Agent skill

Grad School Guide

by wentorai in wentorai/research-plugins

Practical advice for thriving in PhD programs and academic research

MITAuto-check passedResearch & Science

Install Grad School Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill grad-school-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins grad-school-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/methodology/grad-school-guide .claude/skills/grad-school-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
grad-school-guide
GitHub stars
298
Used in
1 other repo
Token cost
~2.1k tokens
SKILL.md length
874 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Practical advice for thriving in PhD programs and academic research

  • Works in 5 steps: Survey the landscape. Read 20-30 recent… → Identify gaps. Look for "future work"… → Narrow progressively. Topic -> Sub-topic… → …
  • Tasks that involve Hypothesis generation
  • SKILL.md covers Overview, Formulating Research Questions, Developing Hypotheses and… and Managing Your Advisor and…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grad School Guide is an agent skill from wentorai/research-plugins. Practical advice for thriving in PhD programs and academic research

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Hypothesis generation. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Hypothesis generation

Example prompts

  • “/grad-school-guide”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Survey the landscape. Read 20-30 recent papers in your area.
  2. Identify gaps. Look for "future work" sections and limitations.
  3. Narrow progressively. Topic -> Sub-topic -> Specific question.
  4. Phrase as a question. "Does X improve Y compared to Z in context W?"
  5. Test with the "so what?" check. If the answer is yes or no, does it matter?

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com
    • karpathy.github.io
    • stearnslab.yale.edu
    • bigaidream.gitbooks.io
    • microsoft.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Grad School Guide loads about 2.1k tokens when it runs. Until then it costs about 21 tokens; SKILL.md has 874 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~21
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 874 words, ~2,122 tokens.

Download SKILL.mdSave it as .claude/skills/grad-school-guide/SKILL.md (or your agent's skills folder).
name
grad-school-guide
description
Practical advice for thriving in PhD programs and academic research

Graduate School Research Guide

Overview

Graduate school -- particularly a PhD program -- is a multi-year commitment that demands not only technical skills but also effective research methodology, advisor management, paper writing strategies, and career planning. The difference between thriving and merely surviving often comes down to having the right mental models and practical frameworks for the research process.

This guide distills wisdom from the awesome-grad-school repository (450+ stars, maintained by the Polo Club of Data Science at Georgia Tech) and supplements it with actionable frameworks for formulating research questions, developing hypotheses, structuring a theoretical framework, and managing the end-to-end research lifecycle. The advice here applies broadly across STEM and social-science disciplines.

Whether you are an incoming PhD student, a mid-program researcher seeking to improve your productivity, or an advanced candidate preparing for the job market, this skill provides concrete tools for each stage of the journey.

Formulating Research Questions

A strong research question is the foundation of any good paper. It should be specific, answerable, and significant.

The FINER Criteria
CriterionDescriptionExample Check
FeasibleCan be answered with available resourcesDo you have the data, compute, and time?
InterestingEngages the research communityWould peers read this at a top venue?
NovelNot already answeredHas OpenAlex/CrossRef search been done?
EthicalFollows research ethics standardsDoes it require IRB approval?
RelevantAdvances the field meaningfullyDoes it connect to open problems?
From Topic to Question: A Step-by-Step Process
  1. Survey the landscape. Read 20-30 recent papers in your area.
  2. Identify gaps. Look for "future work" sections and limitations.
  3. Narrow progressively. Topic -> Sub-topic -> Specific question.
  4. Phrase as a question. "Does X improve Y compared to Z in context W?"
  5. Test with the "so what?" check. If the answer is yes or no, does it matter?

Example progression:

Topic:    Natural language processing
Sub-topic: Low-resource language translation
Gap:      Few-shot methods underperform on morphologically rich languages
Question: Can morphological decomposition improve few-shot translation
          quality for agglutinative languages?

Developing Hypotheses and Theoretical Frameworks

From Question to Hypothesis

A hypothesis is a testable, falsifiable prediction derived from your research question:

  • Directional: "Method A will achieve higher BLEU scores than Method B on agglutinative language pairs."
  • Non-directional: "There will be a significant difference in BLEU scores between Method A and Method B."
  • Null (H0): "There is no significant difference in BLEU scores between Method A and Method B."
Building a Conceptual Model

A conceptual model maps the relationships between your key variables:

Independent Variable      Moderator        Dependent Variable
[Morphological           [Language         [Translation
 Decomposition]  ------> Typology]  -----> Quality (BLEU)]
        |                                        ^
        |          Mediator                      |
        +-------> [Vocabulary                    |
                   Coverage] --------------------+

Document your conceptual model with:

  1. Constructs: The abstract concepts (e.g., "translation quality").
  2. Operationalizations: How you measure each construct (e.g., BLEU, COMET scores).
  3. Relationships: Hypothesized causal or correlational links.
  4. Boundary conditions: Where the model applies and where it does not.

