santifer/career-opsPublic

I spent months applying to jobs the hard way. So I engineered the system I wish I had.
Companies use AI to filter candidates. I just gave candidates AI to choose companies.
Now it's open source.

_{FEATURED IN}

740+ job listings evaluated · 100+ personalized CVs · 1 dream role landed

_{Also runs on any agent-skill-standard CLI. See Supported CLIs.}

career-ops (career-ops.org, also known as careerops) turns any AI coding CLI into a full job search command center. Instead of manually tracking applications in a spreadsheet, you get an AI-powered pipeline that:

• Evaluates offers with a structured evaluation -- blocks A-F scored across 5 weighted dimensions, plus block G, a separate posting-legitimacy assessment that never affects the 1-5 score
• Generates tailored PDFs -- ATS-optimized CVs customized per job description
• Scans portals automatically (Greenhouse, Ashby, Lever, company pages)
• Processes in batch -- evaluate 10+ offers in parallel with sub-agents
• Tracks everything in a single source of truth with integrity checks
• Researches companies and finds the right person to contact -- applications get you in the queue; research gets you a conversation

Important: This is NOT a spray-and-pray tool. career-ops is a filter -- it helps you find the few offers worth your time out of hundreds. The system strongly recommends against applying to anything scoring below 4.0/5. Your time is valuable, and so is the recruiter's. Always review before submitting.

career-ops is agentic: whichever AI coding CLI you choose navigates career pages with Playwright, evaluates fit by reasoning about your CV vs the job description (not keyword matching), and adapts your resume per listing.

Heads up: the first evaluations won't be great. The system doesn't know you yet. Feed it context -- your CV, your career story, your proof points, your preferences, what you're good at, what you want to avoid. The more you nurture it, the better it gets. Think of it as onboarding a new recruiter: the first week they need to learn about you, then they become invaluable.

Built by someone who used it to evaluate 740+ job offers, generate 100+ tailored CVs, and land a Head of Applied AI role. Read the full case study.

career-ops is the first reference implementation of the CareerOps Manifesto. read it. if it says what you believe, sign it. your signature becomes a commit.

Fastest way — one command:

npx @santifer/career-ops init

💡 npx ships with Node.js — it runs the installer once, without installing anything globally. No Node yet? Install it first. (Already using a Claude Code / Gemini / Codex CLI? Then you already have it.)

This clones the latest release into ./career-ops and installs dependencies. Then:

cd career-ops
claude   # or codex / qwen / opencode / agy / grok — open your AI CLI here

On first launch, career-ops walks you through setup — your CV, profile and target roles — just by chatting. Nothing to edit by hand.

git clone https://github.com/santifer/career-ops.git
cd career-ops && npm install
npx playwright install chromium   # only needed for PDF generation

# 2. Check setup
npm run doctor                     # Validates all prerequisites

# 3. Configure
cp config/profile.example.yml config/profile.yml  # Edit with your details
cp templates/portals.example.yml portals.yml       # Customize companies

# 4. Add your CV
# Create cv.md in the project root with your CV in markdown

# 5. Open your AI CLI in this directory
claude   # or codex / opencode / qwen / agy / grok

# Then ask your CLI to adapt the system to you:
# "Change the archetypes to backend engineering roles"
# "Translate the modes to English"
# "Add these 5 companies to portals.yml"
# "Update my profile with this CV I'm pasting"

# 6. Start using
# Paste a job URL or JD text to trigger auto-pipeline
# If your CLI supports slash commands, use /career-ops (or its CLI-specific alias)
# In Codex, ask for the same mode in plain language, e.g.:
# "Run the career-ops scan mode"
# "Run the career-ops pipeline mode for data/pipeline.md"
# "Run the career-ops pdf mode for the latest evaluated role"
# "Run the career-ops tracker mode and summarize the current statuses"

The system is designed to be customized by your AI coding CLI itself. Modes, archetypes, scoring weights, negotiation scripts -- just ask it to change them. It reads the same files it uses, so it knows exactly what to edit.

