Sno Station Skills
Install a real engineering team's working habits into Claude Code and Codex: cross-vendor review, quota handoff, morning briefs and nightly retrospectives.
- Source repo
- sno-ai/sno-station-skills
- Stars
- ★ 861
- Last updated
- today
- License
- Apache-2.0
- Primary language
- Shell
- FA score
- 42/100 · Major gaps
At a glance
- Works with
- Portable with changesCodex · Claude CodeClaude.ai · OpenAI API (Partial support)
- You'll need
- Typical use
- A developer finished a change and wants a reviewer from a different model vendor to read it cold and report what would break in real use.
- Main limitation
- The full cross-vendor workflow depends on having both Claude Code and Codex installed and logged in.
- Source review
- 42/100 · Major gaps 1 safety controls not found
What does this agent do, and when should you use it?
Sno Station Skills is the skill set that Sno Station installs into Claude Code and Codex. The badges and body describe 37 skills shipped as 28 units, grouped into six team capabilities (J peer review, M build, S communication, H reporting, T delegation, R retrospective). Every SKILL.md opens with a requires block naming the Sno Station programs it calls (reach, heartbeat, subscription-quota-check, report-time) and the harness slots it needs, so sno setup can install it fully, in reduced form, or skip it per agent. The core pattern is Dual Brain: one agent does the work, an agent from the other vendor reviews it in a fresh session with none of the author's conversation, and the author fixes findings until the review comes back clean. Before a long run you can arm rotate-agent, which watches remaining quota and hands the task to the other vendor's agent with a verified handover brief and the exact commit to continue from. Work counts as done only when a written list of success checks is answered by real runs. Skills install via sno setup or the Claude Code and Codex plugin marketplaces, and the repository is Apache-2.0.
Skills are Markdown instructions plus scripts that the agent executes. peer-review launches the other vendor's CLI in a new session against a diff, plan or document and drives a fix loop; less-is-more climbs a ladder (needed at all, already in the repo, standard library, platform, installed dependency) before writing code and then trims its own diff; codex-coder keeps the plan in Claude Code and runs codex exec for the coding, killing and restarting a run that has written nothing for 15 minutes; rotate-agent uses heartbeat to read subscription-quota-check every few minutes, then triggers handoff to write a brief and wake the other agent; deliver answers each charter success check with a recorded run tracked by sno deliver-proof; rem-reflect reads the day's local Claude Code and Codex sessions and proposes lessons and skill changes that only apply after a human runs sno rem-reflect accept; away-brief emits a page of at most 60 lines split into Done, Stuck, Needs you and Spend; catch-report counts problems caught by the other model separately from self-caught mistakes, never summing them.
- A developer finished a change and wants a reviewer from a different model vendor to read it cold and report what would break in real use.
- A long build runs overnight and the team wants the task to survive one subscription running out of quota by handing over to the other vendor's agent.
- A user returns in the morning and needs one page covering what got done, what is stuck, which decisions are waiting and how much quota was spent.
- A lead must delegate a job to multiple executor agents and needs a written charter with deliverables, out-of-bounds areas and success checks.
- A team wants agents to learn from repeated corrections but insists that every lesson be approved by a human before it changes a skill.
- A user wants to try a single skill first, such as less-is-more or test-writer, which run without Sno Station.
How do you install or deploy this agent?
Ask your agent in chat to install sno.ai, or run the install script:
curl -fsSL https://sno.ai/install | shIf Sno Station is already present, run sno setup to install the skills into your agents; run it again when you add another agent.
You can also install as a plugin. Claude Code:
claude plugin marketplace add sno-ai/sno-station-skills
claude plugin install sno-station@sno-aiCodex:
codex plugin marketplace add sno-ai/sno-station-skills
codex plugin add sno-station@sno-aiFor a single skill, have the agent install it from the repository, for example peer-review:
Install only the peer-review skill from https://github.com/sno-ai/sno-station-skills
for this project, including its scripts and references.
Check its dependencies and tell me what is missing before installing anything else.rotate-agent additionally needs both CLIs logged in and tmux installed.
How do you use this agent?
After installation, trigger skills in ordinary chat, for example "peer-review this", "arm rotate-agent", "away brief" or "write a charter". The sno-station plugin holds all 37 skills and most call Sno Station programs; install sno-station-standalone@sno-ai instead if you only want the 7 skills that run without Sno Station. Approve nightly lessons with:
sno rem-reflect accept <id>Skills declare what they need at the top of SKILL.md:
requires:
programs: [reach]
harness:
- {slot: 4.shell, need: required}Publishing a skill requires passing the repository checks (LICENSE/NOTICE present, no personal paths or hard-coded models, self-tests on a clean copy), after which the publish step writes PUBLISHED.json.
What are this agent's strengths and limitations?
- peer-review forces a fresh session and prefers the other vendor's CLI, so a harness cannot quietly sign off on its own work.
- rotate-agent acts before quota is exhausted and hands over a verified brief plus the exact commit, instead of waiting for a refusal.
- Done claims are backed by written success checks answered by real runs, tracked with sno deliver-proof.
- rem-reflect requires a human accept before any skill or rule changes, so the nightly loop cannot silently rewrite behavior.
