Borrowing it
Nothing to install: this file belongs to DanWahlin/github-azure-agentic-journeys. 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/DanWahlin/github-azure-agentic-journeys/main/.github/skills/superset-azure/SKILL.mdgit clone --depth 1 https://github.com/DanWahlin/github-azure-agentic-journeysWrote 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/danwahlin/github-azure-agentic-journeys/superset-azure)<a href="https://agentmods.dev/skills/danwahlin/github-azure-agentic-journeys/superset-azure"><img src="https://agentmods.dev/badge/skills/danwahlin/github-azure-agentic-journeys/superset-azure/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/danwahlin/github-azure-agentic-journeys/superset-azure"><img src="https://agentmods.dev/badge/skills/danwahlin/github-azure-agentic-journeys/superset-azure.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 | $0.00026 | $0.02703 |
| Opus 5 | $0.00013 | $0.01352 |
| Sonnet 5 | $0.00005 | $0.00541 |
| Haiku 4.5 | $0.00003 | $0.00270 |
Grade A, and why
superset-azure 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 10d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- superset-azure — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apache Superset on Azure Skill
Deploy Apache Superset data visualization platform on Azure Kubernetes Service.
Complexity Note: Superset is the most complex deployment in this project due to psycopg2 requirements and AKS architecture. Deploy time: ~15-20 minutes.
Prerequisites and Portability
Require Azure CLI, Azure Developer CLI 1.28.0 or later, and Node.js LTS or later. Verify az version, azd version, and node --version before generating infrastructure. The host must not need kubectl or Helm. Installation options for Windows, Mac, and Linux are in ../../../docs/tool-installation.md.
Generate the AKS post-provision workflow as infra-superset/hooks/postprovision.js and reference it directly from azure.yaml. The hook must attach the Kubernetes manifests and a remote deployment script to az aks command invoke. Run Helm and kubectl inside Azure. Invoke az and azd with argument arrays. On Mac and Linux, call each executable directly. On Windows, use the static PowerShell runner and JSON environment payload defined by the container-apps-deployment skill so Azure CLI .cmd shims aren't launched directly. Reject double quotes for every Windows target and additional shell metacharacters or CR/LF for .cmd/.bat; use attached scripts for complex remote commands. Do not generate a Bash-only host hook.
Start the long deployment command with --no-wait, parse the returned command ID, and poll az aks command result. Require provisioningState to equal Succeeded and exitCode to equal 0. Use a separate short AKS run command to read the ingress IP so URL discovery does not depend on long-command log truncation.
Write generated Kubernetes Secret values to a mode-0600 temporary manifest as base64 data. Attach the temporary bundle to AKS run command, do not print the values, delete the remote Secret manifest immediately after kubectl apply, and remove the local bundle in finally after success or failure.
The hook owns SUPERSET_SECRET_KEY and SUPERSET_ADMIN_PASSWORD. On a clean environment, generate cryptographically random values for either missing setting, persist each with azd env set, never print the values, and reuse existing values on reruns. A first deployment must not depend on undocumented manual secret setup.
What ships with it
5 files 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.
- 10d ago First seen · 221 lines · 26 tokens per session scan A 75d81ef6902a
superset-azure is a skill published in the GitHub repository DanWahlin/github-azure-agentic-journeys (37 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 2,703 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
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