Agent skill

Tiered Memory

by kubefleet-dev in kubefleet-dev/kubefleet

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

Apache-2.0Auto-check passedAgent Workflows

Install Tiered Memory

skills CLI
$ npx skills add kubefleet-dev/kubefleet --skill tiered-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install kubefleet-dev/kubefleet tiered-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/kubefleet-dev/kubefleet.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/tiered-memory .claude/skills/tiered-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tiered-memory
GitHub stars
162
Used in
1 other repo
Token cost
~1.8k tokens
SKILL.md length
745 words
Files
1
Skills in repo
11
Repo updated
First seen
Licence
Apache-2.0

At a glance

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

  • Works in 3 steps: End of session: Compress Hot → Cold… → Aged cold entries: Promote Cold → Wiki… → On-demand wiki writes: Any agent can…
  • Tasks that involve Agent memory
  • SKILL.md covers Overview, Memory Tiers, When to Load Each Tier and Spawn Template Pattern, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Tiered Memory is an agent skill from kubefleet-dev/kubefleet. Three-tier agent memory model (hot/cold/wiki) for context reduction per spawn

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Agent memory. The repository describes itself as: KubeFleet is an open-source Kubernetes multi-cluster application management solution. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Agent memory

Example prompts

  • “/tiered-memory”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. End of session: Compress Hot → Cold summary (target: ~10% of session verbosity)
  2. Aged cold entries: Promote Cold → Wiki for decisions/facts that aged into stable knowledge
  3. On-demand wiki writes: Any agent can request Scribe to write a wiki entry mid-session

What it can do on your machine

Read from SKILL.md and the folder at commit ea05fcb. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tiered Memory loads about 1.8k tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 745 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from kubefleet-dev/kubefleet at commit ea05fcb, republished under its Apache-2.0 licence (© kubefleet-dev). 745 words, ~1,819 tokens.

Download SKILL.mdSave it as .claude/skills/tiered-memory/SKILL.md (or your agent's skills folder).
name
tiered-memory
description
Three-tier agent memory model (hot/cold/wiki) for context reduction per spawn
domain
memory-management, performance
confidence
design (runtime not yet implemented)
source
design proposal

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.
❄️ Cold Tier — Summarized Cross-Session History
  • Size target: larger summary, not full transcript (~8–12KB typical)
  • 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: Rolling window (default proposal: 30 days). Eligible entries are then promoted to Wiki.
  • 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.

When to Load Each Tier

SituationHotColdWiki
New task, no prior context needed✅❌❌
Resuming interrupted work✅✅❌
Debugging a recurring issue✅✅❌
Implementing against a spec/ADR✅❌✅
Onboarding to unfamiliar subsystem✅❌✅
Post-incident review✅✅✅

Spawn Template Pattern

The default spawn prompt should include Hot tier only:

## Memory Context

### Hot (current session)
{hot_context}

Add --include-cold when the task needs history:

## Memory Context

### Hot (current session)
{hot_context}

### Cold (summarized history — load on demand)
See: .squad/memory/cold/{agent-name}.md

Add --include-wiki when the task needs domain knowledge:

## Memory Context

### Hot (current session)
{hot_context}

### Wiki (durable reference)
See: .squad/memory/wiki/{topic}.md

Integration with Scribe Agent (design — not yet implemented)

Scribe is the proposed memory coordinator for this system. Once the runtime lands, Scribe will:

  1. End of session: Compress Hot → Cold summary (target: ~10% of session verbosity)
  2. Aged cold entries: Promote Cold → Wiki for decisions/facts that aged into stable knowledge
  3. On-demand wiki writes: Any agent can request Scribe to write a wiki entry mid-session

Until then, see the Scribe charter for current behavior: .squad/agents/scribe/charter.md


Show full SKILL.md (288 more words)Show less

Implementation Checklist (tracked in #1264)

  • Scribe writes Hot context file at session start (.squad/memory/hot/{agent}.md)
  • Scribe compresses and writes Cold summary at session end
  • Spawn templates default to Hot-only
  • Coordinators add --include-cold / --include-wiki flags as needed
  • Wiki entries stored in .squad/memory/wiki/
  • Cold entries stored in .squad/memory/cold/ with rolling TTL

References


Spawn Template

Spawn Template: Agent with Tiered Memory

Use this template when spawning any Squad agent. By default it loads Hot tier only. Add optional sections as needed.


