Gaokao College Application Planner

Problem

In college application planning, raw scores can be misleading because test difficulty changes year to year. A stable province-wide ranking is a more useful anchor for comparing a student with historical admission data. This skill helps turn score, rank, subject choices, regional preferences, budget, and major constraints into a structured application strategy.

Workflow

It collects eight input dimensions in order. The first three are required: province + gaokao model + subject selection, total score + province rank, and physics/history or liberal-arts/science track; if any are missing, it pauses and asks. Recommended fields include region, family budget, interests, career goals, and special identities. It then applies the ranking method to match historical admission ranks, classify schools into reach, target, and safety tiers, and generate a complete plan. If the user supplies current-year undergraduate enrollment plans, it can convert the current rank into an equivalent historical rank using a simple adjustment formula or a nationwide supply-curve model.

Data and Output

The skill uses built-in admission datasets, school labels, multi-year backtests, and province-level professional-group data, while preferring official sources and stating data years. It defaults to public schools only and provides at least ten schools per tier, with rank ranges by major group. Reports are rendered as a self-contained HTML page covering student profile, rank positioning, medical constraints, tiered plans, school analysis, employment evaluation, and risk notes.

Limits

It does not guarantee admission, predict exact current-year cutoffs, or replace the student's final decision. For specific schools, users should rely on provincial exam authorities, official university pages, and the latest admission rules. If data are incomplete, contradictory, or outdated, the skill should flag the issue instead of filling gaps.