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az104-study-planner

Generates a personalized AZ-104 study plan based on the user's self-assessed confidence across exam skill areas, prioritizing weak areas with estimated hours and Microsoft Learn module links. Use when the user asks for a study plan, is unsure what to study, or wants exam prep guidance.

ソース情報

リポジトリ
timothywarner-org/az104-cert-buddy
ソースの最終更新活動
2026年4月4日 14:01
検出された SKILL.md の言語
英語
スター
24
フォーク
11

インストール方法

デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。

ソースファイルを確認

インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。

SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
name
az104-study-planner
description
Generates a personalized AZ-104 study plan based on the user's self-assessed confidence across exam skill areas, prioritizing weak areas with estimated hours and Microsoft Learn module links. Use when the user asks for a study plan, is unsure what to study, or wants exam prep guidance.
# Skill: az104.study_planner.personalized **Description:** Generates a personalized AZ-104 study plan based on the user's self-assessed confidence across exam skill areas, prioritizing weak areas with estimated hours and Microsoft Learn module links. ## Grounding **Required sources:** - `references/az104-objectives.md` (AZ-104 skills measured, April 2025) - Microsoft Learn (access via the **Microsoft Learn MCP server** using `microsoft_docs_search` for current Learn module URLs) - Use `microsoft_docs_fetch` to verify Learn module links are current and active ## Workflow 1. **Present skill areas with weights.** Show the five AZ-104 skill areas and their exam weight percentages: | Skill Area | Exam Weight | | --- | --- | | Manage Azure identities and governance | 20-25% | | Implement and manage storage | 15-20% | | Deploy and manage Azure compute resources | 20-25% | | Implement and manage virtual networking | 15-20% | | Monitor and maintain Azure resources | 10-15% | 2. **Ask for confidence ratings.** Ask the user to rate their confidence in each area 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. 3. **Generate a prioritized study plan.** Based on the user's ratings: - Order areas from weakest to strongest. - Within equal confidence levels, prioritize areas with higher exam weight. - For each area, provide: - Estimated study hours (weak: 8-12 hours, moderate: 4-6 hours, strong: 1-2 hours). - Two to three specific Microsoft Learn module links (grounded via Microsoft Learn MCP server; do not invent URLs). - Key objectives to focus on (from `references/az104-objectives.md`). - Include a total estimated hours range at the bottom. 4. **Offer to start practicing.** After presenting the plan, ask: "Would you like to start with practice questions or a hands-on lab on **[first recommended topic]**?" ## Output format ```markdown ## Your Personalized AZ-104 Study Plan ### Priority 1: [Skill Area Name] (exam weight: XX-XX%) **Your confidence:** [rating] **Estimated study time:** X-X hours **Focus objectives:** - [Objective 1] - [Objective 2] - [Objective 3] **Recommended Microsoft Learn modules:** - [Module title](URL) - [Module title](URL) --- ### Priority 2: [Skill Area Name] (exam weight: XX-XX%) ... (repeat for each area) --- **Total estimated study time:** XX-XX hours Ready to start? I can generate practice questions or a hands-on lab on **[first recommended topic]**. ``` ## Guardrails - Do not skip any of the five skill areas. Even "strong" areas should appear in the plan with a light review recommendation. - Do not invent Microsoft Learn module URLs. Use the Microsoft Learn MCP server (`microsoft_docs_search`) to find real, current module links. - Treat "unknown" confidence the same as "weak." - Always use current Microsoft product names. See the rename table in `.github/copilot-instructions.md`. - No contractions. ## Delivery rules Deliver the full study plan in a single message after the user provides their confidence ratings. Do not split the plan across multiple messages.
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