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para-memory-files

Store persistent agent memory across sessions using the PARA framework.

Updated Apr 28, 2026
Search Tags:#knowledge-graph#memory-management#daily-notes#para-method#personal-knowledge#semantic-recall#fact-tracking
One-click install
npx skills add https://github.com/khoabd/paperclip --skill para-memory-files-khoabd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: para-memory-files
Source: https://github.com/khoabd/paperclip/tree/main/skills/para-memory-files
Command: npx skills add https://github.com/khoabd/paperclip --skill para-memory-files-khoabd

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

AI agents lose all context and learned knowledge when sessions restart, forcing you to re-share the same information, re-explain user preferences, and re-establish project context every time you interact. This Skill eliminates that friction by providing a persistent, file-based memory system that retains all your knowledge between sessions.

Core Features & Use Cases

  • Three-Layer Memory System: Organizes knowledge into a PARA-structured knowledge graph for entity facts, timestamped daily notes for event timelines, and a tacit knowledge file for user-specific operating patterns and preferences.
  • Intelligent Memory Management: Includes atomic fact tracking, memory decay rules to prioritize recent and frequently used information, and safe fact superseding instead of deletion to maintain a complete historical record.
  • Fast Semantic Recall: Integrates with qmd to enable both keyword and semantic search across all your stored memory, so you can find past context, project details, or user preferences in seconds.
  • Use Case: For example, if you’re managing multiple client projects, this Skill will automatically retain each client’s communication preferences, past project milestones, and your team’s learned lessons, so you can pick up work exactly where you left off in the next session without re-gathering context.

Quick Start

Use the para-memory-files skill to save the fact that your client prefers weekly progress reports sent on Friday mornings to their dedicated entity folder in your PARA memory system.

Frequently Asked Questions about para-memory-files

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

FAQPage Schema
How do I retain AI agent knowledge across sessions without losing context?▼

Persistent file-based memory retains AI agent knowledge across sessions by organizing information into a PARA-structured knowledge graph, timestamped daily notes, and a tacit knowledge file for user preferences.

What is the best way to organize personal knowledge for AI using the PARA method?▼

The PARA method organizes personal knowledge for AI by structuring atomic entity facts into a knowledge graph, tracking event timelines in daily notes, and storing user-specific operating patterns in a tacit knowledge file.

How does semantic recall work for retrieving stored facts from daily notes?▼

Semantic recall retrieves stored facts from daily notes by integrating with qmd to enable both keyword and semantic search across all memory layers, finding past context or project details in seconds.

Does this file-based memory system support multi-agent collaboration?▼

Yes, the file-based memory system supports multi-agent collaboration by managing shared planning files, allowing multiple agents to access and coordinate persistent knowledge across different sessions.

How does memory decay prioritize recent information in a knowledge graph?▼

Memory decay prioritizes recent information in a knowledge graph by applying rules that surface frequently used and high-priority facts, while safely superseding outdated facts instead of deleting them to maintain history.

Can I track client communication preferences and project milestones automatically?▼

Yes, you can track client communication preferences and project milestones automatically by saving facts to dedicated entity folders, retaining context so you pick up work exactly where you left off.

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