An AI-powered academic advisor that matches students with ideal universities and majors based on competitive exam data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install form-app
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 form-app 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 Academic Matching & Enrollment (form)?
The form skill is a specialized tool within the Openclaw Skills ecosystem designed to assist students in navigating the complex landscape of higher education admissions. By analyzing entrance exam scores, provincial rankings, and subject preferences, it provides a data-driven strategy for school selection. It specifically addresses the needs of students looking for a balance between ambitious 'reach' schools and reliable 'safety' institutions.
This skill leverages historical admission data to provide insights into specific majors like Computer Science and Electronic Information. It doesn't just suggest names; it evaluates academic strengths, postgraduate success rates, and regional advantages to ensure students make informed decisions about their future careers.
Academic Matching & Enrollment (form) Use Cases
- High school graduates needing to fill out university preference forms based on competitive exam rankings.
- Students seeking a tiered list of 'reach', 'match', and 'safety' schools to minimize the risk of rejection.
- Comparing specific majors across different top-tier universities for postgraduate research potential.
- Analyzing regional advantages of studying in major hubs like Beijing or Shanghai.
How Academic Matching & Enrollment (form) Works
- The user provides key input data including exam scores, provincial ranking, subject combination (e.g., Physics/Chemistry/Biology), and geographic preferences.
- The skill analyzes the input against historical admission benchmarks to categorize schools into three tiers: Reach, Match, and Safety.
- It generates a detailed report highlighting specific majors, last year's cut-off rankings, and risk assessments such as the necessity of 'major adjustment' to avoid disqualification.
- Users can engage in deep-dive Q&A to compare specific institutions based on criteria like research labs, industry partnerships, and graduate school recommendation rates.
Academic Matching & Enrollment (form) Setup
To integrate this skill into your AI agent environment, use the following steps:
# Install the Openclaw CLI if not already present
npm install -g @openclaw/cli
# Add the academic matching skill
openclaw add skill form
Ensure your local database contains the latest university admission datasets for the current academic year.
Academic Matching & Enrollment (form) Data Schema & Taxonomy
The skill organizes data using a structured taxonomy to ensure high precision in matching:
| Field | Description | Example |
|---|---|---|
score_data |
Competitive exam results and rankings | 620 points, 3500th rank |
pref_location |
Preferred cities or regions | Beijing, Shanghai |
tier_classification |
Risk-based school categories | Reach, Match, Safety |
academic_metrics |
Research rates and subject ratings | A+ Evaluation, 25% admission rate |
Academic Matching & Enrollment (form) Advanced Features
- Multi-dimensional comparison of postgraduate research potential across different universities.
- Risk mitigation alerts for major-specific enrollment to prevent application 'slippage' (withdrawal due to score mismatches).
- Dynamic adjustment of recommendations based on evolving user preferences for specific industries like AI or Integrated Circuits.
- Seamless integration with other Openclaw Skills for broader career planning and research.
SKILL.md
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