Atmos is an infrastructure runtime that coordinates tools such as Terraform, OpenTofu, Kubernetes, Helm, Packer, Ansible, and containers through consistent commands and configuration. It is for teams running cloud infrastructure on laptops, in CI, or through AI agents across environments and regions. Its catalogue entries provide skills, agents, commands, and other add-ons for Atmos workflows.
Borrowing it
Nothing to install: this file belongs to cloudposse/atmos. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cloudposse/atmos/main/.claude/skills/gh-stack/SKILL.mdgit clone --depth 1 https://github.com/cloudposse/atmosWrote 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/cloudposse/atmos/gh-stack)<a href="https://agentmods.dev/skills/cloudposse/atmos/gh-stack"><img src="https://agentmods.dev/badge/skills/cloudposse/atmos/gh-stack/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/cloudposse/atmos/gh-stack"><img src="https://agentmods.dev/badge/skills/cloudposse/atmos/gh-stack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00073 | $0.02794 |
| Opus 5.5 | $0.00029 | $0.01118 |
| Sonnet 5.5 | $0.00015 | $0.00559 |
| Haiku 4.5 | $0.00007 | $0.00279 |
Grade A, and why
gh-stack 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 yesterday.
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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub PR stacks
Use this skill for dependent pull requests. Read maintenance and recovery before changing an existing published stack or operating its CI/review queue. Use the pull-request skill for labels, signing, descriptions, and release documentation.
Discover the tool and the actual stack
Start with gh stack --help and the relevant subcommand's --help; commands and supported flags
can change. If the extension is missing, identify github/gh-stack as the required extension
(gh extension install github/gh-stack). Follow the environment's installation permissions;
do not silently replace native stacks with an unregistered branch chain.
A feature branch based on another feature branch is only a dependency chain. GitHub's native
stack is a separate object. Creating PRs with gh pr create --base <parent> alone does not register
that object. Check both the configured base branches and native stack membership. A bottom PR may
target main and still belong to a stack; also look for open PRs based on its head branch.
When native registration is requested or otherwise authorized, use gh stack link for existing PRs
in the intended bottom-to-top order. Inspect current remote membership first, since linking changes
the stack. Do not convert an ordinary chain into a native stack merely to inspect it. Verify the
resulting object and ordering on GitHub, not just local branch ancestry. For example, after
substituting the actual repository and PR number:
gh stack link <bottom-pr> <middle-pr> <top-pr>
gh api graphql -f query='{ repository(owner:"OWNER", name:"REPO") {
pullRequest(number:123) { stack { number size entries(first:100) {
nodes { position pullRequest { number } }
} } }
} }'
Paginate if the returned entries do not cover the reported size. gh stack link can register remote
PRs without initializing local tracking; a local gh stack view failure alone does not prove the
remote stack is absent. Inspect the installed checkout/link help to reconcile local tracking.
What ships with it
1 file 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.
- yesterday Changed · +21 lines · -51 tokens per session 3e4da3a74539
- 3d ago First seen · 174 lines · 124 tokens per session scan A 52d88cd221d5
gh-stack is a skill published in the GitHub repository cloudposse/atmos (1,405 stars, last pushed today), licensed Apache-2.0. It adds 73 tokens to every session and 2,794 once invoked, about $0.0003 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 2026-10-18.
Other skills, from other repositories
work
Handle issue/PR work items with worktree isolation. Triggered by "/work [issuelink|description]" to start focused work.
gh
You have access to gh (GitHub CLI) for repository and project management.
hatch3r-issue-workflow
Guides the 8-step agentic development workflow for issues/work items. Covers parsing issues, loading skills, reading specs, planning, implementing, testing, opening PRs/MRs, and addressing review. Use when working on any issue/work item or when the user mentions an issue number.
hatch3r-pr-creation
Creates a pull request or merge request following project conventions including branch naming, PR/MR template, checklist, and rollout plan. Use when opening or preparing a PR/MR, or when the user asks to create a PR or MR.
pm-pr-workflow
Branch protection and PR creation workflow.
create-issue
Draft and submit a GitHub issue from a user idea or bug description, with bilingual body and correct labels.