exam-prep

Create a exam prep with structured process, quality checks, and system integration

SKILL.md

GitHub

Exam Prep

Purpose

Create a comprehensive exam prep that delivers actionable, measurable results. This skill provides a structured process with quality validation, ensuring professional-grade output every time.

Category: Education & Training

Inputs

Required

  • Objective: What you want to achieve with this deliverable
  • Context: Relevant background information

Optional

  • Constraints: Any limitations or requirements to consider
  • Existing Work: Previous documents or data to build on

System Context

Before starting:

  • Read memory.md for current project context and priorities
  • Check knowledge-base.md for relevant learned rules or constraints
  • Review any existing related documents in the project
  • Note any active tasks in Task Board.md that relate to this deliverable

Process

Step 1: Context & Research

  • Review any existing exam prep documents in the project
  • Check knowledge-base.md for relevant learned rules or constraints
  • Check memory.md for current project context and priorities
  • Identify key stakeholders and their requirements
  • Select the most appropriate framework: Bloom's Taxonomy, ADDIE (Analyze, Design, Develop, Implement, Evaluate), Kirkpatrick Four Levels

Step 2: Analysis & Framework Application

  • Apply the selected framework to structure the exam prep
  • Identify gaps, opportunities, and risks
  • Define success metrics: Completion Rate, Assessment Scores, Knowledge Retention, Learner Satisfaction
  • Document assumptions and dependencies
  • Validate approach against industry best practices

Step 3: Build the Deliverable

  • Structure the exam prep using the output format below
  • Include specific, actionable recommendations — not generic advice
  • Add concrete numbers, timelines, and benchmarks where applicable
  • Cross-reference with existing project documents for consistency
  • Ensure every section adds value — remove filler

Step 4: Quality Validation

  • All required inputs have been addressed
  • Recommendations are specific and actionable (not vague)
  • Numbers and benchmarks are realistic and sourced
  • Output format matches the specification below
  • No contradictions with knowledge-base rules
  • Follows best practice: Start with learning objectives (what will they DO)

Output Format

# Exam Prep

## Executive Summary
[2-3 sentence overview of the deliverable and key recommendations]

## Context & Objectives
- **Objective**: [What this achieves]
- **Audience**: [Who this is for]
- **Timeline**: [When this applies]

## Analysis
[Structured analysis using the selected framework]

## Recommendations
1. [Specific, actionable recommendation with expected impact]
2. [Specific, actionable recommendation with expected impact]
3. [Specific, actionable recommendation with expected impact]

## Implementation
| Action | Owner | Timeline | Priority |
|--------|-------|----------|----------|
| [Action item] | [Who] | [When] | [High/Medium/Low] |

## Success Metrics
| Metric | Current | Target | Measurement Method |
|--------|---------|--------|-------------------|
| [KPI] | [Baseline] | [Goal] | [How to measure] |

## Risks & Mitigations
| Risk | Likelihood | Impact | Mitigation |
|------|-----------|--------|------------|
| [Risk] | [H/M/L] | [H/M/L] | [Action] |

## Next Steps
- [ ] [Immediate next action]
- [ ] [Follow-up action]
- [ ] [Review date]

Applicable Frameworks

  • Bloom's Taxonomy
  • ADDIE (Analyze, Design, Develop, Implement, Evaluate)
  • Kirkpatrick Four Levels
  • Backwards Design
  • Universal Design for Learning
  • Spaced Repetition

Key Metrics

  • Completion Rate
  • Assessment Scores
  • Knowledge Retention
  • Learner Satisfaction
  • Time to Competency
  • Application Rate (on-the-job)

Best Practices

  • Start with learning objectives (what will they DO)
  • Chunk content into 5-7 minute segments
  • Mix modalities (read, watch, do, discuss)
  • Assessment aligned to objectives
  • Follow up at 30, 60, 90 days for retention

After Completion

  • Update memory.md if this deliverable changes project context or priorities
  • Add any reusable learnings to knowledge-nominations.md
  • If follow-up actions were identified, add them to Task Board.md
  • Recommend related skills if additional work is needed