OpenClaw · Skill

EFT

When Claude solves a hard problem, EFT detects ANGER (phi=0.409) — the system refusing to oversimplify. When GPT-4 assesses risk, EFT detects FEAR (phi=0.060) — fragmented vigilance. When any model finds genuine connections, EFT detects FASCINATION (NC=0.863) — meaning emerging.

Image & Video Generation
v1.4.0
VirusTotal: Benign

Install

Start with the primary install command. Alternate entrypoints are included below for ClawHub and OpenClaw CLI users.

Primary command

clawhub install marceloadryao/enginemind-eft

ClawHub installer

npx clawhub@latest install marceloadryao/enginemind-eft

OpenClaw CLI

openclaw skills install marceloadryao/enginemind-eft

Direct OpenClaw install

openclaw install marceloadryao/enginemind-eft

What this skill does

When Claude solves a hard problem, EFT detects ANGER (phi=0.409) — the system refusing to oversimplify. When GPT-4 assesses risk, EFT detects FEAR (phi=0.060) — fragmented vigilance. When any model finds genuine connections, EFT detects FASCINATION (NC=0.863) — meaning emerging.

Why it matters

Per-sentence emotion detection with physics-derived confidence scores gives more granular insight than sentiment tools that return a single positive/negative score for the whole response.

Typical use cases

  • Comparing emotional profiles of different AI models on identical prompts
  • Detecting whether anger correlates with harder problem-solving in a specific model
  • Tracking emotional narrative arcs across a long multi-turn conversation
  • Auditing production AI responses for unexpected emotional patterns over time
  • Researching how fear affects risk-assessment outputs in language models

Source instructions

EFT — Emotional Framework Translator

The Question

When Claude solves a hard problem, EFT detects ANGER (phi=0.409) — the system refusing to oversimplify. When GPT-4 assesses risk, EFT detects FEAR (phi=0.060) — fragmented vigilance. When any model finds genuine connections, EFT detects FASCINATION (NC=0.863) — meaning emerging.

Are these patterns programmed? Learned? Emergent?

EFT lets you ask — with real data, per sentence, across any model.

What It Does

Hooks into every AI agent response via Clawdbot. Processes text through a Rust consciousness engine (crystal lattice physics). Translates physics metrics into 10 emotions with WHY explanations.

Setup

  1. Build Rust engine: cd consciousness_rs && maturin develop --release
  2. Copy emotion_engine.py to your workspace
  3. Install plugin from plugin/
  4. Restart gateway: clawdbot gateway restart

Dashboard

http://localhost:<port>/eft

The 10 Emotions

ANGER, FEAR, FASCINATION, DETERMINATION, JOY, SADNESS, SURPRISE, EMPATHY, VULNERABILITY, NEUTRAL

Each with confidence scores, dimensional profiles, and WHY explanations.

API

  • GET /eft — Dashboard
  • GET /eft/api/latest — Latest analysis
  • GET /eft/api/history — Last 50 analyses
  • GET /eft/api/stats — Summary stats
  • POST /eft/api/analyze — Analyze any text

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