| name | match-thesis-advisors |
| description | Match a deep student research profile to professors, chairs, researchers, and recent papers using the professor seed index plus native web research. Use when asked to find proposal-relevant advisors, rank chairs or supervisors, compare matches, explain fit, or prepare evidence for precise research proposals without a database or UI. |
Match Thesis Advisors
Rank possible thesis advisors by combining the student's in-session research profile with the professor seed index and evidence gathered from official web sources. Treat the ranking as input to research-proposal generation, not as the final product.
Workflow
- Build or reuse a deep student profile. If the user only gave broad interests or one short answer batch, use
build-student-profile first and ask the next 3-5 coaching questions.
- Read
../find-university-chairs/references/professors/INDEX.md for professor names and official starting URIs.
- Use
find-university-chairs and find-recent-papers to gather current public evidence with the active agent's native websearch/browser tools.
- Score candidates qualitatively by proposal fit, research taste fit, evidence freshness, prerequisite fit, and risk.
- Return a ranked shortlist with reasons, caveats, backup options, and proposal hooks.
Output
For each match include:
- chair/lab and relevant person
- fit summary
- evidence from official pages or publication sources
- matching papers or research areas
- prerequisites and preparation
- risks or caveats
- proposal hooks that could become research questions
- suggested next action
End with 2-3 backup directions if the top matches are too competitive or uncertain.
Rules
- Do not produce advisor rankings from a shallow profile or after only one brief question batch. Ask profile-building questions first.
- Do not invent supervision capacity, open topics, quotas, team sizes, citations, or willingness to supervise.
- Distinguish "strong research fit" from "confirmed available thesis topic".
- Do not treat old bundled chair, researcher, or paper profiles as the primary source.
- If websearch/browser tools are unavailable, say that advisor matching can only use the professor seed names and URIs until the user provides page contents or enables browsing.
- Do not depend on the old UI, backend API, database, Docker, Celery, or FastAPI app.
