ingestor

Compute SHA-256 hashes, detect duplicates, and emit an Ingestion Decision Matrix.

Updated Apr 24, 2026

Search Tags:#ingestion #hashing #duplication-detection #content-classification #noise-filtering #ingestion-matrix

Ready to run

npx skills add https://github.com/Aurora-AI/Elysiancorpfront --skill ingestor

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ingestor
Source: https://github.com/Aurora-AI/Elysiancorpfront/tree/main/.aurora/skills/ingestor
Command: npx skills add https://github.com/Aurora-AI/Elysiancorpfront --skill ingestor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Gatekeeper da memória da Aurora: atua como o filtro de ruído, impedindo que conteúdo redundante ou de baixo ganho entre no vault e garantindo que apenas conhecimento com ganho real atravesse o pipeline de ingestão.

Core Features & Use Cases

Calcula hash SHA-256 de documentos para detecção de duplicidade.
Classifica o material como Material Cognitivo, Nova Skill ou Hibrido.
Emite a MATRIZ DE DECISAO DE INGESTAO e reporta o status do pipeline (Stage 1/3), aguardando aprovação humana.
Realiza handoff automático para Stage 2 (Bibliotecário) e Stage 3 (Cientista) quando apropriado.
Referencia regras de classificação e fluxos de ingestao para orientação operacional.

Quick Start

Forneça um documento para ingestão cognitiva usando o comando /ingestao-cognitiva para gerar a MATRIZ DE DECISAO.

Frequently Asked Questions about ingestor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I detect duplicate content before it enters my knowledge repository?▼

Duplicate content detection computes a SHA-256 hash for each input document and checks it against existing entries. This hashing mechanism prevents redundant material from entering the cognitive ingestion pipeline and cluttering the vault.

How does cognitive ingestion noise filtering work for incoming documents?▼

Cognitive ingestion noise filtering evaluates incoming documents by estimating their content gain and risk. It classifies material as Cognitive Content, New Skill, or Hybrid to ensure only high-value knowledge passes through the pipeline.

What is an ingestion decision matrix and when do I need it?▼

An ingestion decision matrix is a generated file that reports the estimated gain, risk, and classification of a document. You need it when processing cognitive content to evaluate whether material should be approved for repository entry.

Can I automate document handoff to downstream stages after noise filtering?▼

Yes, upon approval at the human gate, the pipeline performs an automatic handoff to Stage 2 (Librarian) and Stage 3 (Scientist). This ensures approved documents flow seamlessly into downstream cognitive processing.

Does cognitive ingestion require human approval before adding content to the vault?▼

Yes, cognitive ingestion requires a human gate. After generating the decision matrix with value deltas and classifications, the pipeline awaits explicit human approval before allowing content into the repository.

Why are low-value documents blocked from entering the cognitive pipeline?▼

Low-value documents are blocked to prevent noise and redundancy in the vault. The ingestor estimates a content gain delta and filters out material that does not provide a meaningful knowledge addition to the repository.