Skills

Tiered Memory

Three-tier agent memory model (hot/cold/wiki) for context reduction per spawn

Install

npx skills add microsoft/waza --skill tiered-memory -g -a claude-code -y
Repository
microsoft/waza1.5k
Category
AI and agents
Updated
4d ago
License
MIT
Context cost
Mediumabout 1,794 tokens
Runs scripts
No, instructions only

What it does

Three-tier agent memory model (hot/cold/wiki) for context reduction per spawn

Skill: Tiered Agent Memory

Status (v0.10.0): This skill describes a design proposal, not a shipped runtime. Skill files install via squad init/upgrade, but the underlying tier scaffolding (.squad/memory/hot/, cold/, wiki/), Scribe promotion logic, and spawn-template tier-aware reads are tracked in bradygaster/squad#1264. Until those land, agents continue to load full history.md + decisions.md on every spawn.

Overview

Squad agents today load their full context history on every spawn, which grows unboundedly across sessions. The Tiered Agent Memory model proposes a three-tier separation so agents only load the bytes that are actually relevant to the current task, with older context kept available on demand.


Memory Tiers

🔥 Hot Tier, Current Session Context

  • Size target: keep small (~2, 4KB typical)
  • Load policy: Always loaded. Every spawn includes hot memory by default.
  • Contents: Current task description, active decisions made this session, immediate blockers, last 3, 5 actions taken, who you are talking to right now.
  • Lifetime: Current session only. Discarded after session ends (Scribe promotes relevant parts to Cold).
  • Purpose: Provide immediate task context without any latency or load decision.
Read the whole SKILL.md on GitHub

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