memory-ingest

Ingest validated knowledge into categorized memory files and update indexes.

157|28|Updated Feb 7, 2026
One-click install
npx skills add https://github.com/Fr-e-d/GAAI-framework --skill memory-ingest-fr-e-d
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: memory-ingest
Source: https://github.com/Fr-e-d/GAAI-framework/tree/main/.gaai/core/skills/cross/memory-ingest
Command: npx skills add https://github.com/Fr-e-d/GAAI-framework --skill memory-ingest-fr-e-d

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill transforms validated knowledge into a structured, searchable long-term memory, ensuring that crucial project insights and decisions are persistently stored and easily retrievable.

Core Features & Use Cases

  • Knowledge Structuring: Organizes new information into predefined or new memory categories.
  • Index Management: Automatically updates master and domain-specific indexes for comprehensive discoverability.
  • Use Case: After a discovery phase identifies key architectural decisions and validated user feedback, this skill ingests these into the project's memory, making them accessible for future development or reference.

Quick Start

Ingest the latest validated architecture insights into the project memory.

Frequently Asked Questions about memory-ingest

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

FAQPage Schema
How do I persist validated architecture insights into long-term memory for AI agents?

You persist validated architecture insights by ingesting them into categorized memory files, which automatically updates master and domain indexes to ensure the knowledge is structured and easily retrievable by AI agents.

What is the best way to structure project knowledge to prevent data drift?

The best way to prevent data drift is to enforce knowledge validation during the memory ingestion process, ensuring that only validated decisions and discovery outputs are persisted into structured long-term memory files.

How does index management work when ingesting new project knowledge?

Index management works by automatically updating both master and domain-specific indexes whenever new project knowledge or strategy artefacts are ingested, maintaining comprehensive discoverability across all memory categories.

Can I organize marketing observations and strategy artefacts into new memory categories?

Yes, you can organize marketing observations and strategy artefacts by structuring them into predefined memory categories or creating new ones during the ingestion process to maintain organized and searchable knowledge.

Does this memory ingestion approach work for unvalidated discovery outputs?

No, this approach does not work for unvalidated discovery outputs because it ensures only validated information is persisted, actively preventing data drift and maintaining strict knowledge integrity for AI agents.

When do I need to update domain indexes during the knowledge management process?

You need to update domain indexes whenever you ingest new validated knowledge into categorized memory files, which automatically maintains comprehensive discoverability and keeps the master index synchronized.