See docs/SETUP.md for the full setup guide, docs/RUNNING_ON_A_BUDGET.md for instructions on running career-ops cheaply using custom or local models, docs/AUTOMATION.md for scheduling recurring scans and a zero-token triage-to-shortlist recipe, docs/APPLY_AUTOFILL.md for details on the ATS auto-fill flow, and docs/FAQ.md for answers to common setup questions. Design principles live in ARCHITECTURE.md; runtime flows in docs/ARCHITECTURE.md.

career-ops supports Antigravity CLI natively, the same way it supports Claude Code and OpenCode. All slash commands are available through the shared skill entrypoint, using the same modes/*.md evaluation logic.

Google has transitioned consumer Gemini CLI access to Antigravity CLI. GEMINI.md is now a no-op compatibility guard so Antigravity does not duplicate the full project instructions when it reads both AGENTS.md and GEMINI.md.

# 1. Run in the career-ops directory
cd career-ops
agy

# 2. Use the unified /career-ops command with subcommands:
/career-ops "Senior AI Engineer at Anthropic..."
/career-ops pipeline
/career-ops scan
/career-ops pdf
/career-ops tracker

The skill is defined using the open standard in .agents/skills/career-ops/SKILL.md and symlinked/referenced for each supported CLI (e.g. .claude/, .cursor/, .qwen/, .antigravitycli/, .grok/).

career-ops supports Codex through the same shared router, but the invocation model is different from CLIs that auto-register slash commands. For the full guide, see docs/CODEX.md.

cd career-ops
codex

Slash commands are not guaranteed in Codex. If /career-ops is unavailable, ask Codex to run the mode directly in plain language:

Evaluate this JD with career-ops auto-pipeline: https://company.com/jobs/123
Run the career-ops scan mode and summarize new matches.
Run the career-ops pipeline mode for data/pipeline.md.
Run the career-ops pdf mode for the latest evaluated role.
Run the career-ops tracker mode and summarize the current statuses.

codex exec "Evaluate this JD with career-ops auto-pipeline: https://company.com/jobs/123"
codex exec "Run career-ops scan mode in this repo and summarize new matches."
codex exec "Run career-ops pipeline mode for data/pipeline.md."
codex exec "Run career-ops pdf mode for the latest evaluated role."
codex exec "Run career-ops tracker mode and summarize the current statuses."

career-ops supports Grok Build CLI natively, the same way it supports Claude Code and OpenCode. AGENTS.md is auto-loaded as project rules, and all slash commands are available through the shared skill entrypoint.

# 1. Run in the career-ops directory
cd career-ops
grok

# 2. Use the unified /career-ops command with subcommands:
/career-ops "Senior AI Engineer at Anthropic..."
/career-ops pipeline
/career-ops scan
/career-ops pdf
/career-ops tracker

For headless batch workers, use grok -p "prompt" (add --yolo to auto-approve tool executions).

# 1. Get a free API key at https://aistudio.google.com/apikey
cp .env.example .env
# Edit .env, set GEMINI_API_KEY=your_key_here

# 2. Install dependencies
npm install

# 3. Evaluate a job description
node gemini-eval.mjs "We are looking for a Senior AI Engineer..."
node gemini-eval.mjs --file ./jds/my-job.txt
node agent-inbox.mjs add "..."   # queue a request for the next session
npm run gemini:eval -- "JD text here"

Free tier: Both options work without billing. Native CLI uses Google OAuth; the API script uses gemini-3.6-flash (rate limits are model- and tier-dependent; see Google AI docs for current quotas).

career-ops uses a shared command router. In CLIs that register slash commands, it looks like this:

/career-ops                → Show all available commands
/career-ops {paste a JD}   → Full auto-pipeline (evaluate + PDF + tracker)
/career-ops scan           → Scan portals for new offers
/career-ops pdf            → Generate ATS-optimized CV
/career-ops cover          → Cover letter generator (paste JD or /career-ops cover {slug})
/career-ops email          → Formal application email draft (draft-only; never sends, submits, or clicks)
/career-ops batch          → Batch evaluate multiple offers
/career-ops tracker        → View application status
/career-ops apply          → Fill application forms with AI
/career-ops outcome        → Record application outcome & archive artifacts
/career-ops pipeline       → Process pending URLs
/career-ops contacto       → Find hiring manager / recruiter / peer + draft a ≤300-char LinkedIn message per contact type
/career-ops deep           → Generate a structured 6-axis research prompt (AI strategy, recent moves, culture, challenges, competitors, candidate angle)
/career-ops training       → Evaluate a course/cert
/career-ops project        → Evaluate a portfolio project

Or just paste a job URL or description directly -- career-ops auto-detects it and runs the full pipeline.

