mnemon

A persistent memory integration for OpenClaw, an agent platform. It installs memory instructions, event hooks, and a plugin so the agent can recall relevant memories and receive prompts to save new ones.

In plain words
What is it for?
Use it to install the OpenClaw integration, configure memory reminders and suggestions, and control whether memory cleanup runs automatically.
Why use it?
It helps OpenClaw retain context across messages and conversations, reducing repeated explanations and forgotten information.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/mnemon-dev/mnemon/openclaw
Any agent
npx skills add mnemon-dev/mnemon --skill openclaw
Clone the repo
git clone --depth 1 https://github.com/mnemon-dev/mnemon

Made for: Claude Code, Codex.

Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,195 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00025 $0.01195
Opus 5 $0.00013 $0.00598
Sonnet 5 $0.00005 $0.00239
Haiku 4.5 $0.00003 $0.00120

Measured 2d ago against content hash 73cf7f0f3eaa, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mnemon scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (hooks/mnemon-prime/handler.js, plugin/index.js), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

internal/memory/setup/assets/openclaw/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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
    • 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

Read the full file on GitHub · 139 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 139 lines · 25 tokens per session scan A 73cf7f0f3eaa

Subscribe to this mod's changes

mnemon is a skill published in the GitHub repository mnemon-dev/mnemon (540 stars, last pushed 9d ago), licensed Apache-2.0. It adds 25 tokens to every session and 1,195 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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