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 klh/speedy-claude --skill azgit clone --depth 1 https://github.com/klh/speedy-claudeWrote 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/klh/speedy-claude/az)<a href="https://agentmods.dev/skills/klh/speedy-claude/az"><img src="https://agentmods.dev/badge/skills/klh/speedy-claude/az/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/klh/speedy-claude/az"><img src="https://agentmods.dev/badge/skills/klh/speedy-claude/az.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Prompt Injection · line 10 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00059 | $0.00729 |
| Opus 5 | $0.00030 | $0.00365 |
| Sonnet 5 | $0.00012 | $0.00146 |
| Haiku 4.5 | $0.00006 | $0.00073 |
Grade A, and why
az 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 8d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Azure CLI
Intent Router
| Request | Reference | Load When |
|---|---|---|
| Install tool, first-time setup | references/install-and-setup.md |
User needs to install Azure CLI or do initial configuration |
| Command patterns, ARM/Bicep | references/command-cookbook.md |
User needs resource patterns, ARM deployment, AKS, Key Vault, or RBAC examples |
| Authentication, subscriptions | references/auth-and-config.md |
User needs login setup, service principal, multi-tenant, or sovereign cloud configuration |
Workflow
- Run preflight before any Azure command workflow.
- Check authentication and subscription context.
- Choose a core command track and run inspect commands first.
- Require explicit user confirmation before write/delete commands.
- Re-run context checks and summarize outcomes.
# Log in, confirm active subscription, and list resource groups
az login
az account show
az group list --output table
Preflight
Use bundled scripts for deterministic checks:
scripts/az-preflight.shscripts/az-auth-status.shscripts/az-context.shscripts/az-diagnostics.sh [--json] [--out <file>]
If the environment cannot access ~/.azure, set:
export AZURE_CONFIG_DIR=/tmp/az-config
Core Command Tracks
- Auth and subscription context:
az login,az account show,az account list --output table,az account set --subscription <id-or-name> - Resource group and inventory inspection:
az group list --output table,az resource list --resource-group <rg> --output table - Deployment inspection:
az deployment group list --resource-group <rg> --output table,az deployment group show --resource-group <rg> --name <deployment> - Output shaping and filters:
Use
--queryand--output json|table|yamlfor repeatable results.
What ships with it
11 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.
- agents/claude.yaml 213 B
- agents/openai.yaml 213 B
- references/auth-and-config.md 5.2 KB
- references/command-cookbook.md 5.4 KB
- references/install-and-setup.md 2.0 KB
- scripts/az-auth-status.sh 1.4 KB runs code
- scripts/az-context.sh 1.8 KB runs code
- scripts/az-diagnostics.sh 2.1 KB runs code
- scripts/az-preflight.sh 1.9 KB runs code
- scripts/install.ps1 2.8 KB runs code
- scripts/install.sh 2.3 KB runs code
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.
- 8d ago First seen · 76 lines · 59 tokens per session scan A 74247ac918df
az is a skill published in the GitHub repository klh/speedy-claude (11 stars, last pushed 2d ago), licensed MIT. It adds 59 tokens to every session and 729 once invoked, about $0.0003 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 2026-09-04.
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