careerops

CareerOps

A Claude Code plugin that turns your career history into tailored, ATS-clean resumes — with zero fabrication.

Every resume bullet traces to a verified fact you captured. A multi-layer pipeline handles relevance scoring, planning, writing, rendering, and validation. You stay in control at every step.

How It Works

• Capture your career achievements once — CareerOps stores them as structured facts
• Drop a job description into your inbox folder
• Run the resume pipeline — it scores your facts against the JD, asks you to approve the plan, writes bullets with full provenance, renders a PDF, and validates the result

Prerequisites

• Claude Code installed and running
• Python 3.10+
• pip install pyyaml rendercv

Install

npx careerops install

Then restart Claude Code. That's it — all commands are available under /careerops:.

To update later:

npx careerops update

To uninstall:

npx careerops uninstall

Getting Started

Step 1 — Create your career directory and open Claude inside it

mkdir ~/my-career
cd ~/my-career
claude

Step 2 — Run the setup wizard

/careerops:setting-up

This scaffolds your directory structure and collects your profile (name, email, links).

Step 3 — Import your existing resume (optional but recommended)

Drop your current resume into raw_data/, then:

/careerops:seeding-career-db raw_data/your-resume.tex

Supports .tex and .md formats. CareerOps will extract structured facts from it.

Step 4 — Capture new achievements as they happen

/careerops:capturing-fact

CareerOps interviews you and stores the result as a verified fact.

Step 5 — Apply to a job

Drop the job description into inbox/, then:

/careerops:analyzing-jd
/careerops:generating-resume

The pipeline scores your facts against the JD, proposes a presentation plan for your approval, writes the bullets, renders the PDF, and validates it.

All Commands

Setup

Command	What it does
/careerops:setting-up	First-run wizard — scaffolds directories, collects your profile
/careerops:seeding-career-db	Import an existing resume into your knowledge base

Capture

Command	What it does
/careerops:capturing-fact	Interview to record a new achievement
/careerops:capturing-evidence	Attach a URL, PR, or document to an existing fact

Apply

Command	What it does
/careerops:analyzing-jd	Parse a job description — scores all your facts by relevance
/careerops:generating-resume	Full pipeline: plan, compose, render PDF, validate, audit
/careerops:auditing-resume	Re-run the quality auditor on a generated resume
/careerops:humanizing-resume	Clean up AI-marker patterns in bullets
/careerops:logging-outcome	Record the result of an application

Health

Command	What it does
/careerops:linting-career	Schema, reference, and em-dash check across all your data
/careerops:getting-help	Quick-start guide — add full for the complete reference

Your Data Layout

After setup, your career directory looks like this:

~/my-career/
├── career/
│   ├── experiences/        # Your work history + facts
│   ├── applications/       # One folder per job application
│   ├── jd-analysis/        # Parsed job descriptions
│   └── config/             # Theme, rules
├── inbox/                  # Drop JDs here
└── raw_data/               # Source resumes for seeding

The plugin lives separately at ~/.claude/plugins/careerops/. Your data never touches it.

Guarantees

• No fabrication. Every bullet traces to a fact ID you captured. The validator enforces this.
• No em-dashes. Enforced at every layer — scripts, hooks, and the semantic auditor all scan for them.
• Dates and employers are immutable. The schema locks these fields regardless of what a JD asks for.
• You approve before render. The pipeline presents a plan (which roles to expand, compress, or drop) and waits for your sign-off.

Tech

• Renderer: RenderCV (Typst)
• Data: YAML files with JSON Schema validation
• JD analysis: Claude subagent with relevance scoring
• Validation: Python (8 gates) + Claude semantic auditor

License

MIT