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advisor-agent

Analyze and synthesize intelligence on potential PhD supervisors from academic metrics and reviews.

10|4|Updated Feb 25, 2026
Search Tags:#academic research#career planning#phd advisor#supervisor selection#lab intelligence#reputation check
One-click install
npx skills add https://github.com/Lirsakura/skills-hub --skill advisor-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: advisor-agent
Source: https://github.com/Lirsakura/skills-hub/tree/main/skills/advisor-agent
Command: npx skills add https://github.com/Lirsakura/skills-hub --skill advisor-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps prospective graduate students make informed decisions about choosing a PhD supervisor by providing comprehensive, data-driven intelligence on potential advisors, mitigating the risk of academic career pitfalls.

Core Features & Use Cases

  • Comprehensive Advisor Profiling: Gathers data on academic standing, publication record, lab environment, and student reviews.
  • Risk Assessment: Identifies potential red flags (e.g., poor student reviews, academic misconduct) and positive indicators (e.g., strong mentorship, good student outcomes).
  • Use Case: A student is considering two potential supervisors. This Skill can generate detailed reports for both, allowing the student to compare their research output, lab culture, and alumni career paths side-by-side.

Quick Start

Generate a full investigation report for Professor John Doe at Example University.

Frequently Asked Questions about advisor-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check a potential PhD advisor's reputation and lab dynamics before applying?▼

This skill evaluates a PhD supervisor by cross-referencing academic metrics, publication trends, collaboration networks, and student reviews to generate structured reports on advisor profiles and lab dynamics.

What is the best way to compare two potential PhD supervisors side-by-side?▼

You can generate detailed advisor profiles for both candidates, enabling side-by-side comparison of research output, lab culture, alumni career paths, and potential red flags.

Can I identify academic misconduct or poor mentorship red flags when selecting a supervisor?▼

Yes, risk assessment features identify red flags like poor student reviews or academic misconduct, while also highlighting positive indicators such as strong mentorship and good alumni outcomes.

How do I evaluate a professor's publication trends and collaboration networks for my PhD application?▼

You evaluate a professor's publication trends and collaboration networks by cross-referencing academic metrics to analyze research quality, output frequency, and professional relationships within the academic ecosystem.

Does this advisor selection process require any specific academic databases or APIs to function?▼

No specific external APIs or academic databases are required as dependencies. The skill cross-references available academic metrics and student review data to synthesize advisor intelligence.

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