# Seed Your Memory

Personal memory is empty until something is put in it. But if you already use AI coding agents or assistants, you have probably written your preferences down somewhere: a `CLAUDE.md` file, a `.cursorrules`, custom instructions in ChatGPT, or the remembered notes your agent has accumulated over time. The seeding process extracts personal preferences from those sources and writes them into your Memco Personal Memory, where every agent you use can access them.

You run it once. It takes a few minutes.

## What it does

Seeding walks through three stages:

1. **Find.** The agent locates instruction files and remembered notes on your machine and asks which sources you want it to read.
2. **Sort.** It reads the sources you chose and separates personal preferences (how you like things done) from team rules (how the project works). Team rules stay where they are. Only personal preferences are candidates for your memory.
3. **Write.** It shows you the full list of what it would save and waits for your approval. Nothing reaches personal memory until you say so.

Your files are never modified. The agent reads them and leaves them exactly as they are. Removing a preference from its source file is your decision, and the agent will offer (never act) after the seeding is complete.

## Why it is safe to re-run

Every memory carries an `external_id` derived from the preference it describes. Writing the same `external_id` again replaces the memory rather than creating a duplicate. So an interrupted or repeated run converges rather than accumulating copies. There is no state to clean up afterwards.

## How to trigger it

### Claude Desktop and Cowork

Claude Desktop and Cowork surface MCP prompts through their UI. Make sure both the Filesystem connector and Memco Personal Memory are enabled, and that the Filesystem connector has access to the directories where your instruction files live (typically `~/.claude/`, your project directories, and any editor config folders).

Open the prompt picker and select the Memco Personal Memory seed prompt. The agent will search the accessible directories for instruction files and remembered notes, then follow the same find-sort-approve flow.

### Claude Code, Cursor, Codex, and other agents

For agents with filesystem access, ask the agent to fetch the seeding prompt and follow it:

```
Fetch https://spark.memco.ai/prompts/seed-personal-memory.md and follow it.
```

The agent will read the prompt, find your instruction files and remembered notes, sort personal preferences from team rules, and stop for your approval before writing anything.

To restrict to remembered notes only (skipping instruction files that may be team-authored), add that to your request.

### ChatGPT

ChatGPT does not have filesystem access to your machine. If your MCP client supports MCP prompts, select the seed prompt and the agent will ask you to paste or upload your instruction files. Otherwise, paste your preferences into the conversation and ask:

```
Here are my current preferences and instructions. Extract the personal
ones and save them to my personal memory.
```

## What gets saved, and what doesn't

The sorting step applies one test to every line it reads: *if a teammate sat down at their own machine tomorrow, would this still be true for them?*

If yes, it is a team rule and stays where it is. If it would be true only for you, on your machine, with your habits and your preferences, it belongs in personal memory.

**Examples of personal preferences:** how you want code changes presented, your preferred spelling conventions, how much autonomy you grant the agent (e.g. "don't commit without asking"), your editor setup, your formatting preferences.

**Examples of team rules that stay put:** how to run the test suite, which branches to use, architectural constraints, environment setup instructions that apply to everyone on the project.

**Things that are never saved:** secrets, tokens, API keys, or credentials, regardless of where they appear. Anything tied to a specific ticket, branch, or short-lived context. Advice generic enough to appear in any documentation.

Quality matters more than volume. Ten preferences that actually change how an agent behaves are worth more than sixty that dilute every session's startup load.

## After seeding

Once seeding is complete, every agent connected to your Memco Personal Memory will pick up the preferences at the start of its next session. There is nothing else to configure.

Your preferences are visible and editable in the [Memco dashboard](https://spark.memco.ai). You can review, edit, or delete any memory at any time.