Memory Recall

OrganizationPopular

zilliztech

memory-recall

Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why did we do Y', or 'have I seen this before'. Also use when you see `[memsearch] Memory available` hints injected via SessionStart or UserPromptSubmit. Typical flow: search for 3-5 chunks, expand the most relevant, optionally deep-drill into original transcripts via the anchor format. Skip when the question is purely about current code state (use Read/Grep), ephemeral (today's task only), or the user has explicitly asked to ignore memory.

Overview

Publisher	zilliztech
Repository	`memsearch`
Skill name	`memory-recall`
Stars	2.6K
Forks	251
Bundled files	Instructions only
License	MIT
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 zilliztech on GitHub. Read the source before you install it.

Installation

Install the Memory Recall 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.
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/zilliztech/memsearch.git /tmp/memsearch
mkdir -p .claude/skills
cp -r /tmp/memsearch/plugins/openclaw/skills/memory-recall .claude/skills/memory-recall

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

Use it in TypingMind

Enable Memory Recall 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 Recall 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 Recall 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.

You have three memory tools for progressive recall. Start with search, go deeper only when needed.

Tools (use progressively)

1. memory_search — Start here

Semantic search across all past conversation memories.

Returns: chunk summaries with dates, topics, chunk_hash identifiers
Use for: "What did we discuss about X?", "Have I asked about Y before?"

2. memory_get — When search results aren't detailed enough

Expands a specific chunk_hash to show the full markdown section with surrounding context.

Input: chunk_hash from memory_search results
Returns: full section text, may include transcript anchors ()
Use for: "Show me the details", "I need more context on that result"

3. memory_transcript — When you need the exact original conversation

Parses the original session transcript to retrieve the raw dialogue.

Input: transcript_path from the anchor comment in memory_get results
Returns: formatted conversation with [User]/[Assistant] labels and tool calls
Use for: "What exactly did I say?", "Show me the original conversation"
If the anchor format is unfamiliar (e.g. rollout:, turn:, db: instead of transcript:), try reading the referenced file directly to explore its structure and locate the relevant conversation by the session or turn identifiers in the anchor.

Decision guide

User intent	Tools to use
Quick recall ("did we discuss X?")	memory_search only
Need details ("what was the solution?")	memory_search → memory_get
Need original dialogue ("show me the exact conversation")	memory_search → memory_get → memory_transcript

Tips

memory_search returns chunk_hash — pass it to memory_get for expansion
memory_get may reveal  anchors — pass the path to memory_transcript
If memory_search returns no results, try rephrasing with different keywords
Results are sorted by relevance (hybrid BM25 + vector search)

When unsure what to search

The SessionStart injection already shows you a heading-level preview of recent memory files — skim it first to spot concrete topics (dates, session numbers, task names). If that preview doesn't surface an obvious query, try broad keywords like overview, recent work, or a topic guess — hybrid BM25 + vector retrieval will surface chunks that share any of the terms, and you can iterate from there.

Frequently asked questions

What does the Memory Recall AI skill do?

Why use Memory Recall on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zilliztech/memsearch/tree/main/plugins/openclaw/skills/memory-recall. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Memory Recall?

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 Recall?

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

Is the Memory Recall AI skill free?

Yes. It is published on GitHub by zilliztech 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

Tools (use progressively)

1. memory_search — Start here

2. memory_get — When search results aren't detailed enough

3. memory_transcript — When you need the exact original conversation

Decision guide

Tips

When unsure what to search

Frequently asked questions

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