Remember

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sneg55

remember

Review auto-memory entries and propose promotions to CLAUDE.md, CLAUDE.local.md, or shared memory. Also detects outdated, conflicting, and duplicate entries across memory layers.

Overview

Publisher	sneg55
Repository	`agent-starter`
Skill name	`remember`
Stars	74
Forks	4
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 sneg55 on GitHub. Read the source before you install it.

Installation

Install the Remember 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/sneg55/agent-starter/tree/main/skills/remember
Enable the skill in any chat where you want it available.

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/sneg55/agent-starter.git /tmp/agent-starter
mkdir -p .claude/skills
cp -r /tmp/agent-starter/skills/remember .claude/skills/remember

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

Use it in TypingMind

Enable Remember 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 Remember 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 Remember 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 Review

Goal

Review the user's memory landscape and produce a clear report of proposed changes, grouped by action type. Do NOT apply changes - present proposals for user approval.

Steps

1. Gather all memory layers

Read CLAUDE.md and CLAUDE.local.md from the project root (if they exist). Your auto-memory content is already in your system prompt - review it there. Note which team memory sections exist, if any.

Success criteria: You have the contents of all memory layers and can compare them.

2. Classify each auto-memory entry

For each substantive entry in auto-memory, determine the best destination:

Destination	What belongs there	Examples
CLAUDE.md	Project conventions and instructions for Claude that all contributors should follow	"use bun not npm", "API routes use kebab-case", "test command is bun test", "prefer functional style"
CLAUDE.local.md	Personal instructions for Claude specific to this user, not applicable to other contributors	"I prefer concise responses", "always explain trade-offs", "don't auto-commit", "run tests before committing"
Team memory	Org-wide knowledge that applies across repositories (only if team memory is configured)	"deploy PRs go through #deploy-queue", "staging is at staging.internal", "platform team owns infra"
Stay in auto-memory	Working notes, temporary context, or entries that don't clearly fit elsewhere	Session-specific observations, uncertain patterns

Important distinctions:

CLAUDE.md and CLAUDE.local.md contain instructions for Claude, not user preferences for external tools (editor theme, IDE keybindings, etc. don't belong in either)
Workflow practices (PR conventions, merge strategies, branch naming) are ambiguous - ask the user whether they're personal or team-wide
When unsure, ask rather than guess

Success criteria: Each entry has a proposed destination or is flagged as ambiguous.

3. Identify cleanup opportunities

Scan across all layers for:

Duplicates: Auto-memory entries already captured in CLAUDE.md or CLAUDE.local.md → propose removing from auto-memory
Outdated: CLAUDE.md or CLAUDE.local.md entries contradicted by newer auto-memory entries → propose updating the older layer
Conflicts: Contradictions between any two layers → propose resolution, noting which is more recent

Success criteria: All cross-layer issues identified.

4. Present the report

Output a structured report grouped by action type:

Promotions - entries to move, with destination and rationale
Cleanup - duplicates, outdated entries, conflicts to resolve
Ambiguous - entries where you need the user's input on destination
No action needed - brief note on entries that should stay put

If auto-memory is empty, say so and offer to review CLAUDE.md for cleanup.

Success criteria: User can review and approve/reject each proposal individually.

Rules

Present ALL proposals before making any changes
Do NOT modify files without explicit user approval
Do NOT create new files unless the target doesn't exist yet
Ask about ambiguous entries - don't guess

Frequently asked questions

What does the Remember AI skill do?

Review auto-memory entries and propose promotions to CLAUDE.md, CLAUDE.local.md, or shared memory. Also detects outdated, conflicting, and duplicate entries across memory layers.

Why use Remember on TypingMind?

Because you install it once and use it with any model. Remember 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 Remember in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sneg55/agent-starter/tree/main/skills/remember. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Remember?

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 Remember?

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

Is the Remember AI skill free?

Yes. It is published on GitHub by sneg55 under the MIT 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Memory Review

Goal

Steps

1. Gather all memory layers

2. Classify each auto-memory entry

3. Identify cleanup opportunities

4. Present the report

Rules

Frequently asked questions

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