Task

{task_description}

WHY

{why_this_matters}

Success Criteria

  • {criterion_1}
  • {criterion_2}

Memory Context

🔥 Hot (always included)

Paste current session context here (~2–4KB target):

Current task: {task_description}
Active decisions: {decisions_this_session}
Last actions: {last_3_to_5_actions}
Blockers: {current_blockers_or_none}
Talking to: {current_interlocutor}

❄️ Cold (include when task needs history — add --include-cold)

Load on demand. Do not inline unless specifically needed.

Summarized cross-session history is at: .squad/memory/cold/{agent-name}.md

Include when:

  • Resuming interrupted work
  • Debugging a recurring issue
  • "What have we tried before?"

To load cold memory, add this section and fetch the file before spawning:

## Cold Memory Summary
{contents_of_.squad/memory/cold/{agent-name}.md}

📚 Wiki (include when task needs domain knowledge — add --include-wiki)

Load on demand. Reference specific wiki docs by path.

Wiki entries are at: .squad/memory/wiki/

Include when:

  • Implementing against an ADR or spec
  • Onboarding to unfamiliar subsystem
  • Need stable conventions or API contracts

To load wiki, add this section and reference the specific doc:

## Wiki Reference
{contents_of_.squad/memory/wiki/{topic}.md}

Escalation

If blocked or uncertain:

  • Architecture questions → @picard
  • Security concerns → @worf
  • Infrastructure/deployment → @belanna
  • Memory/history questions → @scribe

Notes

  • Hot tier is always included; keep it focused
  • Cold adds a summary; only include when history is relevant
  • Wiki adds variable size; only include specific relevant docs
  • Runtime backing is tracked in bradygaster/squad#1264 — until those changes land, this skill is design-only and agents continue to load full history.md + decisions.md on every spawn

© kubefleet-dev, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/skills/tiered-memory of kubefleet-dev/kubefleet.

Open the folder on GitHubat commit ea05fcb

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in kubefleet-dev/kubefleet, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Tiered Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tiered Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tiered Memory this skillkubefleet-dev/kubefleet1621 repos~1.8kAutomated safety check: PassApache-2.0
Coding Agent Session Findercode-yeongyu/oh-my-openagent70k1 repos~2.8kAutomated safety check: PassCustom licence
Claude-Mem Cloud Syncthedotmack/claude-mem98k1 repos~1kAutomated safety check: NotesApache-2.0
Cognee CLI Memory Commandstopoteretes/cognee32k1 repos~2.2kAutomated safety check: NotesApache-2.0
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Claude-Mem Searchthedotmack/claude-mem98k1 repos~511Automated safety check: PassApache-2.0

Similar skills

  • Coding Agent Session Finder

    code-yeongyu/oh-my-openagent

    Finds, reads and reconstructs past coding-agent sessions across Codex, Claude, OpenCode, Senpi and many other local agent logs.

    70k GitHub starsUsed in 1 repo~2.8k tokens
    Agent WorkflowsAuto-check passed
  • Claude-Mem Cloud Sync

    thedotmack/claude-mem

    Checks claude-mem cloud sync status and guides you through connecting a cmem.ai Pro account without the sync token ever passing through the chat.

    98k GitHub starsUsed in 1 repo~1k tokens
    Agent WorkflowsAuto-check: notes
  • Cognee CLI Memory Commands

    topoteretes/cognee

    Drives cognee from the terminal with remember, recall, forget and improve memory commands, dataset and config management and database migrations.

    32k GitHub starsUsed in 1 repo~2.2k tokens
    Agent WorkflowsAuto-check: notes
  • Neat-Freak Knowledge Closeout

    KKKKhazix/khazix-skills

    Brings project docs, agent rule files, authorized memory and leftover workspace files back in line with what the code and runtime actually do at the end of a work session.

