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.
npx skills add mnemon-dev/mnemon --skill openclawgit clone --depth 1 https://github.com/mnemon-dev/mnemonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mnemon-dev/mnemon/openclaw)<a href="https://agentmods.dev/skills/mnemon-dev/mnemon/openclaw"><img src="https://agentmods.dev/badge/skills/mnemon-dev/mnemon/openclaw/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mnemon-dev/mnemon/openclaw"><img src="https://agentmods.dev/badge/skills/mnemon-dev/mnemon/openclaw.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 42 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00025 | $0.01416 |
| Opus 5.5 | $0.00010 | $0.00566 |
| Sonnet 5.5 | $0.00005 | $0.00283 |
| Haiku 4.5 | $0.00003 | $0.00142 |
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 1mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mnemon
Install & Configure
1. Install the binary
npm (macOS / Linux / Windows, Node.js 22+):
npm install --global @mnemon-dev/mnemon
Upgrade an npm-managed installation with:
mnemon update
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
- Remember:
mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent- Only exact content repeats are skipped; distinct content is stored and diff suggestions are advisory.
- To retire a superseded memory, store and verify the new fact, then explicitly run
mnemon forget <old-id>. - Output includes
action(added/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_signalis regex-based and prone to false positives — only link if the memories are truly causally related. - Review
semantic_candidates: are these memories meaningfully related? Highsimilarityalone 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>']
- Review
- Recall:
mnemon recall "<query>" --limit 10
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.
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.
- 1mo ago Changed · +18 lines 4ad2b7d9e903
- 1mo ago Changed · -5 lines 4f831f2ae827
- 1mo ago First seen · 139 lines · 25 tokens per session scan A 73cf7f0f3eaa
mnemon is a skill published in the GitHub repository mnemon-dev/mnemon (634 stars, last pushed 5d ago), licensed Apache-2.0. It adds 25 tokens to every session and 1,416 once invoked, about $0.0001 per session on Opus 5.5. 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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