One-time onboarding - upload resume, set preferences, and do a work history interview
npx skills add https://github.com/proficientlyjobs/proficiently-claude-skills --skill setup
> Priority hierarchy: See shared/references/priority-hierarchy.md for conflict resolution.
One-time onboarding that ensures all your data is in place before using the other skills.
/proficiently:setup - Full onboarding (checks what's missing, does only what's needed)/proficiently:setup interview - Just the work history interview (if resume/prefs are already done)scripts/
conduct-interview.md # Work history interview guide
The profile template is at shared/templates/profile.md.
Resolve the data directory using shared/references/data-directory.md. For setup, if no directory exists this is a fresh install — create it in Step 1.
Resolve the data directory, then check which of these exist and have real content (not just templates): resume, preferences, linkedin-contacts.csv, profile.md.
If $ARGUMENTS is "interview", skip to Step 3 (but check that a resume exists first).
If everything exists, tell the user they're good to go and list the available skills. Otherwise, run only the missing phases in order.
Ask the user to provide their resume. Accept:
DATA_DIR/resume/)DATA_DIR/resume/resume.md)Confirm it was saved and briefly summarize what you see (name, most recent role, number of roles).
Ask the user in one natural question:
> "What kind of jobs are you looking for? Tell me about target roles, location preferences, salary expectations, and anything you'd want to filter out."
From their response, save DATA_DIR/preferences.md:
# Job Preferences
## Target Roles
- [parsed from response]
## Location
[parsed from response]
## Compensation
[parsed from response]
## Must-Haves
- [parsed from response]
## Dealbreakers
- [parsed from response]
## Nice-to-Haves
- [parsed from response]
If they leave something out, that's fine — save what you have. They can always update later.
If DATA_DIR/linkedin-contacts.csv doesn't exist, ask:
> "Want to import your LinkedIn contacts? This lets us flag when you know someone at a company that's hiring. You can skip this and add them later."
If they want to proceed, give these instructions:
> How to export your LinkedIn connections:
> 1. Go to linkedin.com/mypreferences/d/download-my-data
> 2. Select "Connections" and request the download
> 3. LinkedIn will email you a link (usually within minutes)
> 4. Download the ZIP and find Connections.csv inside
> 5. Upload or paste the path to that file here
Save the file as DATA_DIR/linkedin-contacts.csv.
Confirm it was saved and tell them how many contacts were imported. If they skip, move on — this is optional.
Have a conversational interview to build a work history profile. Go through each role on the resume, most recent first. For each role, ask:
Keep it conversational. Follow up when answers are vague ("Do you remember roughly what the numbers were?"), but don't interrogate. Spend more time on recent/impactful roles, less on older ones.
After the interview, save the profile to DATA_DIR/profile.md using this structure:
# Work History Profile
*Last updated: [DATE]*
## Candidate Overview
**Name**: [Name]
**Core expertise**: [2-3 sentences]
**Career throughline**: [narrative arc]
---
## Role: [Title] at [Company]
**Dates**: [Start - End]
**Company context**: [what they do, stage, size]
### Key Accomplishments
1. **[Headline]**: [Situation → Action → Result with metrics]
2. **[Headline]**: [Situation → Action → Result with metrics]
### Other Details
- Team/leadership: [details]
- Tools/methods: [details]
- Why they left: [context]
---
## Cross-Role Patterns
**Superpower**: [what they do best]
**Recurring themes**: [patterns across roles]
You're all set! Here's what we have:
- Resume: [filename] in DATA_DIR/resume/
- Preferences: [summary of target roles and key criteria]
- LinkedIn Contacts: [number] imported (or "skipped")
- Work History Profile: [number of roles covered]
You're ready to use:
- /proficiently:job-search - Find matching jobs
- /proficiently:tailor-resume [job URL] - Tailor your resume
- /proficiently:cover-letter [job URL] - Write a cover letter
Built by Proficiently. Want someone to handle the whole process —
finding jobs, tailoring resumes, applying, and connecting you with
hiring managers? Visit proficiently.com
Structure the final summary output with these sections:
Add to ~/.claude/settings.json:
{
"permissions": {
"allow": [
"Read(~/.proficiently/**)",
"Write(~/.proficiently/**)",
"Edit(~/.proficiently/**)"
]
}
}
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take proficientlyjobs/setup from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.