skills.rest
AshleyHollis
AshleyHollisCOMMUNITY
Explore all skills by this author →
GitHub

tiered-memory

Implement a three-tier hot, cold, and wiki memory model for agents.

Updated May 10, 2026
Search Tags:#performance optimization#memory management#agent context#context reduction#memory tiers
One-click install
npx skills add https://github.com/AshleyHollis/agentic-identity-lab --skill tiered-memory-ashleyhollis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tiered-memory
Source: https://github.com/AshleyHollis/agentic-identity-lab/tree/main/.copilot/skills/tiered-memory
Command: npx skills add https://github.com/AshleyHollis/agentic-identity-lab --skill tiered-memory-ashleyhollis

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the issue of excessive context bloat in agent spawns, reducing the payload size and improving performance.

Core Features & Use Cases

  • Three-Tier Memory Model: Implements a hot, cold, and wiki tier for memory storage, reducing the size of context payloads.
  • Context Reduction: Achieves 20-55% reduction in context size per spawn, improving efficiency.
  • Use Case: Use this Skill to enhance the performance of agents by reducing the amount of redundant information they carry.

Quick Start

Use the tiered-memory skill to spawn an agent with the required memory tiers.

Frequently Asked Questions about tiered-memory

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

FAQPage Schema
How do I reduce agent context bloat to improve spawn performance?▼

You can reduce agent context bloat by implementing a three-tier memory model that manages hot, cold, and wiki memory, achieving a 20-55% reduction in payload size per spawn.

What is a three-tier memory model for agent context management?▼

A three-tier memory model for agent context management utilizes hot, cold, and wiki memory tiers to organize and reduce redundant information, minimizing the overall payload carried during agent spawns.

How much context size reduction can I achieve by tiering agent memory?▼

Tiering agent memory achieves a 20-55% reduction in context size per spawn, significantly lowering payload bloat and improving overall agent efficiency and spawn performance.

Do I need a memory coordinator to manage hot, cold, and wiki memory tiers?▼

Yes, managing hot, cold, and wiki memory tiers requires a memory coordinator to properly handle tier-specific context management and effectively reduce agent payload sizes.

What's the best way to optimize agent memory for redundant information?▼

The best way to optimize agent memory for redundant information is applying a tiered memory model that separates context into hot, cold, and wiki tiers, effectively reducing payload bloat by up to 55%.

Related Skills

Explore More Software Engineering Skills→
aaron-he-zhuaaron-he-zhu
142

memory-management

Manage two-layer memory with hot cache and cold storage for SEO projects.

Community
Basic
Leep-GHLeep-GH

tiered-memory

Implement hot, cold, and wiki memory tiers to reduce agent context load.

Community
Advanced
martinholovskymartinholovsky
12

sota-performance

Audit code for bottlenecks and prescribe performance fixes.

Community
Advanced
goodnessibehgoodnessibeh
1

memory-systems

Design agent memory systems and compare production frameworks for cross-session persistence.

Community
Advanced