light-memory-pm

Manage persistent memory and cross-session context for research projects.

514|67|Updated Jun 7, 2026
One-click install
npx skills add https://github.com/Light0305/Light-skills --skill light-memory-pm
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: light-memory-pm
Source: https://github.com/Light0305/Light-skills/tree/main/skills/light-memory-pm
Command: npx skills add https://github.com/Light0305/Light-skills --skill light-memory-pm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manage persistent memory and cross-session context for long-running research projects.

Core Features & Use Cases

  • Two-layer memory model (global Light memory and per-project db09) with SSOT indexing.
  • Memory write policies to MEMORY.md and project_card.md; per-project milestones and version history linkage.
  • Handoff-ready artifacts and active recovery workflow to resume work across sessions.

Quick Start

Create and maintain a persistent project memory across sessions by using a two-layer memory model and handoff artifacts to enable seamless cross-session recovery.

Frequently Asked Questions about light-memory-pm

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

FAQPage Schema
How do I maintain persistent context for a long-running research project across multiple sessions?

To maintain persistent context across multiple sessions, use a two-layer memory model with global Light memory and per-project memory, enforcing explicit indexing through MEMORY.md and project-level artifacts for seamless cross-session recovery.

What is the best way to manage cross-session memory for literature review and experiments?

The best way to manage cross-session memory for literature review and experiments is implementing a two-layer memory model that tracks milestones and version history, creating handoff-ready artifacts for active recovery workflows.

Can I use persistent project memory to ensure continuity during manuscript drafting?

Yes, you can use persistent project memory to ensure continuity during manuscript drafting by maintaining per-project milestones and version history linkage, enabling auditable history and handoff-ready artifacts for resuming work.

How does the two-layer memory model handle cross-session recovery for research workflows?

The two-layer memory model handles cross-session recovery by combining global Light memory with per-project memory, using explicit MEMORY.md indexing as a single source of truth to restore research workflow continuity.

When do I need explicit memory indexing for research project management?

You need explicit memory indexing for research project management when running long tasks like data collection or experiments across multiple sessions, ensuring auditable history and seamless recovery through handoff-ready artifacts.