SISU Research Copilot

Overview

Generate a self-contained, interactive HTML web application that serves as a
university research copilot for SISU (Shanghai International Studies University)
students. The copilot helps students discover and navigate research opportunities
across campus — professors, research groups, labs, courses, seminars, and student
organizations — tailored to their interests, academic background, completed
courses, and career goals.

Key features of the generated app:

1. Natural-language search — Students type queries like "I want to do
   machine learning research" and the app surfaces all relevant opportunities.
2. Student profile builder — Year, department, interests, completed courses,
   skills, career goals. Saved to localStorage.
3. Recommendation engine — Scores every opportunity against the student
   profile and explains why each match is relevant (interest alignment,
   prerequisite completion, career goal fit, skill match).
4. Gap analysis — Identifies missing prerequisite courses and skills for a
   target research area.
5. Personalized path planner — Generates a step-by-step roadmap from
   foundation courses through to advanced research engagement.

When to Trigger

• User asks for a research guide, research assistant, or research copilot for SISU
• User asks "who should I talk to for [research area] at SISU"
• User wants to find research opportunities, labs, or professors at SISU
• User wants a personalized research path or roadmap
• User asks about SISU research ecosystem, faculty, or student organizations

Workflow

Step 1: Research the SISU Academic Ecosystem

Search the web for current information about SISU's research landscape. Consult
references/research-ecosystem-data.md for pre-compiled data on departments,
labs, faculty, courses, seminars, and student organizations, and supplement with
fresh web research to keep information current.

Key data to collect:

• Research institutes & labs — Name, director, research areas, facilities,
  campus location, website
• Professors — Name, department, research areas, email, key publications or
  projects, whether they accept student researchers
• Courses & programs — Course name, department, credits, prerequisites,
  research areas it supports
• Seminars & events — Name, frequency, organizer, topics, how to join
• Student organizations — Name, focus, activities, how to join, research
  areas connected to
• Research areas — Name, description, related departments, prerequisite
  courses, required skills

Search in both Chinese and English. SISU's main research-oriented campuses are
Songjiang (松江) and Hongkou (虹口).

Step 2: Compile and Structure Data

Organize the researched information into the data structures the app needs:

1. researchAreas[] — Each with id, name (CN/EN), description, departments,
   prerequisiteCourses[], requiredSkills[]
2. opportunities[] — Professors, labs, courses, seminars, organizations.
   Each with id, type, name, department, researchAreas[], description,
   prerequisites[], contactInfo, campus
3. courses[] — Course catalog for the profile builder's course selector
4. skills[] — Skill catalog for the profile builder's skill selector

If information is unavailable or uncertain, mark it as "信息待更新" rather than
fabricating details.

Step 3: Generate the HTML Application

Use the HTML template at assets/research-copilot-template.html as the base.
This template contains a complete, working app with:

• SISU color scheme (blue #003F88, gold #C8A951)
• 5 tabs: Home (search), My Profile, Discover, Recommend, Path Planner
• Recommendation scoring algorithm (interest 60%, prerequisites 20%, career 15%,
  skills 5%)
• Gap analysis with prerequisite checking
• Step-by-step path generation
• localStorage persistence for student profiles
• Fully responsive, self-contained (no external dependencies)

Customize the template:

1. Read the template file.
2. Update the data arrays (researchAreas, opportunities, courses, skills) with
   the researched data from Step 2.
3. Ensure all data is embedded in the JavaScript — no external API calls.
4. Keep all CSS inline within the <style> tag.
5. Write the final HTML to the workspace output directory (e.g.,
   sisu-research-copilot.html).

Step 4: Present the Result

Present the generated HTML file using present_files so the user can preview
it in the browser. Include a brief summary of:

• Number of research areas, professors, labs, courses, seminars, and orgs
• Key features available in the app
• Example use case (e.g., "I want to do ML research" flow)

Language

The app should be bilingual: primarily in English (as it targets international
students and English-medium programs) with Chinese translations for names,
departments, and key terms. If the user requests a specific language, follow
their preference.

Quality Checklist

Before presenting the app, verify:

• [ ] All researched opportunities are included in the data arrays
• [ ] Each opportunity has type, name, department, research areas, and description
• [ ] Research areas have prerequisite courses and required skills defined
• [ ] Search functionality works for natural-language queries
• [ ] Profile builder saves and loads from localStorage
• [ ] Recommendation engine produces match scores and explanations
• [ ] Gap analysis correctly identifies missing prerequisites
• [ ] Path planner generates a complete step-by-step roadmap
• [ ] HTML is self-contained (no external CSS, JS, or image dependencies)
• [ ] Page renders correctly and is mobile-responsive
• [ ] SISU color scheme is applied consistently
• [ ] Missing information is marked as "信息待更新" rather than guessed