Skill: impkind/amygdala-memory (version 1.7.0)

--- name: amygdala-memory description: "Emotional processing layer for AI agents. Persistent emotional states that influence behavior and responses. Part of the AI Brain series." metadata: openclaw: emoji: "🎭" version: "1.7.0" author: "ImpKind" repo: "https://github.com/ImpKind/amygdala-memory" requires: os: ["darwin", "linux"] bins: ["jq", "awk"] tags: ["memory", "emotions", "ai-brain"] --- # Amygdala Memory 🎭 **Emotional processing for AI agents.** Part of the AI Brain series. Give your AI agent persistent emotional states that carry across sessions. Not just performing emotions — *having* them. ## The Problem Current AI agents: - ✅ Remember facts (with hippocampus) - ❌ Don't have persistent emotional states - ❌ Start each session emotionally "blank" - ❌ Can describe emotions but don't *feel* differently Memory without emotion is just a database. The amygdala adds weight — this made me happy, that frustrated me, this person brings warmth. ## The Solution Track five emotional dimensions that persist and decay over time: | Dimension | What It Measures | Range | |-----------|------------------|-------| | **Valence** | Positive ↔ Negative mood | -1.0 to 1.0 | | **Arousal** | Calm ↔ Excited/Alert | 0.0 to 1.0 | | **Connection** | Distant ↔ Close/Bonded | 0.0 to 1.0 | | **Curiosity** | Bored ↔ Fascinated | 0.0 to 1.0 | | **Energy** | Depleted ↔ Energized | 0.0 to 1.0 | ## Quick Start ### 1. Install ```bash cd ~/.openclaw/workspace/skills/amygdala-memory ./install.sh --with-cron ``` This will: - Create `memory/emotional-state.json` with baseline values - Generate `AMYGDALA_STATE.md` (auto-injected into sessions!) - Set up cron for automatic decay every 6 hours ### 2. Check current state ```bash ./scripts/get-state.sh # 🎭 Emotional State # Valence: 0.20 # Arousal: 0.30 # Connection: 0.50 # ... ./scripts/load-emotion.sh # 🎭 Current Emotional State: # Overall mood: neutral, calm and relaxed # Connection: moderately connected # ... ``` ### 3. Log emotions ```bash ./scripts/update-state.sh --emotion joy --intensity 0.8 --trigger "completed a project" # ✅ valence: 0.20 → 0.35 (delta: +0.15) # ✅ arousal: 0.30 → 0.40 (delta: +0.1) # 🎭 Logged emotion: joy (intensity: 0.8) ``` ### 4. Set up decay (optional cron) ```bash # Every 6 hours, emotions drift toward baseline 0 */6 * * * ~/.openclaw/workspace/skills/amygdala-memory/scripts/decay-emotion.sh ``` ## Scripts | Script | Purpose | |--------|---------| | `install.sh` | Set up amygdala-memory (run once) | | `get-state.sh` | Read current emotional state | | `update-state.sh` | Log emotion or update dimension | | `load-emotion.sh` | Human-readable state for session context | | `decay-emotion.sh` | Return to baseline over time | | `sync-state.sh` | Generate AMYGDALA_STATE.md for auto-injection | | `encode-pipeline.sh` | LLM-based emotional encoding from transcripts | | `preprocess-emotions.sh` | Extract emotional signals from session history | | `update-watermark.sh` | Track processed transcript position | | `generate-dashboard.sh` | Generate HTML dashboard (auto-runs on sync) | | `visualize.sh` | Terminal ASCII visualization | ## Automatic Emotional Encoding (v1.5.0+) The amygdala can now automatically detect and log emotions from your conversation history using an LLM-based pipeline: ```bash # Run the encoding pipeline ./scripts/encode-pipeline.sh # This will: # 1. Extract new signals since last run (watermark-based) # 2. Score emotional content using rule-based patterns # 3. Spawn a sub-agent for semantic emotional detection # 4. Update emotional-state.json with detected emotions ``` ### Set up automatic encoding (cron) ```bash # Every 3 hours, process new conversations for emotional content 0 */3 * * * ~/.openclaw/workspace/skills/amygdala-memory/scripts/encode-pipeline.sh ``` This means your emotional state updates automatically based on what happens in conversations — no manual logging needed. ## Visualization (v1.6.0+) ### Terminal ```bash ./scripts/visualize.sh 🎭 Emotional State 😄 ═══════════════════════════════════════════════ Valence: [██████████████████░░] +0.86 Arousal: [█████████████████░░░] 0.86 Connection: [███████████████████░] 0.97 💕 ... ``` ### HTML Dashboard (Unified Brain Dashboard) ```bash ./scripts/generate-dashboard.sh open ~/.openclaw/workspace/brain-dashboard.html ``` **Auto-detects installed brain skills** and shows tabs: - **🎭 Emotions** — Amygdala (always shown) - **🧠 Memory** — Hippocampus (if `memory/index.json` exists) - **⭐ Drive** — VTA (if `memory/reward-state.json` exists) **Avatar & Name:** Reads from `IDENTITY.md`: ```markdown # IDENTITY.md - **Name:** YourAgent - **Avatar:** avatar.png ``` The dashboard auto-regenerates on every cron run. ### After Installation (for agents) When you install this skill, **notify the user** about the dashboard: > 🎭 **Amygdala installed!