In Codex, slash commands are not guaranteed. Use the same mode names in a prompt instead, or call them from codex exec.

You paste a job URL or description
        │
        ▼
┌──────────────────┐
│  Archetype       │  Classifies: LLMOps / Agentic / PM / SA / FDE / Transformation
│  Detection       │
└────────┬─────────┘
         │
┌────────▼─────────┐
│  A-G Evaluation  │  Match, gaps, comp research, STAR stories, legitimacy
│  (reads cv.md)   │
└────────┬─────────┘
         │
    ┌────┼────┐
    ▼    ▼    ▼
 Report  PDF  Tracker
  .md   .pdf  entry

The scanner comes with 100+ companies ready to scan and 45+ search queries across major job boards. Copy templates/portals.example.yml to portals.yml and add your own:

AI Labs: Anthropic, OpenAI, Mistral, Cohere, LangChain, Pinecone Voice AI: ElevenLabs, PolyAI, Parloa, Hume AI, Deepgram, Vapi, Bland AI AI Platforms: Retool, Airtable, Vercel, Temporal, Glean, Arize AI Contact Center: Ada, LivePerson, Sierra, Decagon, Talkdesk, Genesys Enterprise: Salesforce, Twilio, Gong, Dialpad LLMOps: Langfuse, Weights & Biases, Lindy, Cognigy, Speechmatics Automation: n8n, Zapier, Make.com European: Factorial, Attio, Tinybird, Clarity AI, Travelperk

Job boards searched: 55+ provider modules cover ATS APIs, board-wide feeds, XML/RSS feeds, markdown feeds, and local parsers. See Supported job boards for the full table.

By default node scan.mjs (a.k.a. npm run scan) trusts what each ATS feed returns. Some companies leave stale postings in their public API even after the role is closed, so those expired entries can leak into pipeline.md. Pass --verify to launch Playwright after the API pass and drop expired postings before they hit the pipeline:

node scan.mjs --verify          # zero-token discovery + Playwright liveness check

The verification is sequential and only runs against new offers (after dedup), so the cost stays bounded.

The built-in terminal dashboard lets you browse your pipeline visually:

npm run serve:dashboard   # launch the TUI
npm run build:dashboard   # optional: build the standalone binary

Features: 6 filter tabs, 4 sort modes, grouped/flat view, lazy-loaded previews, inline status changes.

There is also an experimental web UI (alpha, opt-in — nothing runs unless you start it): see web/README.md.

career-ops/
├── AGENTS.md                    # Canonical agent instructions (all CLIs)
├── CLAUDE.md                    # Claude Code wrapper (imports AGENTS.md)
├── CODEX.md                     # Codex wrapper (imports AGENTS.md)
├── OPENCODE.md                  # OpenCode wrapper (imports AGENTS.md)
├── GEMINI.md                    # Legacy no-op guard to avoid Antigravity duplicate context
├── cv.md                        # Your CV (create this)
├── article-digest.md            # Your proof points (optional)
├── config/
│   └── profile.example.yml      # Template for your profile
├── modes/                       # Skill modes
│   ├── _shared.md               # Shared context (customize this)
│   ├── oferta.md                # Single evaluation
│   ├── pdf.md                   # PDF generation
│   ├── cover.md                 # Cover letter generation
│   ├── email.md                 # Formal application email drafts
│   ├── scan.md                  # Portal scanner
│   ├── batch.md                 # Batch processing
│   └── ...
├── templates/
│   ├── cv-template.html         # ATS-optimized CV template
│   ├── portals.example.yml      # Scanner config template
│   └── states.yml               # Canonical statuses
├── batch/
│   ├── batch-prompt.md          # Self-contained worker prompt
│   └── batch-runner.sh          # Orchestrator script
├── dashboard/                   # Go TUI pipeline viewer
├── data/                        # Your tracking data (gitignored)
├── reports/                     # Evaluation reports (gitignored)
├── output/                      # Generated PDFs (gitignored)
├── fonts/                       # Space Grotesk + DM Sans
├── docs/                        # Setup, customization, budget guide, architecture
└── examples/                    # Sample CV, report, proof points

