Phd copilot
A field-agnostic AI skill suite that automates PhD application research, outreach, and tracking via a shared, version-controlled knowledge base.
npx -y skills add bydeng01/phd-application-skill --skill phd-copilotAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
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Orchestrate the end-to-end PhD application process and route to the right sub-skill. Use this as the front door whenever the user expresses a broad PhD-application intent without naming a specific step — e.g. "help me apply for PhDs", "be my PhD application copilot", "where am I with my applications and what should I do next?", "I want to start applying to PhD programs", or "what's the next thing I should work on?". Surveys the knowledge base to see what stage each opportunity is at, recommends the highest-value next action, and kicks off the matching skill. Trigger for orientation, planning, or whole-pipeline requests; defer to the specific skill when the user already names a concrete task (e.g. "write a cold email to Prof X" → outreach-email).
SKILL.md
4.2 KB, as published. Nobody here has run it
PhD copilot (orchestrator)
This is the front door for someone who knows they want help with PhD applications but not which of the nine steps they need right now. Its value is orientation and momentum: look at where things actually stand, name the single most useful next move, and hand off to the skill that does it. It coordinates; it doesn't duplicate the specialized skills' work.
The pipeline it coordinates
position-discovery → professor-analyzer → opportunity-ranker → outreach-email
→ research-proposal / application-materials → application-tracker → interview-prep
Each step reads and writes the shared knowledge base, so progress is visible as files. The copilot's job is to read that state and figure out what's missing or what's next.
Step 1 — Survey the state
Read across the knowledge base to build a picture:
profile/profile.mdandprofile/cv-master.md— is the applicant's own profile filled in enough to drive everything else? If it's empty, that's almost always the first action.openings/— are there discovered opportunities?openings/_ranking.md— has anything been prioritized?professors/— which targets have been analyzed?applications/*/status.md— what stage is each application at?interactions/— any outreach sent, any follow-ups due?
Step 2 — Diagnose the next best action
Map the state to the pipeline and pick the highest-leverage next step. Heuristics:
- Empty profile → set up
profile/profile.mdandcv-master.mdfirst; everything downstream depends on it. - Profile but no openings/targets → run position-discovery (or analyze a professor the user already has in mind with professor-analyzer).
- Several analyzed targets, nothing prioritized → run opportunity-ranker.
- A ranked shortlist, no outreach → draft outreach for the top targets with outreach-email.
- Outreach sent / deadlines approaching → run application-tracker to surface what's due, missing, or overdue.
- An active application needing documents → application-materials / research-proposal.
- An interview scheduled → interview-prep.
When the user's request implies a specific step ("write a cold email", "rank these"), don't re-survey everything — just route to that skill. The copilot is for ambiguity and planning, not a tollgate on every action.
Step 3 — Recommend and hand off
Give the user a brief, honest status overview and a clear recommended next action (usually one, at most a few in priority order), then invoke the matching skill — keeping the applicant in control of anything that gets sent or submitted. If several things are genuinely parallel (e.g. analyze three professors), say so and offer to proceed.
For a recurring rhythm — a weekly "here's where you are and what's due" check — offer to set up a scheduled task that runs the survey and surfaces the week's actions. This turns the copilot into an ongoing assistant rather than a one-off.
Guardrails
Respect shared/references/ethics.md across everything it coordinates: draft-never-send,
ground in real material, favor focused effort over mass applications. The copilot should make
the process feel manageable and honest — surfacing real next steps and real status, never
manufacturing false progress or urgency. When the knowledge base is too empty to advise well,
the right move is to help the applicant set up their profile, not to guess.