Borrowing it
Nothing to install: this file belongs to timothywarner-org/az104-cert-buddy. 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/timothywarner-org/az104-cert-buddy/main/.github/skills/az104-lab-creator/SKILL.mdgit clone --depth 1 https://github.com/timothywarner-org/az104-cert-buddyWrote 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/timothywarner-org/az104-cert-buddy/az104-lab-creator)<a href="https://agentmods.dev/skills/timothywarner-org/az104-cert-buddy/az104-lab-creator"><img src="https://agentmods.dev/badge/skills/timothywarner-org/az104-cert-buddy/az104-lab-creator/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/timothywarner-org/az104-cert-buddy/az104-lab-creator"><img src="https://agentmods.dev/badge/skills/timothywarner-org/az104-cert-buddy/az104-lab-creator.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 | $0.00063 | $0.01203 |
| Opus 5 | $0.00032 | $0.00602 |
| Sonnet 5 | $0.00013 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
az104-lab-creator 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 11d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: az104.practice_labs.micro.validated
Description: Create short AZ-104 practice labs (10-20 minutes) that are executable and self-validating. Every lab includes prerequisites, exact tasks, validation steps, expected outputs, and cleanup.
Grounding
Required sources:
- Microsoft Learn (primary truth source for architecture and correct configuration; access via the Microsoft Learn MCP server using
microsoft_docs_searchandmicrosoft_docs_fetch) - Microsoft Learn code samples (for CLI/PowerShell/Bicep accuracy; access via
microsoft_code_sample_search)
Style
Microsoft style:
- Use Microsoft instruction formatting conventions for UI labels, commands, and dialog names.
- See
references/style-guide.mdfor detailed Microsoft writing style rules. - Bold for clickable UI elements. Input-neutral verbs: select (not click), enter (not type).
Guardrails
- Keep the lab within AZ-104 scope (admin tasks, not deep dev).
- Prefer lowest-cost resources; include a cost warning if not.
- No contractions.
- No ambiguous "click around until" steps.
- Always include cleanup steps that remove created resources.
- Always use current Microsoft product names. Never use retired names such as "Azure AD" (use "Microsoft Entra ID"), "Azure AD Connect" (use "Microsoft Entra Connect"), and so on. See the full rename table in
.github/copilot-instructions.md. If a lab touches identity or governance, double-check every product name against current terminology.
Fictional company randomization (non-negotiable)
Use fictional company names from references/fictional-companies.md for any scenario context in lab titles or descriptions. You MUST randomize the company selection -- do not default to Contoso for every lab. Draw from the full list of 50+ companies.
Timebox guidance
A lab should contain no more than 12 steps total across all tasks. If the lab requires more than 12 steps, it likely exceeds the 20-minute timebox. In that case, split the content into two separate labs, each focused on a narrower objective.
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.
- 11d ago First seen · 127 lines · 63 tokens per session scan A da9588fda170
az104-lab-creator is a skill published in the GitHub repository timothywarner-org/az104-cert-buddy (22 stars, last pushed 5mo ago), licensed MIT. It adds 63 tokens to every session and 1,203 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 2026-08-30.
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