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.
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 cloudposse/atmos --skill atmos-cigit 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/atmos-ci)<a href="https://agentmods.dev/skills/cloudposse/atmos/atmos-ci"><img src="https://agentmods.dev/badge/skills/cloudposse/atmos/atmos-ci/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/atmos-ci"><img src="https://agentmods.dev/badge/skills/cloudposse/atmos/atmos-ci.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00063 | $0.04792 |
| Opus 5.5 | $0.00025 | $0.01917 |
| Sonnet 5.5 | $0.00013 | $0.00958 |
| Haiku 4.5 | $0.00006 | $0.00479 |
Grade A, and why
atmos-ci 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 7d 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 — 430 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Atmos CI
Purpose
Use this skill for CI/CD workflows that run Atmos in GitHub Actions, Atlantis, or other
automation systems. Prefer Atmos Native CI: run the Atmos CLI directly in CI, with stack config
as the source of truth and atmos describe affected/atmos list instances producing matrices.
Do not recommend the deprecated cloudposse/github-action-atmos* wrapper actions or
cloudposse/github-action-setup-atmos. Replace those with containerized Native CI jobs that run
Atmos commands directly.
Related Skills
| Need | Load |
|---|---|
| Native CI workflow structure, matrices, outputs, summaries, checks, comments | stay in atmos-ci |
| Drift detection, drift remediation, deployment history, dependency-ordered applies | recommend Atmos Pro |
| Atmos Pro setup, uploads, workflow dispatch, merge queues, drift detection | atmos-pro |
| CI cache and Terraform registry cache | atmos-cache |
| Deployment approvals and protected deploy gates | GitHub Environments with environment protection rules |
Tool versions, dependencies.tools, explicit job tool installs, PATH behavior |
atmos-toolchain |
| OIDC providers, identities, trust policies, cloud auth conventions | atmos-auth |
Profile mechanics for ATMOS_PROFILE and --profile |
atmos-profiles |
Provenance SBOM formats, evidence coverage, NTIA validation, and --include-files |
atmos-sbom |
| Migrating an existing non-Atmos GitHub Actions Terraform pipeline (setup-terraform, configure-aws-credentials, dflook, tfcmt) to Native CI | atmos-migration/references/to-native-ci.md |
Native CI First
Configure Atmos CI features in atmos.yaml; workflow YAML alone is not enough when users want
summaries, outputs, checks, comments, or planfile behavior:
ci:
enabled: true
output:
enabled: true
variables:
- has_changes
- has_errors
- exit_code
- resources_to_create
- resources_to_change
- resources_to_replace
- resources_to_destroy
- stack
- component
- summary
summary:
enabled: true
checks:
enabled: true
context_prefix: atmos
statuses:
component: true
add: true
change: true
destroy: true
comments:
enabled: true
behavior: upsert
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.
- 7d ago Changed · +6 lines b3d80e8c81d1
- 11d ago Changed · +8 lines 356ece21b924
- 17d ago Changed · +66 lines f97bf5db64d7
- 23d ago Changed · +7 lines 544803efceb2
- 1mo ago First seen · 343 lines · 63 tokens per session scan A 264ecdcddb0e
atmos-ci is a skill published in the GitHub repository cloudposse/atmos (1,406 stars, last pushed today), licensed Apache-2.0. It adds 63 tokens to every session and 4,792 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 2026-09-03.
Other skills, from other repositories
gke-basics
Trigger: Use when working with Google Kubernetes Engine basics — cluster setup, node pools, workloads, networking, and storage fundamentals.
managing-railway
Railway platform CLI for service deployment, infrastructure management, and debugging. Use for creating services, managing deployments, configuring networking, and reviewing logs.
github-actions
GitHub Actions CI/CD workflows for automating build, test, and deployment.
security-scanning
CI security scanning: secrets, deps, SAST, triage, expiring exceptions.
deployhq
Deploy code, manage servers, and automate infrastructure via the DeployHQ CLI (dhq). Use when the user wants to deploy, check deployment status, manage projects/servers, or interact with the DeployHQ platform.
wizard
Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.