Borrowing it
Nothing to install: this file belongs to timothywarner-org/ab900. 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/ab900/main/.github/skills/ab900-study-planner/SKILL.mdgit clone --depth 1 https://github.com/timothywarner-org/ab900Wrote 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/ab900/ab900-study-planner)<a href="https://agentmods.dev/skills/timothywarner-org/ab900/ab900-study-planner"><img src="https://agentmods.dev/badge/skills/timothywarner-org/ab900/ab900-study-planner.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.02260 |
| Opus 5 | $0.00021 | $0.01130 |
| Sonnet 5 | $0.00008 | $0.00452 |
| Haiku 4.5 | $0.00004 | $0.00226 |
Grade A, and why
ab900-study-planner 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 7d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: ab900.study_planner.personalized
Description: Generates a personalized AB-900 study plan based on the user's self-assessed confidence across the three exam domains, prioritizing weak domains with estimated hours and Microsoft Learn module links.
Grounding
Required sources:
- AB-900 exam skills outline (Microsoft 365 Copilot and Agent Administration Fundamentals, current skills-measured document) [Microsoft Learn]
- Microsoft Learn (access via Microsoft Learn MCP server and Copilot web search for current Learn module URLs)
- Context7 MCP (resolve Learn module links and verify they are current)
Workflow
-
Present exam domains with weights. Show the three AB-900 exam domains and their exam weight percentages:
Domain Exam Weight Domain 1: Identify the core features and objects of Microsoft 365 services 30-35% Domain 2: Understand data protection and governance tasks for Microsoft 365 and Copilot 35-40% Domain 3: Perform basic administrative tasks for Copilot and agents 25-30% These titles and weights are from the Skills measured as of July 22, 2026 version of the study guide. Use them verbatim.
Flag Domain 2 explicitly as the highest-weight domain: "Domain 2 carries the most exam weight (35-40%). If all three domains are weak or unknown, prioritize Domain 2 first."
-
Ask for confidence ratings. Ask the user to rate their confidence in each domain using one of these levels:
- Strong -- comfortable with most objectives; needs only light review.
- Moderate -- familiar with the concepts but needs targeted practice.
- Weak -- limited experience; needs focused study.
- Unknown -- not sure; treat as weak.
-
Generate a prioritized study plan. Based on the user's ratings:
- Order domains from weakest to strongest.
- Within equal confidence levels, prioritize domains with higher exam weight (Domain 2 first, then Domain 1, then Domain 3).
- For each domain, provide:
- Estimated study hours (weak: 6-8 hours, moderate: 3-5 hours, strong: 1-2 hours).
- Two to three specific Microsoft Learn module links (grounded via Microsoft Learn MCP server or web search; do not invent URLs).
- Key objectives to focus on (from the AB-900 skills-measured document).
- High-priority topics specific to AB-900 (see domain-specific guidance below).
- Include a total estimated hours range at the bottom.
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.
- 7d ago First seen · 164 lines · 42 tokens per session scan A 44e5ff11e488
ab900-study-planner is a skill published in the GitHub repository timothywarner-org/ab900 (26 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 2,260 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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