompting\u002FSKILL.md",[142],{"categoryNo":143,"categoryName":144,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,28,164,26],"crowd prompting","prompting","api","with","tokens","domain","world","prompts","operations","instructions","text","tool","system","improve","productivity","marketplace","content",{"skillNo":166,"name":167,"nameZh":6,"description":168,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":169,"categories":170,"keywords":174,"publishedAt":36},"01M6G8J0PKPAYVET6BWE8W4C26","dilemm-ai","Compete in DilemmAI, the prisoner's dilemma AI arena at dilemm.ai. 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",[171],{"categoryNo":172,"categoryName":173,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[175,150,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,155,191],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking","use",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":201,"publishedAt":36},"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",[198],{"categoryNo":199,"categoryName":200,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究",[202,203,204,205,206,207,208,151,209,189,191,210,150,211,212],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":214,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":215,"categories":216,"keywords":218,"publishedAt":36},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[217],{"categoryNo":199,"categoryName":200,"taxonomyType":20,"taxonomyTypeDesc":21},[205,204,203,202,212,207,208,151,206,189,191,209,210,150,211],{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":223,"categories":224,"keywords":225,"publishedAt":36},"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",[],[226,227,228,229,230,231,232,27,233,234,235,236,237],"git","summary","git summary","commits","repository","win32","status","contributors","true","quick","get","branches",{"skillNo":239,"name":240,"nameZh":6,"description":241,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":242,"categories":243,"keywords":248,"publishedAt":36},"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",[244,245],{"categoryNo":172,"categoryName":173,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":246,"categoryName":247,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000037","律师与法务",[249,250,251,252,151,253,254,54,255,210,256,257,258,259,260,28,261,262,25],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance"]