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Mnemon

Persistent memory CLI for LLM agents.

Rating: 4.5 (276 reviews)
Downloads: 5,903 downloads
Version: 1.0.0

Overview

Persistent memory CLI for LLM agents.

Complete Documentation

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mnemon

Install & Configure

1. Install the binary

Homebrew (macOS / Linux):

bash

brew install mnemon-dev/tap/mnemon

Go install:

bash

go install github.com/mnemon-dev/mnemon@latest

2. Set up OpenClaw integration

bash

mnemon setup --target openclaw --yes

This single command deploys all components:

Skill → ~/.openclaw/skills/mnemon/SKILL.md
Hook → ~/.openclaw/hooks/mnemon-prime/ (agent:bootstrap — injects behavioral guide)
Plugin → ~/.openclaw/extensions/mnemon/ (remind, nudge, compact hooks)
Prompts → ~/.mnemon/prompt/ (guide.md, skill.md)

Restart the OpenClaw gateway to activate.

3. Customize (optional)

Edit ~/.mnemon/prompt/guide.md to tune recall/remember behavior.

Plugin hooks are configured in ~/.openclaw/openclaw.json:

json

{
  "plugins": {
    "entries": {
      "mnemon": {
        "enabled": true,
        "config": {
          "remind": true,
          "nudge": true,
          "compact": false
        }
      }
    }
  }
}

Hook	Default	Description
remind	on	Recall relevant memories + remind agent on each message
nudge	on	Suggest remember sub-agent after each reply
compact	off	Save key insights before context compaction

4. Uninstall

bash

mnemon setup --eject --target openclaw --yes

Workflow

Remember: mnemon remember "" --cat --imp <1-5> --entities "e1,e2" --source agent
Diff is built-in: duplicates skipped, conflicts auto-replaced.
Output includes action (added/updated/skipped), semantic_candidates, causal_candidates.
Link (evaluate candidates from step 1 — use judgment, not mechanical rules):
Review causal_candidates: does a genuine cause-effect relationship exist? causal_signal is regex-based and prone to false positives — only link if the memories are truly causally related.
Review semantic_candidates: are these memories meaningfully related? High similarity alone is not sufficient — skip candidates that share keywords but discuss unrelated topics.
Syntax: mnemon link --type --weight <0-1> [--meta '']
Recall: mnemon recall "" --limit 10

Commands

bash

mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
mnemon link <id1> <id2> --type <type> --weight <0-1> [--meta '<json>']
mnemon recall "<query>" --limit 10
mnemon search "<query>" --limit 10
mnemon forget <id>
mnemon related <id> --edge causal
mnemon gc --threshold 0.4
mnemon gc --keep <id>
mnemon status
mnemon log
mnemon store list
mnemon store create <name>
mnemon store set <name>
mnemon store remove <name>

Guardrails

Use the exec tool to run mnemon commands.
Do not store secrets, passwords, or tokens.
Categories: preference · decision · insight · fact · context
Edge types: temporal · semantic · causal · entity
Max 8,000 chars per insight.

Installation

Terminal bash


openclaw install mnemon

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💻Code Examples

mnemon setup --target openclaw --yes

mnemon-setup---target-openclaw---yes.txt

This single command deploys all components:
- **Skill** → `~/.openclaw/skills/mnemon/SKILL.md`
- **Hook** → `~/.openclaw/hooks/mnemon-prime/` (agent:bootstrap — injects behavioral guide)
- **Plugin** → `~/.openclaw/extensions/mnemon/` (remind, nudge, compact hooks)
- **Prompts** → `~/.mnemon/prompt/` (guide.md, skill.md)

Restart the OpenClaw gateway to activate.

### 3. Customize (optional)

Edit `~/.mnemon/prompt/guide.md` to tune recall/remember behavior.

Plugin hooks are configured in `~/.openclaw/openclaw.json`:

}

.txt

| Hook | Default | Description |
|------|---------|-------------|
| `remind` | on | Recall relevant memories + remind agent on each message |
| `nudge` | on | Suggest remember sub-agent after each reply |
| `compact` | off | Save key insights before context compaction |

### 4. Uninstall

mnemon setup --eject --target openclaw --yes

mnemon-setup---eject---target-openclaw---yes.txt

## Workflow

1. **Remember**: `mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent`
   - Diff is built-in: duplicates skipped, conflicts auto-replaced.
   - Output includes `action` (added/updated/skipped), `semantic_candidates`, `causal_candidates`.
2. **Link** (evaluate candidates from step 1 — use judgment, not mechanical rules):
   - Review `causal_candidates`: does a genuine cause-effect relationship exist? `causal_signal` is regex-based and prone to false positives — only link if the memories are truly causally related.
   - Review `semantic_candidates`: are these memories meaningfully related? High `similarity` alone is not sufficient — skip candidates that share keywords but discuss unrelated topics.
   - Syntax: `mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1> [--meta '<json>']`
3. **Recall**: `mnemon recall "<query>" --limit 10`

## Commands

example.json

{
  "plugins": {
    "entries": {
      "mnemon": {
        "enabled": true,
        "config": {
          "remind": true,
          "nudge": true,
          "compact": false
        }
      }
    }
  }
}

example.sh

mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
mnemon link <id1> <id2> --type <type> --weight <0-1> [--meta '<json>']
mnemon recall "<query>" --limit 10
mnemon search "<query>" --limit 10
mnemon forget <id>
mnemon related <id> --edge causal
mnemon gc --threshold 0.4
mnemon gc --keep <id>
mnemon status
mnemon log
mnemon store list
mnemon store create <name>
mnemon store set <name>
mnemon store remove <name>