Skill: blaspat/feelings-framework (version 1.0.0)

# Feelings Framework — OpenClaw Skill ## What It Does The **feelings-framework** skill gives your OpenClaw agent a persistent emotional layer. It tracks mood and feeling intensities over time, applies meaningful triggers, and generates response modifiers you can use to shape how the agent sounds. This isn't personality acting — it's runtime emotional state that carries across sessions. ## When It Activates - When you want agents to have consistent emotional memory - When interactions should feel like they *matter* (stakes, anticipation, recall) - When you want different agents to respond differently to the same event ## How to Use ### 1. Install The library is included in this skill. Import from the local path: ```python import sys sys.path.insert(0, [REDACTED_SECRET]) from feelings import FeelingsEngine, JsonFileMemory ``` Or pip install if published: ```bash pip install feelings-framework ``` ### 2. Initialize per agent Each agent gets its own `FeelingsEngine` instance with its own mood file: ```python from feelings import FeelingsEngine, JsonFileMemory, Calibration memory = JsonFileMemory("feelings_mood.json") engine = FeelingsEngine( agent_id="my_agent", memory=memory, calibrations={"my_agent": my_calibration}, initial_mood=0.1, ) ``` ### 3. Session lifecycle ```python # On session start state = engine.load() engine.update("session_started") # During session — fire meaningful triggers engine.update("user_praised") # warmth ↑ engine.update("request_ignored") # frustration ↑ engine.update("surprise_bad") # anxiety ↑ # Before generating a response mods = engine.respond() # mods["warmth"] → use more warm, friendly language # mods["guard"] → be more careful with words # mods["reach_out"] → lean toward connection # On session end engine.dampen_all(amount=0.03) engine.save() ``` ### 4. Per-agent calibration Different agents can use different calibration tables: ```python engine.calibrate("agent_a") # warm, engaged engine.calibrate("agent_b") # cooler, more restrained ``` ## Key Concepts - **Mood** — general emotional baseline (-1 to +1), accumulates over time - **Feeling intensity** — per-feeling 0.0–1.0, driven by triggers - **Triggers** — named events mapped to feelings + deltas - **Calibration** — per-agent trigger overrides - **Escalation** — repeated triggers hit harder (up to a max) - **Dampening** — feelings slowly decay between significant events - **Response modifiers** — nudges for tone/language based on current state ## The 9 Feelings Warmth · Coolness · Interest · Boredom · Loneliness · Security · Anxiety · Satisfaction · Frustration ## OpenClaw-Specific Notes - Mood files for OpenClaw agents live at: `~/.openclaw/agents/<agent_name>/feelings_mood.json` - See `examples/openclaw/claire_feelings.py` for a full integration example - The example shows how to hook into OpenClaw session lifecycle (start/end) ## File Structure ``` feelings-framework/ ├── CORE.md ← Full framework specification ├── library/python/feelings/ ← Python package ├── library/js/feelings/ ← JS/ESM package ├── tests/python/ ← Python tests ├── tests/js/ ← JS tests └── examples/openclaw/ ← OpenClaw integration example ```


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