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 timothywarner-org/ai901-cert-buddy-claude --skill ai901-lab-creatorgit clone --depth 1 https://github.com/timothywarner-org/ai901-cert-buddy-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/timothywarner-org/ai901-cert-buddy-claude/ai901-lab-creator)<a href="https://agentmods.dev/skills/timothywarner-org/ai901-cert-buddy-claude/ai901-lab-creator"><img src="https://agentmods.dev/badge/skills/timothywarner-org/ai901-cert-buddy-claude/ai901-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/ai901-cert-buddy-claude/ai901-lab-creator"><img src="https://agentmods.dev/badge/skills/timothywarner-org/ai901-cert-buddy-claude/ai901-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 | $0.00097 | $0.04662 |
| Opus 5 | $0.00048 | $0.02331 |
| Sonnet 5 | $0.00019 | $0.00932 |
| Haiku 4.5 | $0.00010 | $0.00466 |
Grade A, and why
ai901-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 12d 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 — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: ai901.practice_labs.micro.validated
Description: Create short AI-901 practice labs (15-25 minutes) that are executable and self-validating. Every lab includes prerequisites, exact tasks, validation steps, expected outputs, and cleanup.
Course context
This skill backs Tim Warner's Microsoft Press AI-901 video course companion repo at C:\github\ai901. The course is a 16-lesson Microsoft Press video course. Lessons 01-07 are concept lessons aligned to AI-901 Domain 1. Lessons 08-16 are build lessons aligned to AI-901 Domain 2. Each lesson lives at lessons/lesson-NN/README.md. When a lab is built to support a specific lesson, save the lab artifact under lessons/lesson-NN/labs/ so that learners find it next to the lesson plan.
Audience profile
The AI-901 audience is at the beginning of a career in AI solution development. Learners have conceptual knowledge of AI in Azure, can read Python coding syntax, and are familiar with Azure resources. Lab prose stays warm and direct. Avoid jargon that the lesson has not yet introduced.
Style precedence
Follow the Microsoft Worldwide Learning Exam Writing Style Guide (WWL) for any text that mirrors exam phrasing (titles, goal statements, named resources, company references). Follow the Microsoft Writing Style Guide (MWSG) for the lab prose itself: warm, scannable, present-tense, sentence-style capitalization. Two MWSG conventions overridden by WWL for our labs: no contractions and all uppercase for key names (TAB, ENTER, CTRL+ALT+DELETE).
Lab categories
AI-901 labs span four practical categories that map to the AI-901 build domain:
- foundry-portal -- Microsoft Foundry portal hands-on. Model deployment from the model catalog, playground experiments, single-agent builds, prompt flow inspection, and grounded chat configuration entirely inside the portal.
- foundry-sdk -- Python 3.12 client apps that call Microsoft Foundry endpoints with the azure-ai-projects and azure-ai-agents packages. Authentication is keyless via DefaultAzureCredential. Patterns include chat completion, multi-turn conversations, single-agent invocation, and tool-augmented agents.
- ai-services -- Azure AI Language, Azure AI Speech, and Azure AI Vision exercised through Microsoft Foundry Tools. Examples include text analytics, sentiment, key phrases, entity recognition, speech-to-text, text-to-speech, image analysis, optical character recognition, and image generation.
- content-understanding -- Azure Content Understanding analyzers across the four supported modalities: documents, images, audio, and video. Includes analyzer creation, schema definition, sample input runs, and output validation.
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.
- 12d ago First seen · 331 lines · 97 tokens per session scan A 9c6ebaae7ef2
ai901-lab-creator is a skill published in the GitHub repository timothywarner-org/ai901-cert-buddy-claude (9 stars, last pushed 2mo ago), licensed MIT. It adds 97 tokens to every session and 4,662 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
canvas
Fetch Canvas LMS courses and assignments via API token.
rwkv-architecture
RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
skill-creation-walkthrough
Step-by-step guide for creating your own Claude Skills, from deciding whether a skill is the right tool to writing the SKILL.md file, structuring reference material, and making it trigger reliably. Use when you want to package a workflow, framework, or repeated task into a reusable Skill, when an existing skill is not…
stride-analysis-patterns
Apply STRIDE methodology to systematically identify threats. Use when analyzing system security, conducting threat modeling sessions, or creating security documentation.
prompts-chat
Use when searching, installing, or improving AI skills and prompts via prompts.chat or skills.sh. Triggers on skill search, prompt lookup, install skill, improve prompt, prompts.chat.
bq-skill
A coaching workflow for building a reusable library of truthful stories for behavioral job interviews. It uses structures such as STAR—Situation, Task, Action, Result—and can connect stories to a job description and résumé.