• Agent: AI coding CLI with shared skills and modes (AGENTS.md + CLI wrapper)
• PDF: Playwright + HTML template
• Cover letters: HTML template + Playwright (A4 PDF, same pipeline as CVs)
• Scanner: Playwright + Greenhouse API + WebSearch
• Dashboard: Go + Bubble Tea + Lipgloss (Catppuccin Mocha theme)
• Data: Markdown tables + YAML config + TSV batch files

• cv-santiago -- The portfolio website (santifer.io) with AI chatbot, LLMOps dashboard, and case studies. If you need a portfolio to showcase alongside your job search, fork it and make it yours.

What is career-ops? career-ops is an open-source, CLI-agnostic job-search command center. It turns any AI coding CLI into a pipeline that evaluates job offers against your CV, generates ATS-tailored PDFs, finds the right person to contact, and tracks everything in one place — while you keep the final decision. It is the first reference implementation of the CareerOps Manifesto. More at career-ops.org.

Can I run career-ops for free, or on a cheaper / local model? Yes. career-ops is CLI-agnostic and runs on free and local models — via OpenRouter free models, Ollama, or any OpenAI-compatible endpoint — so you are not tied to a paid subscription. See docs/RUNNING_ON_A_BUDGET.md for the full setup.

Which AI CLIs does career-ops work with? career-ops runs on any major AI coding CLI — Claude Code, Codex, Gemini / Antigravity, OpenCode, Grok, Qwen and more — through the open Agent Skill Standard, so it is never locked to a single vendor. Use the CLI you already have.

How do I install career-ops on Windows? career-ops runs on Windows. If skills fail to load with a symlink error during install, the fix is in docs/FAQ.md. Full steps are in docs/SETUP.md.

Does career-ops auto-apply to jobs for me? No. career-ops is a filter, not a spray-and-pray auto-applier. The AI evaluates, ranks and drafts; you review and decide. It never submits, sends, or clicks anything — you always have the final call. That human-in-the-loop design is the whole point.

Is career-ops free and open source? Yes. career-ops is free and open source, and for the candidate it always will be — it is the first reference implementation of the CareerOps Manifesto. Read it, and if it says what you believe, sign it.

I'm Santiago Fernández de Valderrama Aparicio (santifer) -- Head of Applied AI, former founder (built and sold a business that still runs with my name on it). I built career-ops to manage my own job search. It worked: I used it to land my current role.

Curious how this repo is maintained in ~4 hours a week? Read Agentic maintenance: how career-ops is run by a fleet of AI agents.

My portfolio and other open source projects → santifer.io

Wikidata: Santiago Fernández de Valderrama Aparicio · career-ops.

career-ops is a local, open-source tool, NOT a hosted service. By using this software, you acknowledge:

1. You control your data. Your CV, contact info, and personal data stay on your machine and are sent directly to the AI provider you choose (Anthropic, OpenAI, etc.). We do not collect, store, or have access to any of your data.
2. You control the AI. The default prompts instruct the AI not to auto-submit applications, but AI models can behave unpredictably. If you modify the prompts or use different models, you do so at your own risk. Always review AI-generated content for accuracy before submitting.
3. You comply with third-party ToS. You must use this tool in accordance with the Terms of Service of the career portals you interact with (Greenhouse, Lever, Workday, LinkedIn, etc.). Do not use this tool to spam employers or overwhelm ATS systems.
4. No guarantees. Evaluations are recommendations, not truth. AI models may hallucinate skills or experience. The authors are not liable for employment outcomes, rejected applications, account restrictions, or any other consequences.

See LEGAL_DISCLAIMER.md for full details. This software is provided under the MIT License "as is", without warranty of any kind.

Every person who has shipped code, docs, translations or tests is listed in CONTRIBUTORS.md — including non-code contributions, which the graph above cannot show.

Got hired using career-ops? Share your story!

The code is licensed under MIT. The "career-ops" name and brand are governed by the Trademark Policy, permissive for community use, reserved for commercial product naming and endorsement.