    21k GitHub stars~1.9k tokensUpdated 6 days ago
    Agent WorkflowsAuto-check passed
  • Claude-Mem Search

    thedotmack/claude-mem

    Searches the user's persistent cross-session memory for timestamped observations synthesized from past agent sessions on cmem.ai.

    98k GitHub starsUsed in 1 repo~511 tokens
    Agent WorkflowsAuto-check passed
  • Beads Task Memory

    gastownhall/beads

    Tracks multi-session work with dependencies in the bd issue tracker so the agent can find ready tasks and recover its context after conversation compaction.

    28k GitHub stars~1.2k tokensUpdated today
    Agent WorkflowsAuto-check passed

More from kubefleet-dev/kubefleet

All 11 skills in this repo
  • Cross Squad

    kubefleet-dev/kubefleet

    Coordinating work across multiple Squad instances — discovery, delegation, and disambiguation when the user says 'squad' (the product) vs casual English 'group of agents'.

    162 GitHub starsUsed in 1 repo~2.5k tokens
    Auto-check passed
  • Iterative Retrieval

    kubefleet-dev/kubefleet

    Max-3-cycle protocol for agent sub-tasks with WHY context and coordinator validation.

    162 GitHub starsUsed in 1 repo~1.6k tokens
    Auto-check passed
  • Coordinator Response Mode

    kubefleet-dev/kubefleet

    Selecting WHO handles work is the Routing table; selecting HOW they handle it (Direct, Lightweight, Standard, Full) is Response Mode.

    162 GitHub starsUsed in 1 repo~1.2k tokens
    Auto-check passed
  • Cross Squad Communication

    kubefleet-dev/kubefleet

    Protocol for sending queries, delegating tasks, and sharing context between independent Squad instances across different repositories

    162 GitHub starsUsed in 1 repo~4.8k tokens
    Auto-check passed
  • Reflect

    kubefleet-dev/kubefleet

    Learning capture system that extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes.

    162 GitHub starsUsed in 1 repo~1.9k tokens
    Auto-check passed
  • Squad

    kubefleet-dev/kubefleet

    Squad's command catalog and interactive menu. An agent skill from kubefleet-dev/kubefleet.

    162 GitHub starsUsed in 1 repo~2.7k tokens
    Auto-check passed

Categories

Questions about Tiered Memory

What does Tiered Memory do?

Three-tier agent memory model (hot/cold/wiki) for context reduction per spawn. Tiered Memory is an agent skill from kubefleet-dev/kubefleet.

When should I use Tiered Memory?

Tiered Memory fits situations like: tasks that involve Agent memory.

How do I install Tiered Memory in Claude Code?

Run `npx skills add kubefleet-dev/kubefleet --skill tiered-memory -a claude-code`. Or copy the skill folder (.github/skills/tiered-memory in kubefleet-dev/kubefleet) into .claude/skills/tiered-memory in your project. Claude Code loads it when a task matches its description.

How do I install Tiered Memory in Codex?

Run `npx skills add kubefleet-dev/kubefleet --skill tiered-memory -a codex`. Or copy the skill folder (.github/skills/tiered-memory in kubefleet-dev/kubefleet) into .agents/skills/tiered-memory in your project. Codex loads it when a task matches its description.

Can I use Tiered Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kubefleet-dev/kubefleet --skill tiered-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tiered-memory, .gemini/skills/tiered-memory, .github/skills/tiered-memory and .opencode/skills/tiered-memory in your project.

What does Tiered Memory need to run?

SKILL.md names no scripts, command-line tools or credentials: Tiered Memory is instructions for the agent only.

Does Tiered Memory access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Tiered Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tiered Memory use?

Tiered Memory is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tiered Memory use?

About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tiered Memory?

Skills that share tags, products or a category with Tiered Memory: Coding Agent Session Finder (code-yeongyu/oh-my-openagent, 70k stars), Claude-Mem Cloud Sync (thedotmack/claude-mem, 98k stars), Cognee CLI Memory Commands (topoteretes/cognee, 32k stars) and Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tiered Memory?

kubefleet-dev (a GitHub organization) maintains it in kubefleet-dev/kubefleet, which has 162 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 8, 2026.

Source: kubefleet-dev/kubefleet on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.