SkillHub

mnemon

v0.1.2

Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.

Sourced from ClawHub, Authored by Grivn

Installation

Please help me install the skill `mnemon` from SkillHub official store. npx skills add Grivn/mnemon

mnemon

Install & Configure

1. Install the binary

Homebrew (macOS / Linux):

brew install mnemon-dev/tap/mnemon

Go install:

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

2. Set up OpenClaw integration

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:

{
  "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

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

Workflow

  1. Remember: mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent
  2. Diff is built-in: duplicates skipped, conflicts auto-replaced.
  3. Output includes action (added/updated/skipped), semantic_candidates, causal_candidates.
  4. Link (evaluate candidates from step 1 — use judgment, not mechanical rules):
  5. 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.
  6. Review semantic_candidates: are these memories meaningfully related? High similarity alone is not sufficient — skip candidates that share keywords but discuss unrelated topics.
  7. Syntax: mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1> [--meta '<json>']
  8. Recall: mnemon recall "<query>" --limit 10

Commands

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.