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 agentskillexchange/skills --skill argo-workflows-dag-pipeline-buildergit clone --depth 1 https://github.com/agentskillexchange/skillsWrote 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/agentskillexchange/skills/argo-workflows-dag-pipeline-builder)<a href="https://agentmods.dev/skills/agentskillexchange/skills/argo-workflows-dag-pipeline-builder"><img src="https://agentmods.dev/badge/skills/agentskillexchange/skills/argo-workflows-dag-pipeline-builder/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/agentskillexchange/skills/argo-workflows-dag-pipeline-builder"><img src="https://agentmods.dev/badge/skills/agentskillexchange/skills/argo-workflows-dag-pipeline-builder.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 | $0.00047 | $0.00414 |
| Opus 5.5 | $0.00019 | $0.00166 |
| Sonnet 5.5 | $0.00009 | $0.00083 |
| Haiku 4.5 | $0.00005 | $0.00041 |
Grade A, and why
Argo Workflows DAG Pipeline Builder 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.
What it actually says
Argo Workflows DAG Pipeline Builder
Constructs Kubernetes-native workflow DAGs using Argo Workflows CRDs with configurable retry strategies, artifact passing via S3/MinIO, and template composition through WorkflowTemplates and ClusterWorkflowTemplates.
Installation
Requirements and caveats from upstream:
- Including for Python users through the Hera Python SDK for Argo Workflows.
- Check out our Java, Golang, Python (Hera), and Typescript (Juno) clients.
- Scheduling (affinity/tolerations/node selectors)
Basic usage or getting-started notes:
-
Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes.
-
Cloud agnostic and can run on any Kubernetes cluster.
-
Extracted from upstream docs: https://raw.githubusercontent.com/argoproj/argo-workflows/HEAD/README.md
Source
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 · 38 lines · 47 tokens per session scan A 2144c2c3b884
Argo Workflows DAG Pipeline Builder is a skill published in the GitHub repository agentskillexchange/skills (55 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 414 once invoked, about $0.0002 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.
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