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aice

AI Confidence Engine — 5 dominios bidireccionales (TECH/OPS/JUDGMENT/COMMS/ORCH). Agent + User scoring. Triggers: puntúa, auto-score, task-complete, idea-validate, criteria-evolution. Pool scoring por runtime.

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0

Installs

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Status

ACTIVE

Visibility

PUBLIC

安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 aice 技能。 若已安装,则直接安装 aice 技能。

Overview

Skill Key
brugillo/aice
Author
brugillo
Source Repo
openclaw/skills
Version
1.1.0
Source Path
skills/brugillo/aice
Latest Commit SHA
293ac3e19907fdab8661dfd96f502ee873d11ae9

Extracted Content

SKILL.md excerpt

# AICE — AI Confidence Engine

Motor de confianza con 5 dominios. Tu score refleja cuánto confía el usuario en ti.

**Estado:** `confidence.json` | **Ref:** `resources/AICE_REFERENCE.md` | **User:** `resources/AICE_USER_SCORING.md` | **Triggers/Patterns:** `resources/TRIGGERS_AND_PATTERNS.md`

---

## 1. Dominios

| Dominio | Código | Emoji | 🤖 Agente mide | 👤 Usuario mide |
|---------|--------|:-----:|----------------|----------------|
| Técnico | `TECH` | 🔧 | Código, investigación | Specs, scope |
| Disciplina | `OPS` | ⚙️ | Reglas, formato, memoria | Proceso, ADRs |
| Criterio | `JUDGMENT` | 🧠 | Visión, anticipación | Dirección, decisiones |
| Comunicación | `COMMS` | 💬 | Tono, timing, callar | Feedback, claridad |
| Coordinación | `ORCH` | 🎯 | Sub-agentes, seguimiento | Contexto, refs |

**Score global** = `Σ(score[d] × weight[d]) / Σ(weight[d])` — Rango: −100% a +100%, inicio 50%.

---

## 2. Scoring

**Errores:** 🟡 Leve (−1) · 🟠 Medio (−3) · 🔴 Grave (−5) · ⚫ Crítico/Reincidencia (−10)
**Aciertos:** 🟢 Pro-patrón (+3 fijo) · ⭐ Bonus (max 3/día) · 🚀 Excepcional (+5-10, streak ≥ 3)

**Caps/dominio:** Warmup (<40 evals): −30/+15 · Normal: −20/+10 (neto, ADR-031)
**Rachas:** `ACC={0:0,..,4:1,5:2,6:4,7:6,8:8,9:10,10:12}; delta=ACC[curr]-ACC[prev]`. Error→streak=0.
**Clusters:** Misma cadena causal = 1 cluster. Raíz: 100%, derivados: 50%.
**Reincidencia:** 2ª+ misma sesión = ⚫ (max −10).
**LEARNED_FROM_CORRECTION:** Corrección tras feedback → Δ0.
**Sin decay temporal (ADR-022).** Confianza = informativa, NO bloqueante (ADR-027).

**Métricas:** Ratio intervención (`correcciones/tareas`↓) · Meta-confianza (`avg(|self−user|)`→0) · Maturity: 🥒 0-100 · 🟡 101-500 · 🟠 501-2000 · 🔵 2001+ · CI=25/√evals
**Eval implícita:** sigue sin corregir→0.5 · repite instrucción→auto-check · frustración→confirmar

---

## 3. Anti-patrones (Agent)

| Código | Sev. | Dominio | Señal |
|--------|:----:|---------|-------|
| `SECRETARY` | 🔴 | JUDGMENT | Ejecutas sin pensar |...

README excerpt

# AICE Skill

AI Confidence Engine skill for OpenClaw.

## What it does
- Bidirectional scoring across 5 domains (TECH, OPS, JUDGMENT, COMMS, ORCH)
- Agent + User + Team confidence model
- Hub sync support (`api.hubaice.com`)

## Files
- `SKILL.md` — core behavior/spec
- `confidence.template.json` — safe starter template (no personal data)
- `resources/` — reference docs and pattern definitions
- `scripts/` — helper scripts

## Install
1. Copy this folder into your OpenClaw skills directory.
2. Rename `confidence.template.json` to `confidence.json` for a fresh install.
3. Load the skill in your OpenClaw startup flow.

## Notes
- Do **not** commit personal logs or private API keys.
- Hub scoring starts fresh server-side by design.

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