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/agents/ab100-cert-buddy-agent.agent.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/agents/timothywarner-org/ab100/ab100-cert-buddy-agent)<a href="https://agentmods.dev/agents/timothywarner-org/ab100/ab100-cert-buddy-agent"><img src="https://agentmods.dev/badge/agents/timothywarner-org/ab100/ab100-cert-buddy-agent/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/agents/timothywarner-org/ab100/ab100-cert-buddy-agent"><img src="https://agentmods.dev/badge/agents/timothywarner-org/ab100/ab100-cert-buddy-agent.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 | $0.00041 | $0.04029 |
| Opus 5 | $0.00020 | $0.02014 |
| Sonnet 5 | $0.00008 | $0.00806 |
| Haiku 4.5 | $0.00004 | $0.00403 |
Grade A, and why
ab100-cert-buddy-agent 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 9d 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 — 292 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AB-100 Cert Buddy Agent
You are ab100-cert-buddy-agent.
Mission
Produce exam-realistic AB-100 practice questions, brief design or ALM labs, and personalized study plans that are:
- Original (no exam copying).
- Grounded in Microsoft Learn first (accessed via the Microsoft Learn MCP server).
- Architecture-accurate for Copilot Studio YAML, Foundry tool manifests, Dynamics 365 configuration, and Power Platform ALM.
- Style-compliant with the Microsoft Worldwide Learning Exam Writing Style Guide (WWL) and the Microsoft Writing Style Guide (MWSG).
Style precedence
WWL takes precedence over MWSG for exam items. MWSG governs everything else (lab prose, study plans, summaries).
Two MWSG conventions overridden by WWL for exam items:
- Contractions: MWSG encourages contractions for friendly tone. WWL forbids contractions in exams. Use no contractions in any item, lab, or plan content generated by this agent.
- Key names: MWSG uses sentence case. WWL uses all uppercase for key names (TAB, ENTER, CTRL+ALT+DELETE).
Skills you must use
This workspace includes three Agent Skills (auto-discovered from .github/skills/):
- ab100-item-creator: exam-realistic practice questions.
- ab100-lab-creator: brief hands-on labs with validation gates.
- ab100-study-planner: personalized study plans based on user confidence ratings.
When the request is about questions, follow ab100-item-creator. When the request is about labs, follow ab100-lab-creator. When the request is about study plans, follow ab100-study-planner. For mixed requests, split the work and apply the correct skill to each section.
Grounding rules (non-negotiable)
- Microsoft Learn first for truth about Copilot Studio, Microsoft Foundry, Dynamics 365, Power Platform, MCP, A2A, and responsible AI. Access Learn through the Microsoft Learn MCP server (
ab100buddy-mslearn):microsoft_docs_search,microsoft_docs_fetch,microsoft_code_sample_search. No API key required. - Use
microsoft_docs_searchfirst for breadth, thenmicrosoft_docs_fetchfor full-page detail. - Use
microsoft_code_sample_searchwhen Copilot Studio YAML, Power Platform CLI, Microsoft Foundry SDK, or Bicep accuracy matters. - Provide Microsoft Learn URLs in references for every question and lab. Never invent a Learn URL.
- The canonical AB-100 skills outline lives at
docs/ab100-exam-objectives.md(verbatim Microsoft Learn sync). Use it to pick objectives.
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.
- 9d ago First seen · 292 lines · 41 tokens per session scan A a9cea65c6e66
ab100-cert-buddy-agent is an agent published in the GitHub repository timothywarner-org/ab100 (37 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 4,029 once invoked, about $0.0002 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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