Managing Your Advisor and Research Workflow

Communication Frameworks

The Weekly Update Email:

Subject: Weekly Update - [Your Name] - Week of [Date]

1. ACCOMPLISHED THIS WEEK
   - Completed experiment X with results Y
   - Drafted Section 3 of the paper

2. BLOCKERS
   - Need access to GPU cluster for large-scale runs
   - Waiting on co-author feedback on Section 2

3. PLAN FOR NEXT WEEK
   - Run ablation study on components A, B, C
   - Begin writing Section 4

4. DISCUSSION ITEMS FOR MEETING
   - Should we include dataset Z in our evaluation?
   - Timeline for submission to [Conference]
Research Productivity System
PracticeCadenceTool
Daily progress logEnd of each dayPlain text file or Notion
Literature reading2-3 papers/weekZotero + annotations
Experiment trackingPer runWeights & Biases or MLflow
Writing30 min daily minimumLaTeX or Markdown
Advisor meeting prepWeeklyStructured update email
Research talksMonthly (lab meeting)15-min presentation

Paper Writing Strategy

The Reverse-Outline Method
  1. Write bullet points for each section (1-2 sentences per paragraph).
  2. Order bullets by logical flow.
  3. Expand each bullet into a full paragraph.
  4. Revise for transitions and coherence.
Show full SKILL.md (346 more words)Show less
Section-by-Section Tips
  • Introduction: Open with a concrete problem, not "In recent years..."
  • Related Work: Organize by theme, not chronologically. Compare approaches, do not just list them.
  • Methods: Write so a competent researcher can reproduce your work.
  • Results: Lead with the most important finding. Use tables for exact numbers, figures for trends.
  • Discussion: Address limitations honestly. Reviewers respect self-awareness.
Handling Rejection

Paper rejection is a normal part of academic life. The awesome-grad-school community recommends:

  1. Allow 24-48 hours to process emotions. Do not respond immediately.
  2. Categorize each review comment as: (a) valid and fixable, (b) valid but requires new experiments, (c) misunderstanding to clarify, or (d) subjective disagreement.
  3. Create an action plan for addressing category (a) and (b) items.
  4. Resubmit to the next venue with improvements, not just the same paper.

Career Planning

Timeline for a 5-Year PhD
YearFocusMilestones
1Coursework + explorationPass qualifying exam, identify area
2First project + first paperSubmit to workshop or conference
3Core research + publications1-2 papers at top venues
4Thesis writing + job market prepDraft thesis proposal, internship
5Defense + job searchSubmit thesis, interview
Building Visibility
  • Maintain a personal academic website with publications and blog posts.
  • Present at conferences and workshops.
  • Share preprints on arXiv before publication.
  • Engage constructively on academic social media.

Best Practices

  • Start writing early. The paper is not separate from the research -- writing clarifies thinking.
  • Build a library of reusable code. Experiment templates, plotting scripts, and data loaders save hours on each project.
  • Invest in relationships. Collaborators, mentors, and peers are your most valuable resource.
  • Take care of your health. PhD burnout is real. Set boundaries and maintain activities outside research.
  • Read broadly. Some of the best ideas come from adjacent fields.
  • Track your accomplishments. Maintain a running CV and a "brag document" for annual reviews and job applications.

References

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/research/methodology/grad-school-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Grad School Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Questions about Grad School Guide

What does Grad School Guide do?

Practical advice for thriving in PhD programs and academic research. Grad School Guide is an agent skill from wentorai/research-plugins.

When should I use Grad School Guide?

Grad School Guide fits situations like: tasks that involve Hypothesis generation.

How do I install Grad School Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill grad-school-guide -a claude-code`. Or copy the skill folder (skills/research/methodology/grad-school-guide in wentorai/research-plugins) into .claude/skills/grad-school-guide in your project. Claude Code loads it when a task matches its description.

How do I install Grad School Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill grad-school-guide -a codex`. Or copy the skill folder (skills/research/methodology/grad-school-guide in wentorai/research-plugins) into .agents/skills/grad-school-guide in your project. Codex loads it when a task matches its description.

Can I use Grad School Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill grad-school-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/grad-school-guide, .gemini/skills/grad-school-guide, .github/skills/grad-school-guide and .opencode/skills/grad-school-guide in your project.

What does Grad School Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Grad School Guide is instructions for the agent only.

Does Grad School Guide access the network?

SKILL.md names 5 domains. As links in the text: github.com, karpathy.github.io, stearnslab.yale.edu, bigaidream.gitbooks.io and microsoft.com. This is read from the text; nothing was executed.

Is Grad School Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Grad School Guide use?

Grad School Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Grad School Guide use?

About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Grad School Guide?

Skills that share tags, products or a category with Grad School Guide: Hypothesis Generation (spacering-net/codeg, 3.9k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars), Hypothesis Generation (K-Dense-AI/claude-scientific-writer, 2.4k stars) and Good Question (Rimagination/good-question, 305 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grad School Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.