# Phd Copilot

> >-

- **Type:** Skill
- **Install:** `agentstack add skill-bydeng01-phd-application-skill-phd-copilot`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [bydeng01](https://agentstack.voostack.com/s/bydeng01)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [bydeng01](https://github.com/bydeng01)
- **Source:** https://github.com/bydeng01/phd-application-skill/tree/main/skills/phd-copilot

## Install

```sh
agentstack add skill-bydeng01-phd-application-skill-phd-copilot
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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.md` and `profile/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.md` and `cv-master.md` first; 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.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [bydeng01](https://github.com/bydeng01)
- **Source:** [bydeng01/phd-application-skill](https://github.com/bydeng01/phd-application-skill)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-bydeng01-phd-application-skill-phd-copilot
- Seller: https://agentstack.voostack.com/s/bydeng01
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.