An expert AI tool that reverse-engineers teaching syllabi into structured, weighted exam combat maps.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install exam-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install exam-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Exam Point Analyzer?
The Exam Point Analyzer is a specialized agent designed to strip away academic filler and reveal the high-stakes core of any course or examination guide. By leveraging 20 years of pedagogical expertise, this skill within the Openclaw Skills ecosystem identifies specific terminology, formulas, and theories that are most likely to appear on actual tests.
It serves as a bridge between dense official documents and actionable study plans. Whether you are dealing with a standard syllabus, exam instructions, or past papers, this tool filters out administrative jargon to provide a structured JSON output of what truly matters for your academic success.
Exam Point Analyzer Use Cases
- Converting a 50-page university syllabus into a one-page study guide.
- Analyzing past exam papers to identify recurring patterns and high-frequency topics.
- Mapping specific verbs like 'master' or 'understand' to exam weight and difficulty levels.
- Predicting question types (e.g., multiple choice vs. calculation) based on the nature of the learning objective.
How Exam Point Analyzer Works
- The user provides a course name, syllabus text, or past exam documents to the Openclaw Skills interface.
- The agent identifies the document type and extracts key chapters while filtering out non-essential 'fluff'.
- It applies a weight-ranking logic based on action verbs: 'Mastery' yields 3 stars, 'Understanding' yields 2 stars, and 'Awareness' yields 1 star.
- The system maps these points to probable question formats like conceptual questions for multiple choice or derivations for calculation problems.
- A final, strictly formatted JSON object is generated containing the course name, overall objectives, paper structure, and the detailed combat map.
Exam Point Analyzer Setup
To integrate this skill into your workflow using Openclaw Skills, use the following activation prompts:
# Trigger via text commands
"Analyze exam points"
"Extract exam focus"
"Generate exam combat map"
You can also directly upload your .txt or .md syllabus files to the agent for automated processing.
Exam Point Analyzer Data Schema & Taxonomy
The skill organizes extracted intelligence into a hierarchical schema:
| Field | Description | Type |
|---|---|---|
| Course Name | The identified subject title | String |
| Assessment Goal | A one-sentence summary of the core exam objective | String |
| Paper Structure | Array of objects defining question types and score percentages | Array |
| Combat Map | A nested structure of chapters and specific exam points | Array |
| Importance Star | Rating from 1 to 3 stars based on verb intensity | String |
Exam Point Analyzer Advanced Features
- Professional verb-to-weight mapping for high-accuracy importance prediction.
- Automated noise reduction to filter out administrative and non-testable content.
- Predictive mapping that correlates learning objectives to specific question formats.
- Pure JSON output mode for seamless integration into other developer-built study applications within Openclaw Skills.
SKILL.md
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