- Every unit is self-tested on a clean copy before release, and PUBLISHED.json records self-test counts and digests.
- The requires block lets setup install, degrade or skip each skill based on what the host agent can actually do.
- The full cross-vendor workflow depends on having both Claude Code and Codex installed and logged in.
- rotate-agent needs tmux in addition to the two CLIs, raising the environment bar above a single-agent setup.
- Most skills call Sno Station programs and require the separate sno installation; only 7 skills run standalone.
- Outside local-first mode rem-reflect uploads session text (best-effort redacted) and installed skills to Sno's cloud, so data boundaries need review.
- The README's opening line says 31 skills while the badge and body say 37 skills in 28 units, an inconsistency to reconcile before trusting counts.
- With only one vendor installed, peer-review degrades to a same-vendor review and loses the independence that motivates it.
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| Sno Station Skills This agent | 42 · Major gaps | — | ★ 861 | today | Shell | Codex · Claude Code |
| Finding-Unknowns Skills | 76 · Good | Agent plugin / skillFree | ★ 363 | 1mo ago | Python | Claude Code · Claude.ai |
| oh-my-agent | 48 · Major gaps | CLIFree + model costs | ★ 1.4k | 1d ago | TypeScript | Codex · Claude Code |
| Beautiful Rust | 78 · Good | Agent plugin / skillFree + model costs | ★ 1.7k | 2d ago | Python | ChatGPT · Codex · Claude Code · Claude.ai |
How does FollowAgents rate this agent?
Why each dimension lost points
README asserts least-privilege behaviors (medic read-only, rem-reflect requires human accept, handoff verifies before writing) and confirmation flows, but these are prose claims with no scripts or permission manifests in the provided files, so least_privilege and user_confirmation score 1-2. Install via curl | sh remote script and automatic self-update lack auditable data-flow or external-effect documentation, deducted. No dependency manifest or scanning evidence, so dependency_security is 0. Rollback is only implied by handoff verification; no version rollback or undo mechanism described. Source attribution points to sno.ai and a sibling repo, but publisher identity is unverified.
Internal inconsistency: description says 31 skills while badges and body say 37 skills in 28 units, and supported-agent lists differ (Claude Code/Codex vs OpenClaw/Hermes), deducted. Dependency availability is only described in prose (needs Sno Station programs and a logged-in reviewer) with no version constraints or failure handling detail. Failure messages are comparatively concrete: medic claims WARN/FAIL with exact fix commands, scoring 2.
Audience and scenarios are well described across review, handoff, reporting and nightly learning, scoring 2. Capability boundaries are stated (which skills run standalone vs need Sno Station), scoring 2. Trigger precision relies on natural-language phrases (e.g. "peer-review this") with no explicit trigger rules or conflict handling, scoring 1. Environment fit lists supported agents but omits OS and version requirements, scoring 1.
Information architecture is clear with J/M/S/H/T/R categories and a linked skills index, scoring 2. Install notes are thorough with multiple methods, scoring 2. Naming stability is deducted because skill counts and names are inconsistent across the document. Examples and FAQ are narrative stories without complete copyable examples, scoring 1. Known limitations are only scattered, with no dedicated section. License is the full Apache-2.0 text, scoring 3. No version number or changelog, scoring 0. Maintenance responsibility points only to sno.ai and a security email with unverified publisher, scoring 1.
Output usability is described with concrete artifacts (one-page brief, work orders, review reports), scoring 2. Marginal value claims are strong but lack quantified comparison to alternatives, and much functionality depends on the closed Sno Station, scoring 1. Cost-benefit mentions quota savings but provides no benchmark data, scoring 1.
Claims reference an evidence folder and screenshots, but no such files are present in this repository, only external links, so claim_traceability scores 1. Cross-source corroboration is limited to README self-report with no independent sources, scoring 1. Fact/inference separation is weak: marketing narrative and factual claims are interleaved (e.g. "162 written, 7 approved") without clear labeling, scoring 1.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Installation uses a curl | sh remote script with automatic self-update; review the script in an isolated environment before running.
- README is internally inconsistent on skill count (31 vs 37) and supported agents; verify actual scope against repository files.
- Much core functionality depends on the closed-source Sno Station program not present in this repository, limiting standalone usability.
- Publisher identity is unverified by FollowAgents; maintenance responsibility and update path are unclear.
- No dependency manifest, version number, or changelog, so dependency security and upgrade impact cannot be statically assessed.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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v1.0.31 Sno Station skills 1.0.31
Release notes excerpt
Sno Station skills 1.0.31 The team skills your agents share: peer review, handoff, delegation, reporting and learning from mistakes. Install them with sno setup. Already installed? Run sno update.View on GitHub ↗ -
v1.0.30 Sno Station skills 1.0.30
Release notes excerpt
Sno Station skills 1.0.30 The team skills your agents share: peer review, handoff, delegation, reporting and learning from mistakes. Install them with sno setup. Already installed? Run sno update.View on GitHub ↗ -
v1.0.29 Sno Station skills 1.0.29
Release notes excerpt
Sno Station skills 1.0.29 The team skills your agents share: peer review, handoff, delegation, reporting and learning from mistakes. Install them with sno setup. Already installed? Run sno update.View on GitHub ↗