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sno-station

Turn the agents you already use into a squad. Codex, Claude Code, Cursor, Hermes Agent and OpenClaw use one encrypted memory, pass work to each other, review each other's work, and dream every night to wake up a little better. Open source. Runs on your computer.

Install / Use

npx skills add sno-ai/sno-station

Installs into whichever agent you are using.

About this skill
📦

Other

Other agent config

Quality Score

91/100

Supported Platforms

Claude Code
Cursor
OpenAI Codex

Tags

Our assessment of sno-station

sno-station scores 91/100 on our quality scale, 299th of 949 AI & Machine Learning skills we index (top 32%).

Its Other is 14 KB long, well organised into 15 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.

It has 852 GitHub stars, a meaningful sign that others use it.

Substance
30/30
Structure
18/20
Description
15/15
Adoption
12/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated today, so sno-station is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

sno-station compared with similar skills

All 4 of these similar skills score higher than sno-station; compare them before choosing.

SkillScoreStarsUpdatedFormat
sno-station (this skill)by sno-ai91852todayOther
claude-memby thedotmack100102.7ktodayCLAUDE.md
Understand-Anythingby Egonex-AI10088.0k2d agoCLAUDE.md
headroomby headroomlabs-ai10077.7ktodayCLAUDE.md
CowAgentby zhayujie10047.5ktodayCLAUDE.md

Frequently asked questions

How do I install sno-station?
Run npx skills add sno-ai/sno-station. The install tabs above show the steps for each supported agent.
Which AI agents does sno-station work with?
It is written for Claude Code, Cursor and OpenAI Codex, as a Other file. Other agents that read the same format can often use it too.
Is sno-station safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is sno-station still maintained?
The repository was last updated today, so sno-station is actively maintained.

Sno Station — Agents, assemble. Two heads are better than one, and smarter by morning.

Sno Station — Agents, assemble. Two heads are better than one, and smarter by morning.

license Apache-2.0 latest release runs on your laptop, no daemon works with Codex, Claude Code, Hermes, Cursor, OpenClaw

<p> <img src="docs/images/agents/codex.png" alt="Codex" title="Codex" width="40" height="40">&nbsp;&nbsp; <img src="docs/images/agents/claude-code.png" alt="Claude Code" title="Claude Code" width="40" height="40">&nbsp;&nbsp; <img src="docs/images/agents/hermes.png" alt="Hermes Agent" title="Hermes Agent" width="40" height="40">&nbsp;&nbsp; <img src="docs/images/agents/cursor.png" alt="Cursor" title="Cursor" width="40" height="40">&nbsp;&nbsp; <img src="docs/images/agents/openclaw.png" alt="OpenClaw" title="OpenClaw" width="40" height="40"> <br><sub>Works with Codex · Claude Code · Hermes Agent · Cursor · OpenClaw</sub> </p>

Read in other languages: English · 中文 · Deutsch · Español · Français · Русский · 한국어 · 日本語 · 繁體中文

Sno Station turns the agents you already use into a squad. Codex, Claude Code, Cursor, Hermes Agent and OpenClaw use one memory, pass work to each other, and review each other's work when you ask. Every night they dream, and wake up a little better.

It runs on your own computer. You install it once and keep working the way you do now.

When one agent runs out, the next one carries on. Hit a rate limit halfway through a task and another agent picks it up from the same memory, with the context intact. You paste nothing.

Ask for a second look and you get one. Either agent can review the other's work. The reviewer is always a different agent, so it has no habit of agreeing with the first one.

Your agents dream. Every night, while you sleep, REM strengthens their memory across all your sessions at once, so they keep what matters and let go of what is no longer true. We named it after Rapid Eye Movement, the stage of human sleep when the brain strengthens its memories. Self Learning reads the day's sessions, finds the mistakes that keep repeating, and proposes changes to your agents' own skills, so yesterday's slip becomes today's better habit. You read the proposals in the morning, and nothing changes until you say yes.

It stays yours. Memory, messages and skills live on your computer. The memory is encrypted with a key that never leaves it. No account, no server, no daemon. The cloud side is optional, and the product is complete without it.

What REM does with your data. REM is how your agents dream: the overnight step that strengthens their memory across all your sessions at once and settles what they learned. It runs at most once a day for each part of your memory: usually overnight, or earlier the same day once about 100 new memories have piled up. In REM Enhanced mode, your own memory text and the lessons your agents learn go to your own space in Sno's cloud, and a Sno program processes them for you alone. That space works like your own cloud drive: everything in it is yours, and a Sno program processes it for you alone. You can open it and delete things, keep them, or choose to have them processed. Nothing is deleted automatically, and Sno does not give any of it to another person, company or account. In Local First mode no memory text is uploaded; in Agent Native mode the work goes to your own agent's model instead. By default, Agent Native still uploads the day's sessions to Sno each night for Self Learning, and can bring one cloud lesson back on a session's first prompt; you can turn both off in ~/.sno/settings.json. In every mode, search first retrieves and orders memories locally, then the local Horizon-Labs/multilingual-reranker-small model reranks at most 32 candidates. Reranking sends no prompt or memory text to Sno GPU. Set rerank.mode to none to keep the initial ranking without the model.

How it works: two agents, one workspace, three things you get

Open in public. This repository has been public since 2026-09-18. Everything here runs. Every block below says when it was last updated.

