Open-source AI job search: scan job portals, score listings A-F, tailor your CV, track applications — runs locally in your AI coding CLI (Claude Code, Gemini, Codex, OpenCode…)
59.5k
Stars
11.8k
Forks
153
Open issues
30
Contributors
AI Analysis
Career-Ops is an open-source, locally-run AI agent system designed to automate the job search workflow: scanning job portals, scoring listings A-F, tailoring CVs to specific roles, and tracking applications. It runs inside AI coding CLIs such as Claude Code, Gemini CLI, or Codex, making it best suited for developers comfortable with agentic coding environments. Non-technical job seekers without familiarity with CLI-based AI tools will find it inaccessible.
Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.
AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.
Open-source AI job search pipeline uses Claude Code to evaluate, score, and tailor applications at scale
Career-Ops is a self-hosted, agentic job search system that wraps AI coding CLIs (primarily Claude Code) into a structured pipeline for job hunters. It automates portal scanning via Playwright, scores job offers on 10 weighted dimensions (A-F), generates per-job ATS-optimized PDF CVs, and tracks everything in a dashboard. Built by someone who used it to land a role after evaluating 740+ listings. Target users are technical job seekers — developers and engineers — who want systematic, high-signal filtering rather than volume-spray applications. Press coverage from Business Insider and Wired suggests non-trivial public awareness.
Created April 2026 by @santifer as a personal tool built during a real job search. Open-sourced shortly after the author landed a role, positioned as a 'system I wish I had' — a common and credible origin story for developer tools.
Nearly 55K stars in under three months is a sharp, press-amplified spike consistent with a viral personal story (Business Insider feature, Wired coverage, Product Hunt listing) hitting at a moment of high anxiety around AI-disrupted hiring. The 1,321 stars in the last 7 days suggests the spike has not fully plateaued. Forks at ~11K indicate meaningful hands-on interest beyond passive starring.
Author documents personal production use: 740+ job listings evaluated, 100+ CVs generated, one job offer accepted. Business Insider and Wired coverage (linked, not paywalled summaries) corroborate real-world origin. ~11K forks suggests many users have run or adapted it. Adoption beyond the author's personal case is not independently verified at scale, but community signals (Discord, npm package, Trendshift trending badge) suggest non-trivial active user base.
Appears to be a multi-layer system: a Node.js/JavaScript core handling skill modes and orchestration, a Go component for the TUI dashboard (likely using Bubble Tea), Playwright for browser automation of job portals, and PDF generation as a separate output stage. Likely structured as a CLI-first tool invokable from any agent-skill-compatible CLI. The '14 skill modes' likely represent discrete prompt-driven workflows. Sub-agent parallelism for batch processing is described explicitly.
Not documented in README.
Last push was June 18, 2026 — two days before evaluation date. Active maintenance is evident. The README is multilingual (12 languages), suggesting sustained investment. Discord community presence and a versioned npm release badge indicate ongoing release cadence.
ADOPT IF: you are a technical job seeker comfortable running Node.js/CLI tools and want a structured, AI-assisted filtering system to avoid wasting time on poor-fit roles. AVOID IF: you expect a polished SaaS product, lack Claude Code or equivalent API access, or need compliance guarantees around data handling for sensitive CV content. MONITOR IF: you are building job-search or HR tooling and want to track whether this matures into a reusable framework or remains a personal-tool-turned-viral-repo.
Independent dimensions
Mainstream potential
4/10
Technical importance
6/10
Adoption evidence
5/10
- Viral star counts driven by press coverage may not reflect sustained, return-user adoption — churn after initial spike is plausible.
- Playwright-based portal scraping is inherently fragile; Greenhouse, Ashby, and Lever frequently update their markup, requiring ongoing maintenance.
- Strong dependency on Claude Code API availability and pricing — cost per 740-listing run could be prohibitive for users on limited budgets.
- No documented test coverage makes it harder to verify reliability of scoring logic or PDF output quality as the codebase evolves.
- Single-maintainer project risk: if @santifer moves on post-job-search, maintenance continuity is uncertain despite the community Discord.
Likely stabilizes as a well-maintained niche tool with a loyal technical-user base, possibly evolving toward multi-LLM support and a managed hosted tier. Mainstream consumer adoption appears unlikely without significant UX abstraction.
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Languages
Information
- Website
- https://career-ops.org
- Language
- JavaScript
- License
- MIT
- Last updated
- 6h ago
- Created
- 3mo ago
- Analyzed with
- anthropic/claude-sonnet-4-6
Stars over time
Contributors over time
Top 100 contributors only — repos with more will plateau at 100.
Open issues
Top contributors
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Career-Ops is built on top of Claude Code's agent infrastructure rather than competing with it. Claude Code is the execution engine; Career-Ops is the domain-specific skill layer for job searching.
A curated collection of Claude skill sets, broader in scope. Career-Ops is a single-domain, opinionated implementation rather than a catalog — more immediately usable but narrower.
Claude Squad focuses on multi-agent task orchestration generally; Career-Ops uses a similar pattern but constrains it entirely to the job search domain with specific tooling (PDF, portal scrapers).
Appears to be a general Claude skills repo. Career-Ops is purpose-built with integrated infrastructure (Go dashboard, Playwright, PDF) rather than prompt collections alone.
