Memory Manager

Community

XuanRanL

memory-manager

Manage HOT/WARM/COLD memory transitions, Wiki Phase 1/2/3 entity sedimentation, GDPR Art 17 purge. Triggered by hooks/stop_finalize.py + /forget-project command.

Overview

Publisher	XuanRanL
Repository	`loamwright-SEO-Skill`
Skill name	`memory-manager`
Stars	52
Forks	9
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by XuanRanL on GitHub. Read the source before you install it.

Installation

Install the Memory Manager AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/XuanRanL/loamwright-SEO-Skill/tree/main/subskills/cross-cutting/memory-manager
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/XuanRanL/loamwright-SEO-Skill/tree/main/subskills/cross-cutting/memory-manager

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/XuanRanL/loamwright-SEO-Skill.git /tmp/loamwright-SEO-Skill
mkdir -p .claude/skills
cp -r /tmp/loamwright-SEO-Skill/subskills/cross-cutting/memory-manager .claude/skills/memory-manager

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Memory Manager in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Memory Manager on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Memory Manager is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Memory Manager

Per seo-geo HOT/WARM/COLD pattern.

Memory layers


projects/{slug}/                ← Per-client (HOT/WARM)
  ├── business-context.json     ← 90d TTL
  ├── research-cache/            ← 72h TTL
  └── ...

memory/                          ← Global (HOT/WARM/COLD)
  ├── entities/{id}.md           ← Permanent (Wiki Phase 1/2/3)
  ├── wiki/                      ← Phase 1/2/3 sediment
  ├── workspace/{task_id}/       ← HOT (current task)
  └── learned-patterns.json      ← Permanent (self-improvement)

Wiki Phase sedimentation

Phase 1: Mention (1-2 articles cite entity)
Phase 2: Established (3-9 cites; add 47 signals)
Phase 3: Authority (10+ cites; full schema + ai_resolution probe weekly)

GDPR Art 17 (forget command)


/forget-project <slug>:
  1. Move projects/{slug}/ → projects/.deleted/{slug}-{timestamp}/
  2. Tombstone file with deleted_at timestamp
  3. Schedule physical deletion in 30 days (per stop_finalize.py hook)
  4. Memory/entities/: do NOT delete unless explicit (cross-project shared)

Workflows

HOT → WARM (task completion)

After Stage: final, workspace/{task} → memory/workspace/.archived/{YYYY-MM}/{task}/

WARM → COLD (90d expiry)

After 90d: projects/{slug}/business-context.json.freshness_state = "expired" → Suggest /init --refresh

Cleanup (stop_finalize hook)

Archive completed tasks
Purge .deleted projects >30d old
Compact wiki entries that haven't been cited in 12 months

Frequently asked questions

What does the Memory Manager AI skill do?

Manage HOT/WARM/COLD memory transitions, Wiki Phase 1/2/3 entity sedimentation, GDPR Art 17 purge. Triggered by hooks/stop_finalize.py + /forget-project command.

Why use Memory Manager on TypingMind?

Because you install it once and use it with any model. Memory Manager is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Memory Manager in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/XuanRanL/loamwright-SEO-Skill/tree/main/subskills/cross-cutting/memory-manager. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Memory Manager?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Memory Manager?

As many as you like. As long as a model supports skills, you can use Memory Manager with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Memory Manager AI skill free?

Yes. It is published on GitHub by XuanRanL under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Tavily

openclaw

OrganizationPopular

Tavily web search, content extraction, and research tools.

Deep Research

Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any…

Exa Search

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search…

Wayfinder

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Memory Manager

Memory layers

Wiki Phase sedimentation

GDPR Art 17 (forget command)

Workflows

HOT → WARM (task completion)

WARM → COLD (90d expiry)

Cleanup (stop_finalize hook)

Frequently asked questions

Related AI Skills

Set up your own AI workspace now