An operating system for research-oriented coding agents.
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PhD-Zero is a repository of reusable skills for AI research work. The point is not to make an agent sound smart for one turn. The point is to give it a workflow it can actually follow: plan the task, gather evidence, run experiments, keep context, ask for human review when needed, and write results down in a form another person can inspect.
The same skill library is exposed to different runtimes. Codex-style agents read workspace rules from AGENTS.md. Claude Code sees a mirrored discovery layer under .claude/skills/. The actual source of truth lives in .agents/skills/.
If you just want to see whether the repo is wired correctly, do this:
git clone https://github.com/TenureAI/PhD-Zero.git
cd PhD-Zero
find .agents/skills -mindepth 1 -maxdepth 1 -type d
find .claude/skills -mindepth 1 -maxdepth 1 -type lThose two commands should list the same skill names. If they do, the shared skill layer is in place.
From there:
- Read
AGENTS.mdto understand the workspace rules used by Codex-style agents. - Inspect
.agents/skills/if you want the canonical skill implementations. - Inspect
.claude/skills/if you want to verify the Claude Code mirror.
If you prefer a landing page over the raw repository view, there is also a static site under docs/index.html.
The repository is intentionally small. It does not try to be a benchmark suite, a framework, and a demo app all at once. It is mostly a skill library plus the rules that tell agents how to use it.
.
├── AGENTS.md
├── REPO_CONVENTIONS.md
├── .agents/skills/ # canonical skill definitions
├── .claude/skills/ # Claude Code mirror layer
├── .github/workflows/ # repository validation
├── assets/ # shared visual assets
└── docs/ # static landing page
The CI in this repo checks that the skill directories under .agents/skills and .claude/skills stay in sync, and that every tracked skill has a readable SKILL.md.
The current skill set covers the basic loop of a research-oriented agent:
| Skill | What it is for |
|---|---|
run-governor |
Stage control, run discipline, and execution policy |
research-workflow |
The default loop for non-trivial research tasks |
research-plan |
Turning an open-ended goal into a concrete plan |
deep-research |
External search, literature comparison, and synthesis |
experiment-execution |
Running code, debugging, and experiment execution |
memory-manager |
Working state and reusable memory |
project-context |
Project-specific runtime context and conventions |
human-checkpoint |
Human review for risky or expensive decisions |
paper-writing |
Drafting and revising research artifacts |
That list will probably grow, but the idea is stable: break research into pieces that can be reused instead of trying to solve everything with one giant prompt.
PhD-Zero is for people who are already using coding agents in research or engineering-adjacent work and want more discipline around the process. If you care about literature review, experiment planning, reproducibility, or keeping an agent from improvising its way through a long task, this repo is meant to be useful. If you just want a flashy demo, it is probably not the right project.
Contributions are welcome, especially in three areas:
- new skills that fit the repository's scope
- tighter workflows for the existing skills
- validation and examples from real usage
Before opening a PR, check REPO_CONVENTIONS.md. This repo keeps reusable skill content in version control and keeps task-specific logs or run artifacts out.
PhD-Zero is shaped by the broader ecosystem around coding agents, research tooling, and writing support. In particular, the repository draws useful ideas from projects that treat workflows as first-class artifacts rather than one-off prompts.
We also want to acknowledge:
These are not runtime dependencies here, but they were useful references when thinking about writing quality and reusable editing guidance.
If PhD-Zero is useful in your workflow or research, you can cite it as:
@misc{phd_zero_github,
author = {TenureAI Contributors},
title = {PhD-Zero: An Operating System for Research-Oriented Coding Agents},
year = {2026},
howpublished = {\url{https://github.com/TenureAI/PhD-Zero}},
note = {GitHub repository}
}