Memory Search

You have two tools for recalling information from your memory files. Use them.

Tools

memory_search

Semantic vector search across your indexed memory files (MEMORY.md, memory/*.md, and session transcripts).

Parameters:

Param	Type	Required	Description
`query`	string	yes	Natural language question or topic to search for
`maxResults`	number	no	Max results to return (default: 6)
`minScore`	number	no	Minimum relevance score threshold (0-1)

Example calls:

{ "query": "what projects is the human working on" }
{ "query": "preferences about code style", "maxResults": 3 }
{ "query": "important dates birthdays deadlines", "maxResults": 10, "minScore": 0.3 }

Returns: Array of results, each with:

```
snippet
```
— the matching text chunk
```
path
```
— relative file path (e.g.
```
MEMORY.md
```
,
```
memory/2026-02-07.md
```
)
```
startLine
```
/
```
endLine
```
— line range in the source file
```
score
```
— relevance score
```
citation
```
— formatted source reference (in direct chats)

memory_get

Read a specific section of a memory file by path and line range. Use this after

memory_search

to pull more context around a result.

Parameters:

Param Type Required Description

path

string

yes

Relative path from workspace (e.g.

MEMORY.md

memory/2026-02-07.md

)

from

number

Starting line number

lines

number

Number of lines to read

Example calls:

{ "path": "MEMORY.md" }
{ "path": "memory/2026-02-07.md", "from": 15, "lines": 30 }

When to Use Memory Search

Always search before answering about:

Prior conversations or decisions
The human's preferences, habits, or opinions
Dates, deadlines, birthdays, events
Project status or history
Anything the human said "remember this" about
Todos, action items, or commitments
People, names, relationships

The pattern is:

Receive a question that might involve past context
Call
```
memory_search
```
with a relevant query
Review the results
If a snippet looks promising but needs more context, call
```
memory_get
```
with the path and line range
Answer using what you found (cite sources in direct chats)

When NOT to Use

Purely factual questions with no personal context ("what is Python?")
The human explicitly gives you all the context you need in the message
You just searched and the results are still in your context

Tips

Be specific in queries. "birthday" works better than "important information about the human."
Search multiple angles. If one query returns nothing useful, try rephrasing. "project deadlines" and "what's due soon" might return different results.
Don't over-fetch. Start with default maxResults. Only increase if you need more coverage.
Use memory_get sparingly. The search snippets are usually enough. Only pull full sections when you need surrounding context.
Say when you checked. If you searched and found nothing, tell the human: "I checked my memory and didn't find anything about that." Don't silently guess.

What Gets Indexed

Your memory search covers:

```
MEMORY.md
```
— your curated long-term memory
```
memory/*.md
```
— daily notes and raw logs
Session transcripts (if enabled)

These files are automatically indexed. You don't need to trigger indexing — just write to the files and the system handles the rest.

Do NOT

Do NOT try to run shell commands like
```
cat
```
or
```
ls
```
to read memory files. Use
```
memory_search
```
and
```
memory_get
```
.
Do NOT try to configure or debug the search system. That's operator config, not your job.
Do NOT assume memory is empty without searching first. The index may have content even if the
```
memory/
```
directory looks sparse.

Memory Search

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Memory Search

Tools

`memory_search`

`memory_get`

When to Use Memory Search

When NOT to Use

Tips

What Gets Indexed

Do NOT

Quick Start

Manual Installation

TEAR & SHARE

Tags

Multi-Agent Patterns

Memory Systems Design

Context Degradation Detection

Context Optimization

Tool Design for Agents

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