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/regression-test/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/regression-test)<a href="https://agentmods.dev/skills/cloudposse/atmos/regression-test"><img src="https://agentmods.dev/badge/skills/cloudposse/atmos/regression-test/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/regression-test"><img src="https://agentmods.dev/badge/skills/cloudposse/atmos/regression-test.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 | $0.00078 | $0.02057 |
| Opus 5.5 | $0.00031 | $0.00823 |
| Sonnet 5.5 | $0.00016 | $0.00411 |
| Haiku 4.5 | $0.00008 | $0.00206 |
Grade A, and why
regression-test 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 2d 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Regression Test
Answer: What happens differently to an existing user who upgrades without changing their project?
Investigate and report. Do not fix product code, implement edition transitions, regenerate goldens, publish findings, or create issues as part of this skill. The number of bugs found is not a success metric. Unchanged bugs do not count as new regressions, but a worsening of an existing bug can. New functionality matters here when it affects existing workflows.
Use the hypothesis-driven, real-execution discipline of field-test, with the comparative evidence and edition analysis below. Passing today's unit tests alone does not establish upgrade compatibility. Under plan mode, research and specify the experiments; wait for execution mode before writing fixtures or executing the investigation.
1. Freeze the comparison
Interpret supplied baseline, candidate, and subsystem arguments. Otherwise:
- Resolve the latest published, non-draft, non-prerelease release through GitHub release
metadata (
gh api repos/cloudposse/atmos/releases/latest). A newer RC tag is not the default. - Resolve remote
main, fetching missing/stale refs when necessary. Pin both endpoints to commit SHAs; record the release tag, publication time, resolution time, and candidate SHA. Never substitute the current feature branch or include its uncommitted code in the candidate. - Verify refs and ancestry. Use the endpoint diff (
git diff <baseline-sha> <candidate-sha>), not a merge-base diff that silently changes the baseline. If refs cannot be obtained, report the unavailable comparison rather than guessing a different release. - Preserve the user's checkout and changes. Build isolated sources under a unique
.context/regression-test/<run>/directory; record source, toolchain, build settings, binary hashes, and harness revision. Distinguish locally rebuilt releases from published binaries. If both endpoints are identical, report that there is no revision delta to investigate.
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.
- 2d ago First seen · 154 lines · 78 tokens per session scan A 9a0fda6d623e
regression-test is a skill published in the GitHub repository cloudposse/atmos (1,405 stars, last pushed today), licensed Apache-2.0. It adds 78 tokens to every session and 2,057 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 2026-10-19.
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Lovable MCP tool usage — deploy projects, message agent, test with agent-browser. Minimize credits by delegating to local repo.