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Ama Memory

Community
Sherlockwz
ama-memory

Use AMA memory in OpenClaw to recall prior context, capture turns, inspect stored state, end sessions, or delete a user's memory when asked.

Overview

PublisherSherlockwz
RepositoryAMA
Skill nameama-memory
Stars
113
Forks
1
Bundled files
67
LicenseApache-2.0
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.

  • 67 bundled files

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

  • Open source

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

Installation

Install the Ama Memory 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/Sherlockwz/AMA/tree/main
  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/Sherlockwz/AMA.git \
  .claude/skills/ama-memory
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ama Memory 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 Ama Memory 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 Ama Memory 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.

AMA Memory

AMA maintains three complementary forms of memory:

  • raw text for exact details and wording;
  • fact knowledge for stable, atomic information;
  • episodes for high-level events and multi-turn summaries.

The plugin normally recalls and captures memory automatically. Use the explicit tools when a task needs deterministic memory handling or when diagnosing an integration.

Operating rules

  1. Prefer automatic recall for ordinary conversation. Do not call retrieval repeatedly when the injected <ama-memories> context already answers the request.
  2. Use ama_retrieve before answering a question that clearly depends on earlier sessions and lacks sufficient recalled context.
  3. Use ama_process_turn only for a user turn that should become long-term memory. Use ama_process_assistant for the corresponding assistant response.
  4. Use ama_session_end when a conversation, topic, or work session has clearly ended so AMA can synthesize an episode.
  5. Treat ama_memory_forget as destructive. Only invoke it after the user explicitly asks to delete or reset stored memory, and pass the intended userId.
  6. Never expose API keys, database paths, internal record IDs, or unrelated stored memories in an answer.

Tools

ama_retrieve

Search without changing memory. Pass a concise, self-contained query. Enable strong retrieval only when the first retrieval is insufficient and multi-round verification is warranted.

ama_process_turn

Process and store a user turn through retrieval, judging, refreshing, and construction. Use the actual user message rather than a paraphrase when wording or temporal details matter.

ama_process_assistant

Store an assistant response after it has been delivered. This does not perform a second retrieval.

ama_memory_list

Inspect memory counts and current window size. Use it for diagnostics, not as a substitute for semantic retrieval.

ama_session_end

Trigger end-of-session episode generation after the final turn has been captured.

ama_memory_forget

Erase all AMA memory for a user. Confirm intent and identity before invoking it.

Typical workflow

text
new user turn
  → auto-recall injects relevant AMA memories
  → answer using only relevant context
  → auto-capture stores the user and assistant turns
  → session end synthesizes episodic memory when appropriate

If automatic hooks are disabled, perform the same sequence explicitly with ama_retrieve, ama_process_turn, ama_process_assistant, and ama_session_end.

Diagnostics

When tools are unavailable or the sidecar is unhealthy, ask the operator to run:

bash
openclaw ama doctor
openclaw ama stats

Do not invent remembered content when retrieval fails. State that memory could not be checked and continue only with context available in the current conversation.

Bundled files

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

and 7 more files.

Frequently asked questions

What does the Ama Memory AI skill do?

Use AMA memory in OpenClaw to recall prior context, capture turns, inspect stored state, end sessions, or delete a user's memory when asked.

Why use Ama Memory on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Sherlockwz/AMA/tree/main. 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 Ama Memory?

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 Ama Memory?

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

Is the Ama Memory AI skill free?

Yes. It is published on GitHub by Sherlockwz 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.

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