awesome student ai skills

University students often struggle with the rigid structure and high stakes of official applications for scholarships, research funding, and competitions. A single formatting error or missing section can disqualify a high-potential project.

What it does

• Automatic Routing uses a 5-level decision tree to identify which of the 35 specific application types the user needs.
• Smart Information Gathering interviews users for specific facts, awards, and metrics to ensure data-driven content.
• Academic Document Generation produces professionally formatted docx and PDF files using institution-specific templates.
• Compliance Pre-checking simulates expert review panels and runs n-gram plagiarism detection before finalization.
• Institutional Adaptation adjusts margins, fonts, and structures for specific universities like PKU, Tsinghua, and ZJU.

How it works

1. The user provides a prompt or an existing draft regarding a specific application or competition.
2. The dispatcher.py module analyzes the intent and routes the request to one of the 9 major categories.
3. The skill prompts the user for missing evidence, such as specific GPAs, award names, or project milestones.
4. The system generates a structured document and runs it through the review_simulator.py for quality assurance.

Frameworks & tools

The skill utilizes a custom Python toolkit including docx_common.py for formatting, pdf_export.py for dual-engine conversion, and specialized JSON-based school templates.

Why this beats prompting it yourself

Generic prompts often produce "fluff" that fails academic scrutiny or ignores specific institutional formatting rules. This skill enforces strict structural compliance and factual density required for high-stakes government and university submissions.

Use cases

• Drafting a National Scholarship application focused on high-impact academic achievements.
• Generating a "Challenge Cup" or "Internet+" business plan with technical roadmaps.
• Preparing formal Youth League or Party membership reports and transfer requests.
• Writing social survey proposals for "Three Rural Areas" summer volunteer programs.

Known limitations

Does not support creative fiction or factual embellishment; users must provide verifiable data. Requires local Python environment for direct CLI execution of utility scripts.