# Memory Tools

The [Memory Tree](/openhuman/features/obsidian-wiki/memory-tree.md) is OpenHuman's knowledge base. The memory tools are how the agent talks to it during a conversation.

## Tools in the family

| Tool     | What it does                                                                                              |
| -------- | --------------------------------------------------------------------------------------------------------- |
| `recall` | Search the Memory Tree by query - source-scoped, topic-scoped, or global. Returns chunks with provenance. |
| `store`  | Write a new memory the agent decided is worth keeping (a fact, a preference, a piece of context).         |
| `forget` | Remove a memory by ID - used when something is wrong, stale, or the user explicitly asks to forget it.    |

There is also a tree-aware retrieval surface (drill down a topic, fetch the global digest for a day) - the agent picks the right one based on the question.

## Why these are tools, not implicit context

The Memory Tree is too big to dump into every conversation. The tools let the model *ask* - "what do I know about Alice?", "what happened yesterday?", "remind me of last week's Stripe webhook" - and the retrieval layer returns just the relevant chunks, with provenance back to the source file in your Obsidian vault.

## See also

* [Memory Tree](/openhuman/features/obsidian-wiki/memory-tree.md) - what these tools read from and write to.
* [Auto-fetch](/openhuman/features/obsidian-wiki/auto-fetch.md) - how the tree gets populated in the first place.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://tinyhumans.gitbook.io/openhuman/features/native-tools/memory-tools.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.