study-os-thesis

Build a deep in-session student research profile through an interview about interests, taste, skills, constraints, and thesis preferences. Use when asked to understand a student before generating research proposals, infer a thesis profile, prepare matching inputs, or turn course/interests text into a structured profile without storing private data.

Design, review, or improve portable Agent Skills with SKILL.md files. Use when asked to create a new skill, split an agent workflow into skills, write skill instructions, evaluate skill portability across agents such as Codex, Claude Code, OpenCode, or similar clients, or generate a skill package for thesis-finder workflows.

Draft concise, high-signal first-contact messages to potential thesis advisors using a deep student profile, a concrete research-proposal sketch, relevant papers, and chair fit evidence. Use when asked to write or improve an email to a professor, PhD student, postdoc, lab, chair, or thesis supervisor.

Find, rank, and summarize recent research papers for thesis discovery. Use when a student or coding agent asks for papers, publications, related work, recent research directions, literature leads, or thesis ideas based on interests, courses, skills, chairs, supervisors, or research areas.

Find university teaching chairs, research groups, professors, and possible thesis supervisors only after a sufficiently deep student research profile exists. Use when asked which chair, lab, professor, PhD student, research group, or university supervisor fits a topic, course profile, paper list, thesis direction, or research proposal.

Generate precise research-proposal sketches, thesis questions, and advisor-ready conversation starters from a deep student profile, recent paper evidence, and chair or supervisor matches. Use when asked for research proposals, thesis proposal ideas, proposal directions, topic hypotheses, or questions to discuss with a potential advisor.

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.

Optionally maintain secondary thesis-finder Markdown data by fetching recent OpenAlex works for reviewed researchers and regenerating reviewable paper indexes. Use when running GitHub Actions, monthly maintenance, or manual data refresh workflows; not for student-facing thesis advice.