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 Arvo-AI/aurora --skill scalewaygit clone --depth 1 https://github.com/Arvo-AI/auroraWrote 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/arvo-ai/aurora/scaleway)<a href="https://agentmods.dev/skills/arvo-ai/aurora/scaleway"><img src="https://agentmods.dev/badge/skills/arvo-ai/aurora/scaleway.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 48 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00029 | $0.01407 |
| Opus 5 | $0.00015 | $0.00704 |
| Sonnet 5 | $0.00006 | $0.00281 |
| Haiku 4.5 | $0.00003 | $0.00141 |
Grade A, and why
scaleway 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scaleway Integration
Overview
Scaleway cloud provider for managing compute instances, Kapsule Kubernetes clusters, object storage, and managed databases.
Instructions
CLI COMMANDS (use cloud_exec with 'scaleway')
CRITICAL: Always use cloud_exec('scaleway', 'command') for Scaleway commands, NOT terminal_exec! The cloud_exec tool has your Scaleway credentials configured.
Discovery Commands:
- List projects:
cloud_exec('scaleway', 'account project list') - List zones:
cloud_exec('scaleway', 'instance zone list') - List instance types:
cloud_exec('scaleway', 'instance server-type list') - List images:
cloud_exec('scaleway', 'instance image list')
Instance Management:
- List instances:
cloud_exec('scaleway', 'instance server list') - Create instance:
cloud_exec('scaleway', 'instance server create type=DEV1-S image=ubuntu_jammy name=my-vm') - With zone:
cloud_exec('scaleway', 'instance server create type=DEV1-S image=ubuntu_jammy name=my-vm zone=fr-par-1') - Start/Stop/Reboot:
cloud_exec('scaleway', 'instance server start|stop|reboot <SERVER_ID>') - Delete:
cloud_exec('scaleway', 'instance server delete <SERVER_ID>') - SSH into server:
cloud_exec('scaleway', 'instance server ssh <SERVER_ID>')
Kubernetes (Kapsule):
- List clusters:
cloud_exec('scaleway', 'k8s cluster list') - Create cluster:
cloud_exec('scaleway', 'k8s cluster create name=my-cluster version=1.28 cni=cilium') - Get kubeconfig:
cloud_exec('scaleway', 'k8s kubeconfig get <CLUSTER_ID>') - List pools:
cloud_exec('scaleway', 'k8s pool list cluster-id=<CLUSTER_ID>') - Create pool:
cloud_exec('scaleway', 'k8s pool create cluster-id=<CLUSTER_ID> name=worker-pool node-type=DEV1-M size=3')
Object Storage:
- List buckets:
cloud_exec('scaleway', 'object bucket list') - Create bucket:
cloud_exec('scaleway', 'object bucket create name=my-bucket')
Databases:
- List instances:
cloud_exec('scaleway', 'rdb instance list') - Create instance:
cloud_exec('scaleway', 'rdb instance create name=my-db engine=PostgreSQL-15 node-type=DB-DEV-S')
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 First seen · 133 lines · 29 tokens per session scan A 29d45137c4e2
scaleway is a skill published in the GitHub repository Arvo-AI/aurora (405 stars, last pushed today), licensed Apache-2.0. It adds 29 tokens to every session and 1,407 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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