para-memory-files

Organize persistent knowledge across AI sessions using the PARA method.

Updated Mar 11, 2026
One-click install
npx skills add https://github.com/Dinuda/summun.cloud --skill para-memory-files-dinuda
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: para-memory-files
Source: https://github.com/Dinuda/summun.cloud/tree/main/skills/para-memory-files
Command: npx skills add https://github.com/Dinuda/summun.cloud --skill para-memory-files-dinuda

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a robust, file-based memory system that prevents knowledge loss across sessions and helps manage information overload by organizing it according to Tiago Forte's PARA method.

Core Features & Use Cases

  • Structured Knowledge Graph: Stores atomic facts in YAML files within PARA-defined folders (Projects, Areas, Resources, Archives).
  • Daily Notes Timeline: Captures raw events and conversations as a chronological record.
  • Tacit Knowledge Capture: Documents user patterns, preferences, and lessons learned.
  • Automated Curation: Summarizes knowledge and manages retrieval priority based on access recency and frequency.
  • Use Case: When discussing a new client, the skill can create an entry in areas/companies/<client_name>/items.yaml to store key facts, and update summary.md to reflect the latest interactions.

Quick Start

Use the para-memory-files skill to save the fact "The user prefers dark mode" to the relevant entity.

Frequently Asked Questions about para-memory-files

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

FAQPage Schema
How do I organize knowledge with the PARA method across AI sessions?▼

To organize knowledge with the PARA method, this system stores atomic YAML facts in Projects, Areas, Resources, and Archives folders, creating a persistent knowledge graph that prevents data loss across AI sessions.

What is the best way to maintain persistent memory for note taking in AI workflows?▼

Maintaining persistent memory relies on a three-layer system: a PARA knowledge graph with atomic YAML facts, daily notes as a raw timeline, and tacit knowledge tracking for user patterns and preferences.

How do I save a new fact to a specific entity using file-based memory?▼

Saving a new fact to a specific entity involves writing atomic data to the relevant YAML file, such as adding client details to areas/companies/<client_name>/items.yaml, which automatically updates the summary.md file.

Does this PARA knowledge management system handle memory decay and automated curation?▼

Yes, the PARA knowledge management system handles memory decay and automated curation by adjusting retrieval priority based on access recency and frequency, while performing weekly synthesis to summarize stored knowledge.

Can I capture tacit knowledge and user preferences with PARA note taking?▼

Yes, capturing tacit knowledge is possible through a dedicated memory layer that documents user patterns, preferences, and lessons learned, functioning alongside the daily notes timeline and structured knowledge graph.