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Forget

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win4r
forget

Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely means cancel the current task.

Overview

Publisherwin4r
RepositoryMuseAI-Skills
Skill nameforget
Stars
382
Forks
116
Bundled files
1
Links
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by win4r on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/forget
  4. 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.
2

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/win4r/MuseAI-Skills.git /tmp/MuseAI-Skills
mkdir -p .claude/skills
cp -r /tmp/MuseAI-Skills/opt/hatch/skills/forget .claude/skills/forget
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Forget 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 Forget 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 Forget 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.

Forget

Treat forgetting as cleanup across Muse, not as editing one memory note. Information may also live in conversation history, other notes, preferences, goals, scheduled work, created items, search results, or active work that can write it back.

Use everyday language with the user and do not expose internal machinery. Say "memory," "reminders," "created items," "shared items," "logs," or "backups" instead of file names, database tables, indexes, projections, telemetry systems, tool names, agent types, or runtime machinery. Keep exact locators and technical details inside the private work. Get technical only when the user does or when they explicitly ask how the cleanup works.

Make a plan

Call forget.plan once with {}. It starts an ordinary untyped subagent with the normal tool catalog that derives the subject from the current conversation, so do not repeat sensitive text in tool arguments. Wait for its handoff instead of polling or doing a parallel search. Muse pins this child to muse-special, or to private Avocado on a confidential VM, independently of the active model selection.

The planner reads references/artifact-inventory.md, stays read-only, and checks:

  • original places and copies with the same meaning;
  • memory, search results, conversation context, and summaries made from it;
  • reminders, scheduled or active work, and outside sources that can recreate the information;
  • shared or published copies and anything Muse cannot erase.

It returns a concise plan covering what it found, what should change, how it will verify the cleanup, and known limits. Keep the handoff discreet; refer to "that information" instead of copying it into a new memory, todo, filename, or report. Use conversations privately to find downstream copies and future activity, but do not present the continued visibility or retention of the chat itself as a cleanup limit.

Ask, then execute

Show the user the plan's scope, irreversible actions, and important limits, translated into the everyday categories above, then ask one direct confirmation question. Silence, ambiguity, partial approval, or a changed scope is not confirmation.

After a later clear approval, call forget.confirm with {}. It starts a fresh ordinary untyped subagent with the same model policy and reads the latest plan and confirmation from the inherited conversation. There is no planning-agent id to preserve or pass.

The executor must stop without mutation if it cannot identify one clear recent plan and its approval. Otherwise it revalidates current state, stops approved work before removing its outputs, uses the tools that own each item, preserves unrelated content, refreshes anything derived from what changed, and verifies from fresh state. For shopping preferences, check ~/memory/shopping/PROFILE.md directly, edit or remove matching entries, and verify no staged, queued, running, or scheduled shopping-profile run can restore them. If the situation has materially changed or there is no safe way to clean up one place, make a revised plan instead of broadening the cleanup.

Do not send approved cleanup targets to recoverable trash. For an exact local file that should disappear entirely, use rm -- <exact-path> through exec; never use rm -r or another recursive shell deletion. Revalidate the path immediately before removal, never use a glob or a broad target, and edit mixed-content files instead of deleting them. Clean up directories through the product action that owns them; if there is no safe owning action, make a revised plan. If an owning product action archives a definition in trash as part of its cleanup, permanently remove an exact matching standalone-file tombstone. The plan must describe permanent removal as irreversible before the user approves it.

Before finishing, the executor stages what it removed from memory so the runtime can retract the matching memory claims and everything derived from them: it writes ~/workspace/memory/forget/pending.json as {"claims":[...],"citations":[...]}, listing the claim ids it saw in memory_explain or memory_search metadata and the exact MEMORY.md#L<line> or memory/<date>.md#L<line> locators it removed or rewrote. Ids and locators only, never the forgotten text; the file is written even when both lists are empty.

After the executor finishes successfully, Muse retracts the staged claims and refreshes memory search, and waits for both before relaying the result. If the refresh fails, report the cleanup as incomplete instead of claiming the information is no longer searchable. Perform the cleanup directly in this executor rather than delegating it to another subagent. If delegated work is still settling when the executor finishes, Muse reports the cleanup as incomplete so later changes cannot outrun the refresh. The executor should still verify the other affected places; it does not need to refresh memory search a second time.

If either tool fails, do not fall back to unplanned manual deletion or claim success. Explain the failure and make a new plan if the user still wants to continue.

Report honestly

Tell the user which categories were cleaned up, which reminders or other future activity were stopped, and what remains. Do not repeat the forgotten information.

Say "forgotten" only when fresh verification finds no active memory, derived copy, or future activity that can bring the information back. Outside services, shared or published items, logs, backups, or other retained copies may remain; name the everyday category and whether Muse can keep it out of active use.

Do not tell the user that their original messages may remain visible in the chat, and do not frame that as something Muse failed to erase. Visible conversation text is not a cleanup target or a completion blocker. Inspect it privately only to find and clean up memory, derived material, or future activity that used it.

The request does not authorize deleting outside email, calendar data, device records, shared publications, or another person's copy. Those actions need their own user approval.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Forget AI skill do?

Remove a personal fact, preference, relationship detail, topic, or prior event from Muse's active memory and stop existing copies or automations from bringing it back. Use for explicit requests such as 'forget that', 'don't remember this about me', or 'remove that from your memory'. Do not use when 'forget it' merely means cancel the current task.

Why use Forget on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/forget. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Forget?

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 Forget?

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

Is the Forget AI skill free?

It is published on GitHub by win4r. Check the repository for licensing terms. 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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