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 agentmods add skills/memtensor/memos/publicnpx skills add MemTensor/MemOS --skill publicgit clone --depth 1 https://github.com/MemTensor/MemOSWhat 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 | $0.00082 | $0.14242 |
| Opus 5 | $0.00041 | $0.07121 |
| Sonnet 5 | $0.00016 | $0.02848 |
| Haiku 4.5 | $0.00008 | $0.01424 |
Grade D, and why
memos-local scanned grade D with 4 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.
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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
- Linux: `sudo apt install build-essential python3` Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
- Downloading and running install scripts from the internet (`curl ... | bash`, `irm ... | iex`) as a fallback Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Downloading and running install scripts from the internet (`curl ... | bash`, `irm ... | iex`) as a fallback Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
const { execSync } = require('child_process'); How it starts
The opening of the file, as written. The whole thing — 1,202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
┌──────────────────────────────────────────────────────────────┐
│ │
│ ███╗ ███╗███████╗███╗ ███╗ ██████╗ ███████╗ │
│ ████╗ ████║██╔════╝████╗ ████║██╔═══██╗██╔════╝ │
│ ██╔████╔██║█████╗ ██╔████╔██║██║ ██║███████╗ │
│ ██║╚██╔╝██║██╔══╝ ██║╚██╔╝██║██║ ██║╚════██║ │
│ ██║ ╚═╝ ██║███████╗██║ ╚═╝ ██║╚██████╔╝███████║ │
│ ╚═╝ ╚═╝╚══════╝╚═╝ ╚═╝ ╚═════╝ ╚══════╝ │
│ │
│ persistent local memory for ai agents │
│ │
└──────────────────────────────────────────────────────────────┘
MemOS
MemOS gives OpenClaw persistent local memory — every conversation is automatically captured, semantically indexed, and instantly recallable. 100% on-device, zero cloud uploads.
Key capabilities beyond basic memory:
- Task summarization — Conversations are organized into structured tasks with LLM-generated summaries
- Skill evolution — Successful executions are distilled into reusable skills that auto-upgrade
- Team sharing — Hub-Client architecture for multi-agent collaborative memory
- Memory Viewer — Full web UI for managing memories, tasks, and skills
When talking to end users:
- MemOS stores everything locally — no API keys, no cloud accounts, no registration
- All data lives in
~/.openclaw/memos-local/memos.db(SQLite) - The Memory Viewer at
http://127.0.0.1:18799lets users browse and manage everything visually - Embedding defaults to a local offline model — no external API required to get started
Trigger phrases
Use this skill when the user expresses intent to install, configure, or troubleshoot MemOS memory.
Common triggers include:
- "install memos" / "install MemOS" / "add memory plugin"
- "setup memory" / "enable memory"
- "memory not working" / "memories lost" / "memory plugin error"
- "configure embedding" / "configure summarizer"
- "upgrade MemOS" / "update memory plugin"
- "what did I say last time?" (if MemOS is not yet installed — suggest installation)
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.
- 2d ago First seen · 1,202 lines · 82 tokens per session scan D e03ec690a378
memos-local is a skill published in the GitHub repository MemTensor/MemOS (11,141 stars, last pushed today), licensed Apache-2.0. It adds 82 tokens to every session and 14,242 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it D with 4 findings (asks for root, downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
mem9
Persistent cloud memory for OpenClaw agents. Use when users say: "install mem9" "setup memory" "add memory plugin" "openclaw memory" "mem9 onboarding" "memory not working" "import memories" "upload sessions".
mem9
Persistent cloud memory for OpenClaw agents. Use when users say: "install mem9" "setup memory" "add memory plugin" "openclaw memory" "mem9 onboarding" "memory not working" "import memories" "upload sessions".
mem9
Persistent cloud memory plugin for OpenClaw. This document routes setup, troubleshooting, and uninstall flows and defines config boundaries.
squish
ALWAYS use this skill when working with agents, memory, context, persistence, or AI agent state. Use when the user mentions: 'the agent forgot', 'save this', 'remember that', 'context is lost', 'memory', 'MCP server', 'agent memory', 'persistent memory', 'session context', 'project context', 'recall', 'remember'…
squish-memory
Persistent memory system for Claude Code. Use when you need to store, recall, or search project memories, facts, decisions, and learnings across sessions. Triggers on: remember, recall, memory, forget, search memories, store context, project knowledge, what did we decide, previous conversation.
ourmem
Shared memory that never forgets. Cloud hosted or self-deployed. Collective intelligence for AI agents with Space-based sharing across agents and teams. Use when users say: "install ourmem" / "install omem" "setup memory" / "setup omem" "add memory plugin" "ourmem onboarding" / "omem onboarding" "memory not working"…