Borrowing it
Nothing to install: this file belongs to timothywarner-org/ab100. 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/ab100/main/.github/skills/ab100-item-creator/SKILL.mdgit clone --depth 1 https://github.com/timothywarner-org/ab100Wrote 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/ab100/ab100-item-creator)<a href="https://agentmods.dev/skills/timothywarner-org/ab100/ab100-item-creator"><img src="https://agentmods.dev/badge/skills/timothywarner-org/ab100/ab100-item-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/ab100/ab100-item-creator"><img src="https://agentmods.dev/badge/skills/timothywarner-org/ab100/ab100-item-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 | $0.00081 | $0.04610 |
| Opus 5 | $0.00041 | $0.02305 |
| Sonnet 5 | $0.00016 | $0.00922 |
| Haiku 4.5 | $0.00008 | $0.00461 |
Grade A, and why
ab100-item-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 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.
How it starts
The opening of the file, as written. The whole thing — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: ab100.practice_questions.exam_realistic
Description: Generate AB-100 practice questions that feel like the real exam without copying it. Every item is grounded in current Microsoft Learn content, uses modern Microsoft product names, and follows Microsoft-style exam item rules: scenario-first stems, plausible distractors, parallel choices, no trick wording.
Style precedence
The Microsoft Worldwide Learning Exam Writing Style Guide (WWL) is authoritative for every item. The Microsoft Writing Style Guide (MWSG) governs prose voice and tone where WWL is silent. When the two guides conflict, WWL wins.
Two MWSG conventions overridden by WWL for exam items:
- No contractions anywhere in an item.
- All uppercase for key names: TAB, ENTER, CTRL+ALT+DELETE.
Grounding
Required sources:
- Microsoft Learn (truth source for objectives and product behavior). Access via the Microsoft Learn MCP server using
microsoft_docs_searchandmicrosoft_docs_fetch. - Microsoft Learn code samples (for Copilot Studio YAML, Power Platform CLI, Microsoft Foundry SDK accuracy). Access via
microsoft_code_sample_search. - Canonical AB-100 skills outline:
docs/ab100-exam-objectives.md(verbatim sync from Microsoft Learn).
AB-100 domains (canonical)
| Domain | Weight |
|---|---|
| Plan AI-powered business solutions | 25-30% |
| Design AI-powered business solutions | 25-30% |
| Deploy AI-powered business solutions | 40-45% |
Pull specific objectives from docs/ab100-exam-objectives.md. If that file is unavailable, query the Microsoft Learn MCP for the AB-100 study guide.
Style and word usage (WWL, mandatory)
Question sentence
- Begin with What (stand-alone interrogative pronoun) or Which (followed by a noun).
- The auxiliary in question sentences is should. Do not use can, must, might, do, would, or may in question sentences.
- Approved stems: What should you do? / What should you recommend? / Which agent should you use? / Which two actions should you perform? / What are two possible ways to achieve this goal?
- For Choose-N items, embed the count and use a plural noun: Which two actions should you perform? Each correct answer presents part of the solution.
- Avoid negatives. If a negative is unavoidable, CAP and bold it (for example, NOT).
- Goal statements use You need to ... or You need to ensure that ...
- Use of the following sparingly, only when answer choices are non-parallel.
- True/False stems are not allowed.
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 · 357 lines · 81 tokens per session scan A ad4b747f8df2
ab100-item-creator is a skill published in the GitHub repository timothywarner-org/ab100 (37 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 4,610 once invoked, about $0.0004 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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