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/agents/README.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/agents/cloudposse/atmos/readme)<a href="https://agentmods.dev/agents/cloudposse/atmos/readme"><img src="https://agentmods.dev/badge/agents/cloudposse/atmos/readme/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/agents/cloudposse/atmos/readme"><img src="https://agentmods.dev/badge/agents/cloudposse/atmos/readme.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 | $0.00000 | $0.00694 |
| Opus 5.5 | $0.00000 | $0.00278 |
| Sonnet 5.5 | $0.00000 | $0.00139 |
| Haiku 4.5 | $0.00000 | $0.00069 |
Grade A, and why
README 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 1mo 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude Agents
Specialized Claude agents for Atmos development. Each agent is an expert in a specific domain, helping scale development through focused expertise.
Available Agents
agent-developer
Expert in creating and maintaining Claude agents with correct frontmatter, context efficiency, and PRD awareness.
Use when: Creating new agents, updating existing agents, or optimizing agent instructions.
tui-expert
Theme-aware Terminal UI system expert. Use for developing UI components, refactoring to theme-aware patterns, and theme architecture guidance.
Use when: Working with theme system, TUI components, or terminal output formatting.
example-creator
Expert in creating Atmos examples with proper structure, documentation, mock components, and CI testing integration.
Use when: Creating new examples/demos, adding mock components, writing test cases for examples, or updating documentation with EmbedFile components.
coderabbit-review
Reviews and addresses CodeRabbit feedback on code changes: parses review threads, verifies each finding against current code, applies valid fixes, skips stale/wrong ones with explanation.
Use when: A CodeRabbit review lands with unresolved feedback, on-demand or from the pr-maintenance-loop skill's hourly cycle.
lint-fix
Fixes golangci-lint findings (patch-scoped or full-repo) produced by the lint skill, following this repo's formatting/error-handling/comment conventions.
Use when: The lint skill has findings to fix, either human-invoked or from pr-maintenance-loop's hourly cycle.
test-coverage-fix
Fixes in-scope failing tests (never pre-existing ones), then fixes genuine coverage gaps on added lines, for the current patch vs origin/main. Zero tolerance for coverage theater or weakened assertions.
Use when: The test-coverage skill has failures or coverage gaps to address, either human-invoked or from pr-maintenance-loop's hourly cycle.
merge-conflict-resolve
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.
- 1mo ago First seen · 78 lines · 0 tokens per session scan A 32071865c9f3
README is an agent published in the GitHub repository cloudposse/atmos (1,403 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 694 tokens. 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 2026-08-30.
Other agents, from other repositories
k8s-engineer
Kubernetes specialist for container orchestration, cluster management, and deployment strategies. Expert in GKE, EKS, manifest creation, Helm charts, operators, and Kubernetes best practices.
aiox-qa
AIOX QA/Tester autônomo. Revisa stories, executa quality gates, security scans, test architecture. Usa task files reais com gate decision (PASS/CONCERNS/FAIL).
aiox-ux-design-expert
🎨 UX/UI Designer & Design System Architect (Uma). Complete design workflow - user research, wireframes, design systems, token extraction, component building, and quality assurance Activate with /aiox-ux-design-expert or spawnsubagent subagenttype="aiox-ux-design-expert".
aiox-pm
AIOX Project Manager autônomo. Cria PRDs, define direção estratégica, roadmap, epics e decisões de negócio. Usa task files reais do AIOX.
aiox-po
AIOX Product Owner autônomo. Valida stories, gerencia backlog, garante coerência de epic context. Usa task files reais do AIOX.
deploy
Deploy to target platform — Vercel, Netlify, Fly.io, AWS, VPS. Pre-deploy verification + security gates. Tests and sentinel MUST pass first.