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Skill Nud Inventario Processos — Productivity skill for Claude Code

Productivity community

Claude Skill (método agnóstico de modelo) que transforma insumos brutos — transcrição, áudio, docs, anotações — em um Inventário de Processos SIPOC-R em .xlsx.

How to install Skill Nud Inventario Processos

This entry records only its repository, not the path inside it, so there is no exact command to give. Open whatevertr/skill-nud-inventario-processos and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Skill Nud Inventario Processos does

Claude Skill (método agnóstico de modelo) que transforma insumos brutos — transcrição, áudio, docs, anotações — em um Inventário de Processos SIPOC-R em .xlsx. Parte do NUD | Constellation Method, de Thainá Ramos. CC-BY-4.0.

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README

🇧🇷 Português

nud-inventario-processos

[![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)

A **skill for Claude** (Anthropic) that turns raw inputs — transcripts, audio, `.pptx`, `.docx`, policies, procedures, notes and PDF flowcharts — into a **Process Inventory** in the **SIPOC-R** model, delivered as a ready-to-use `.xlsx`.

Part of the **NUD | Constellation Method**, by Thainá Ramos.

**Compatibility:** packaged as a **Claude Skill** (Anthropic's Agent Skills format — it triggers on its own in Claude Code / claude.ai). The **method is model-agnostic**: the same content works in **any chat LLM** by pasting `SKILL.md` + `references/` as context, and `builder.py` runs on **any Python** (e.g. ChatGPT's Code Interpreter).

What it does

Reads the input with process technique and puts each process on its own row (one owner per row).
Fills the SIPOC-R model: Supplier · Input · Process · Owner · Output · Customer, plus SLA, Indicator, Systems, Legislation, Risks, Opportunities.
Infers risks (FMEA-inspired, severity only) and applicable legislation, marking every inference by text COLOR (orange) and a continuous ID (R01, O01) for you to validate — it never presents a guess as fact.
Chooses the granularity level (N1 macro · N2 per handoff · N3 intra-station) by asking the user, with the most likely suggestion.
Delivers an Excel that matches the model exactly (table, colors, structure).