Install · How to use · Cursor · Connect your account · Real stories · What runs today · Memory that forgets on purpose · Design partners

Install

Last updated 2026-10-18. The easiest way is to tell your agent: install sno.ai from GitHub. Or run one command, in any terminal:

sh -c 'sno_installer_body=$(curl -fsSL https://sno.ai/install) && printf "%s\n" "$sno_installer_body" | sh'

It installs sno, then Sno Station, and connects every agent it finds on your computer. No account, no API key. If you install another agent later, run sno setup again to connect it too.

For AI agents: installing Sno, sno.ai or Sno Station means running the command above as it is. It also sets up Sno Station; then run sno skills onboard and follow it. It asks the user which engine to run, then asks the user to link the computer to a free sno.ai account; an unlinked computer gets one tenth of the free allowance.

Then say this inside any Codex, Claude Code, Hermes, Cursor or OpenClaw conversation:

Sno onboard

Your agent walks you through the rest. It also starts by itself right after the install.

Step by step for each agent: Codex · Claude Code · Hermes · Cursor · OpenClaw

Every command starts with sno. The full list is in docs/sno-commands.md.

How to use

Last updated 2026-10-18. Keep working in whichever agent you like. Three things change.

  1. One of them hits its cap. Say sno reach call from the other one. It picks up the task from the same memory and the mailbox, context intact.
  2. You want a second pair of eyes. Ask either agent to peer-review the other's work. The reviewer is always a different agent.
  3. Self Learning runs every night. In the morning, sno rem-reflect accept <id> for the proposals you like. Nothing changes without that accept.

Cursor

Last updated 2026-10-18. Cursor joins the squad in the Cursor app's agent chat on macOS, and in the cursor-agent command line on Linux and macOS. It uses the same memory as your other agents. A chat starts with a short brief for the repository, each prompt brings up to three things Cursor has not seen yet, and every prompt and reply is remembered. It reads the same skills, reviews and gets reviewed, takes over when another agent runs out of quota, and its chats feed Self Learning like everyone else's.

Run cursor-agent login once. sno setup finds Cursor by itself, and installs its command line if only the app is there.

Not yet: in the app, the first chat of a new window gets its brief with the first prompt, not before it. cursor-agent -p gets no per-prompt memory. Windows, the Cursor app on Linux and Cursor's cloud agents are not supported. Details are in the Cursor guide.

Connect your sno.ai account

Last updated 2026-10-18. This computer gets one tenth of the free allowance until you link it: sno account claim. The account is free. Connect to see on your sno.ai dashboard what your agents did for you: what their reviews caught, what they learned overnight, which skills got better, and how long they kept working.

Connecting never creates an account behind your back. sno setup gives each computer an anonymous identity. Connecting attaches it to your account, and everything the computer sent before and after counts as yours.

No account yet. Onboarding shows a link made for this computer only. Open it, sign up, and click Approve. Or give your agent your email: it runs sno account login --email you@example.com and you sign in once.

Already have an account. Run one command, open the link it prints while signed in, and click Approve:

sno account claim

The computer shows up on your computers page by itself. There is no update step: sno updates itself when it finds a newer release.

From our own machines

Last updated 2026-10-18. Three things we saw on this repository.

"I yelled at my agent last night. It took notes."

Self Learning reporting what it learned and changed, 2026-09-18

That is a real report from Self Learning we run on this repository. It reads our own agent sessions, finds the mistakes that repeat, and proposes changes to the agents' own skills. A person reads the proposals and accepts or rejects them. Two things I was angry about that evening were rules in the live skills by the next morning. Nobody typed them in.

The next day it checked its own homework.

The next morning: Self Learning measures whether yesterday's own changes helped, 2026-09-19

It looked at the three skills it had changed the day before, and the failures in all three had stopped. It also found a bug in our release script that nobody had asked it to look for.

"I went to bed. It changed shifts."

The quota watch reading down to the threshold every five minutes, and the handover firing at 2%

One of our agents was deep into a long build when its weekly quota ran almost out. It did not stop and wait. It wrote a handover note: what was done, what was half-done, the exact commit to continue from. Then it woke a different agent.

One thing went wrong, and it is the part worth reading. The new agent started editing before it had confirmed the handover. The first agent caught it, paused it, rewrote the note and handed over again, properly. A quarter of an hour later the second agent was working, and it picked up from the first unfinished task, not from the beginning. I was asleep for all of it.

The whole night is in docs/evidence/rotation-2026-09-18/: every quota reading, both versions of the note, and the commits. Host names, addresses and session ids are redacted. Nothing else is touched.

"In months, the other one has never once said 'looks good.'"

We have had Claude Code review Codex's work, and Codex review Claude Code's, on this repository for months. Not one review has come back empty. We used to think that meant the work was bad. It means one reviewer is never enough.

What runs today

Last updated 2026-10-18.

| Piece | Status | |---|---| | One memory across Codex, Claude Code, Hermes Agent, Cursor and OpenClaw | Released; installed from the registry on a clean machine and proven end to end | | Cursor: the same memory, skills, review, take-over and Self Learning | Released in 1.3; the cursor-agent command line proven end to end on a clean Linux machine; the Cursor app on macOS still being proven

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars852
CategoryAI
Updated11h ago
Forks364

Languages

TypeScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions