Research proposal
Skill bydeng01/phd-application-skill/skills/research-proposal
A field-agnostic AI skill suite that automates PhD application research, outreach, and tracking via a shared, version-controlled knowledge base.
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Draft a PhD research proposal or research plan aligned to a specific lab's current and future agenda. Use this whenever the user needs a research proposal, project proposal, research statement, or research plan for a PhD application or a particular professor — e.g. "write a research proposal for the Smith lab", "I need a 2-page research plan for my Cambridge application", "draft a PhD proposal on diffusion models for this professor", or "help me turn my interests into a proposal that fits her work". Builds a concrete, feasible project at the intersection of the lab's open problems and the applicant's strengths, grounded in real prior work, as a draft the applicant authors and refines. Trigger whenever the intent is to produce a research proposal tied to a PhD opportunity.
SKILL.md
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Research proposal
A PhD research proposal does two jobs at once: it shows the applicant can think like a researcher (frame a real problem, propose a credible approach, see the obstacles), and it demonstrates specific fit with the target lab. A proposal that could be sent to any lab in the field fails the second job. The aim here is a proposal that sits precisely at the intersection of where the lab is heading and what the applicant can credibly do — concrete enough to be evaluated, modest enough to be feasible in a PhD, and clearly the applicant's own thinking.
Step 1 — Load the lab and the applicant
Read the professor's profile at knowledge-base/professors/<slug>.md, focusing on
Research agenda & open problems and recent publications — the proposal must connect to
the lab's trajectory, not its past. Read the applicant's profile/profile.md,
profile/research-statement.md (if present), and profile/cv-master.md for the methods and
results they can credibly build on.
If no professor profile exists, run professor-analyzer first; a proposal not anchored in the lab's real open problems is just a generic essay. Note any program constraints the user gives (page/word limit, required structure) and follow them.
Step 2 — Find the intersection
The core intellectual work: identify a problem that is (a) genuinely open in the lab's agenda, (b) something the applicant's background gives them a credible angle on, and (c) scoped to a PhD. Avoid both extremes — a problem the lab has already solved, or a moonshot no student could make progress on. Prefer a specific, well-motivated question over a broad theme. It's fine to propose one main thrust with one or two extensions rather than a sprawl.
Step 3 — Draft the proposal
Use this structure unless the program specifies otherwise. Keep it tight; most PhD proposals are 1–3 pages.
# <Working title>
## Motivation & problem
The specific problem, why it matters, and the gap in current work (cite real papers —
the lab's and the field's). 1–2 paragraphs.
## Background & related work
What's been done, including the lab's relevant work, and what's still open. Show you've
read the literature, including the professor's. Cite specific real papers.
## Proposed research
The core idea and approach. Concrete enough to picture the first experiments. Break into
1–3 aims/phases. State hypotheses and what success would look like.
## Methods & feasibility
How you'd actually do it, what you'd build on (your own skills/results + the lab's
resources), and why it's achievable in a PhD timeframe.
## Risks & alternatives
The main ways it could go wrong and your fallback directions. Including this signals
research maturity — proposals that pretend nothing can fail read as naive.
## Fit with the lab
Why *this* lab: the specific resources, datasets, methods, or expertise that make the
project viable here and not just anywhere. Tie to the professor's open problems by name.
## References
Real citations only.
Step 4 — Keep it honest and the applicant's own
Cite only real papers, and never claim preliminary results the applicant doesn't have —
"preliminary experiments show X" is a fabrication unless X actually happened. Where the
proposal would benefit from a specific the applicant must supply (a dataset they have, a
result from their MS thesis, a concrete prior finding), mark it with [brackets] rather
than inventing it. The proposal should read as the applicant's thinking sharpened, not as
generic AI prose — match the voice in their research statement.
Step 5 — Save and hand off
Write the proposal to knowledge-base/applications/<id>/proposal.md. Summarize for the user
the core idea, why it fits this lab, and which [brackets] they need to fill. For a
submission-grade document (PDF/Word with formatting), hand off to the pdf or docx skill.
If the proposal surfaces a strong angle, suggest it can seed the outreach-email hook or
the application-materials SOP so the application tells one coherent story.
Guardrails
Follow shared/references/ethics.md. The proposal represents the applicant's research
judgment to people deciding whether to mentor them for years — fabricated results or a
misrepresented grasp of the literature are both dishonest and easily caught in interview.
Aim for a strong, real, feasible draft the applicant can stand behind and defend.