What is tiered-memory?

A three-level memory system for coding agents: recent session details, summarized past work, and longer-term reference information.

Use it to organize agent context across sessions and load older decisions only when a task needs them.

It reduces the amount of old or irrelevant conversation loaded each time an agent starts.

tiered-memory — Skill for Claude Code and Codex by Azure-Samples

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add Azure-Samples/eShopLite --skill tiered-memory

Clone the repo

git clone --depth 1 https://github.com/Azure-Samples/eShopLite

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/azure-samples/eshoplite/tiered-memory/github.svg)](https://agentmods.dev/skills/azure-samples/eshoplite/tiered-memory)

Your own site

<a href="https://agentmods.dev/skills/azure-samples/eshoplite/tiered-memory"><img src="https://agentmods.dev/badge/skills/azure-samples/eshoplite/tiered-memory/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/azure-samples/eshoplite/tiered-memory"><img src="https://agentmods.dev/badge/skills/azure-samples/eshoplite/tiered-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,804 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Agent Snooping · line 233
Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.

Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00025	$0.01804
Opus 5.5	$0.00010	$0.00722
Sonnet 5.5	$0.00005	$0.00361
Haiku 4.5	$0.00003	$0.00180

Measured 1mo ago against content hash 9ee36cd7dac5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

tiered-memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

tiered-memory — 100% identical, 0 lines differ

.squad/templates/skills/tiered-memory/SKILL.md · 235 lines

How it starts

The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Tiered Agent Memory

Overview

Squad agents currently load their full context history on every spawn, resulting in 34–74KB payloads per agent (8,800–18,500 tokens). Measurement shows 82–96% of that context is "old noise" — information that is no longer relevant to the current task. The Tiered Agent Memory skill introduces a three-tier memory model that eliminates this bloat, achieving 20–55% context reduction per spawn in production.

Memory Tiers

🔥 Hot Tier — Current Session Context

Size target: ~2–4KB
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.

❄️ Cold Tier — Summarized Cross-Session History

Size target: ~8–12KB
Load policy: Load on demand. Include only when the task explicitly needs history.
Contents: Summarized past sessions (compressed by Scribe), cross-session decisions, recurring patterns, unresolved issues from prior work.
Lifetime: 30 days rolling window. After 30 days, Scribe promotes to Wiki tier.
Purpose: Answer "what have we tried before?" and "what was decided?" without replaying full transcripts.
How to include: Pass --include-cold in spawn template or add ## Cold Memory section.

📚 Wiki Tier — Durable Structured Knowledge

Size target: variable, structured reference docs
Load policy: Async write, selective read. Load only when task requires domain knowledge.
Contents: Architecture decisions (ADRs), agent charters, routing rules, stable conventions, external API contracts, known platform constraints.
Lifetime: Permanent until explicitly deprecated.
Purpose: Authoritative reference. Not history — structured facts.
How to include: Pass --include-wiki or reference specific wiki doc paths in spawn template.

Read the full file on GitHub · 235 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 235 lines · 25 tokens per session scan A 9ee36cd7dac5

Subscribe to this mod's changes

tiered-memory is a skill published in the GitHub repository Azure-Samples/eShopLite (168 stars, last pushed 5d ago), licensed MIT. It adds 25 tokens to every session and 1,804 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Memory and context aspire azd azd-templates azure-openai chromadb deepseek-r1

mempalace

MemPalace — Local AI memory with 96.6% recall. Semantic search, temporal knowledge graph, palace architecture (wings/rooms/drawers). Free, no cloud, no API keys.

MemPalace/mempalace · 47 tokens

mempalace-task

Create, hand off, claim, execute, and close agent tasks through the MemPalace logstream. Use when the user wants to delegate work, prepare a ready-to-paste task for another agent, receive a MemPalace task id, or explicitly launch a supported headless agent in controlled mode.

MemPalace/mempalace · 67 tokens

tiered-memory