** > > View your agent's emotional state in the Brain Dashboard: > `~/.openclaw/workspace/brain-dashboard.html` ## Auto-Injection (Zero Manual Steps!) After install, `AMYGDALA_STATE.md` is created in your workspace root. OpenClaw automatically injects all `*.md` files from workspace into session context. This means: 1. **New session starts** 2. **AMYGDALA_STATE.md is auto-loaded** (no manual step!) 3. **You see your emotional state** in context 4. **Responses are influenced** by your mood The file is regenerated whenever `decay-emotion.sh` runs (via cron every 6h). ## Supported Emotions When you log an emotion, it automatically adjusts the relevant dimensions: | Emotion | Effect | |---------|--------| | `joy`, `happiness`, `delight`, `excitement` | ↑ valence, ↑ arousal | | `sadness`, `disappointment`, `melancholy` | ↓ valence, ↓ arousal | | `anger`, `frustration`, `irritation` | ↓ valence, ↑ arousal | | `fear`, `anxiety`, `worry` | ↓ valence, ↑ arousal | | `calm`, `peace`, `contentment` | ↑ valence, ↓ arousal | | `curiosity`, `interest`, `fascination` | ↑ curiosity, ↑ arousal | | `connection`, `warmth`, `affection` | ↑ connection, ↑ valence | | `loneliness`, `disconnection` | ↓ connection, ↓ valence | | `fatigue`, `tiredness`, `exhaustion` | ↓ energy | | `energized`, `alert`, `refreshed` | ↑ energy | ## Integration with OpenClaw ### Add to session startup (AGENTS.md) ```markdown ## Every Session 1. Load hippocampus: `~/.openclaw/workspace/skills/hippocampus/scripts/load-core.sh` 2. **Load emotional state:** `~/.openclaw/workspace/skills/amygdala-memory/scripts/load-emotion.sh` ``` ### Log emotions during conversation When something emotionally significant happens: ```bash ~/.openclaw/workspace/skills/amygdala-memory/scripts/update-state.sh \ --emotion connection --intensity 0.7 --trigger "deep conversation with user" ``` ## State File Format ```json { "version": "1.0", "lastUpdated": "2026-02-01T02:45:00Z", "dimensions": { "valence": 0.35, "arousal": 0.40, "connection": 0.50, "curiosity": 0.60, "energy": 0.50 }, "baseline": { "valence": 0.1, "arousal": 0.3, "connection": 0.4, "curiosity": 0.5, "energy": 0.5 }, "recentEmotions": [ { "label": "joy", "intensity": 0.8, "trigger": "building amygdala together", "timestamp": "2026-02-01T02:50:00Z" } ] } ``` ## Decay Mechanics Emotions naturally return to baseline over time: - **Decay rate:** 10% of distance to baseline per run - **Recommended schedule:** Every 6 hours - **Effect:** Strong emotions fade, but slowly After 24 hours without updates, a valence of 0.8 would decay to ~0.65. ## Event Logging Track emotional activity over time for analytics: ```bash # Log encoding run ./scripts/log-event.sh encoding emotions_found=2 valence=0.85 arousal=0.6 # Log decay ./scripts/log-event.sh decay valence_before=0.9 valence_after=0.85 # Log emotion update ./scripts/log-event.sh update emotion=joy intensity=0.7 ``` Events append to `~/.openclaw/workspace/memory/brain-events.jsonl`: ```json {"ts":"2026-02-11T09:30:00Z","type":"amygdala","event":"encoding","emotions_found":2,"valence":0.85} ``` Use for trend analysis — visualize emotional patterns over days/weeks. ## AI Brain Series | Part | Function | Status | |------|----------|--------| | [hippocampus](https://www.clawhub.ai/skills/hippocampus) | Memory formation, decay, reinforcement | ✅ Live | | **amygdala-memory** | Emotional processing | ✅ Live | | [vta-memory](https://www.clawhub.ai/skills/vta-memory) | Reward and motivation | ✅ 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 | ## Philosophy Can an AI *feel* emotions, or only simulate them? Our 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. --- *Built with ❤️ by the OpenClaw community*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)