10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
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.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install brugillo/aiceInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
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
| 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%.
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
| Código | Sev. | Dominio | Señal |
|---|---|---|---|
SECRETARY |
🔴 | JUDGMENT | Ejecutas sin pensar |
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
AI Confidence Engine skill for OpenClaw.
api.hubaice.com)SKILL.md — core behavior/specconfidence.template.json — safe starter template (no personal data)resources/ — reference docs and pattern definitionsscripts/ — helper scriptsconfidence.template.json to confidence.json for a fresh install.# 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 |...# 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.
generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
Productivity system based on Maya calendar with 13 natural tones for project management and personal development
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.