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kaoyan-navigator

Analyze Chinese graduate school admission data to evaluate program competitiveness and admission risks.

18|2|Updated Jun 8, 2026
Search Tags:#ai agent#data analysis#academic research#decision support#kaoyan#graduate admission
One-click install
npx skills add https://github.com/mcxiaoxiao/kaoyan-navigator-skill --skill kaoyan-navigator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kaoyan-navigator
Source: https://github.com/mcxiaoxiao/kaoyan-navigator-skill/tree/main
Command: npx skills add https://github.com/mcxiaoxiao/kaoyan-navigator-skill --skill kaoyan-navigator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill solves the information asymmetry and data fragmentation in Chinese graduate school admissions by providing a structured, evidence-based research workflow that prevents users from relying on unreliable "fortune-telling" predictions.

Core Features & Use Cases

  • Structured Research: Normalizes research objects (school, college, major, year) to ensure data integrity and prevent cross-contamination of statistics.
  • Evidence-Based Analysis: Evaluates risks like "score inflation," "enrollment cuts," and "recommendation squeeze" using a rigorous, multi-dimensional decision model.
  • Use Case: When a student is unsure if a specific computer science program is a "trap," the Skill aggregates official data from the past three years, calculates the actual competition level, and provides a risk assessment based on verifiable sources rather than social media rumors.

Quick Start

Use the kaoyan-navigator skill to analyze the 2027 admission prospects for the computer science program at your target university by searching for official historical data and identifying any missing information.

Frequently Asked Questions about kaoyan-navigator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I assess graduate admission risk for a specific Chinese university program?▼

Evaluating graduate admission risk involves analyzing historical test scores, enrollment quotas, and recommendation ratios from official sources to identify score inflation, enrollment cuts, and recommendation squeeze before applying.

What is the best way to analyze Chinese graduate school test score trends?▼

Analyzing test score trends requires a structured research workflow that aggregates official institutional admission data over multiple years, calculates actual competition levels, and verifies data provenance to identify score inflation.

Can I use historical enrollment data to identify graduate admission traps?▼

Yes, historical enrollment data identifies admission traps by calculating actual competition levels from official test scores and enrollment quotas over the past three years, providing a verifiable risk assessment.

Does this graduate admission analysis rely on official data or social media predictions?▼

This graduate admission analysis relies strictly on official institutional sources for data provenance and source verification, explicitly preventing reliance on unreliable social media predictions or fortune-telling forecasts.

What limitations exist when researching graduate admission quotas and recommendation ratios?▼

Limitations include potential missing information in official historical data, requiring you to normalize research objects by school, college, major, and year to prevent cross-contamination of statistics and ensure data integrity.

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