projecoes-read-models

Use para criar projeções como 9BOX, dashboards e visões de leitura otimizadas para decisão.

16 stars

Best use case

projecoes-read-models is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Use para criar projeções como 9BOX, dashboards e visões de leitura otimizadas para decisão.

Teams using projecoes-read-models should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/projecoes-read-models/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/data-ai/projecoes-read-models/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/projecoes-read-models/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How projecoes-read-models Compares

Feature / Agentprojecoes-read-modelsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Use para criar projeções como 9BOX, dashboards e visões de leitura otimizadas para decisão.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

---

name: projecoes-read-models
description: Use para criar projeções como 9BOX, dashboards e visões de leitura otimizadas para decisão.
--------------------------------------------------------------------------------------------------------

# Instruções da Skill

Trabalhe exclusivamente no **lado de leitura** do sistema.
Tudo aqui deve ser **derivado** e **reconstruível**.

## Regras e Passos

1. **Modelagem (M):**

   * Defina tabelas de projeção (`nine_box_projections`, dashboards).
   * Nunca trate projeção como fonte da verdade.

2. **Ação (A):**

   * Crie Projectors que reagem a eventos (`AxesUpdated`).

3. **Lógica (L):**

   * Converta scores contínuos em bandas (low / mid / high).
   * Determine quadrante apenas na projeção.

4. **Teste (T):**

   * Teste reconstrução completa a partir de eventos simulados.

## Uso de Ferramentas

* Utilize scripts da pasta `/scripts/projections` se existirem.
* Evite lógica complexa em queries SQL.

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