Career-Ops
github.com/santifer/career-ops- Category
- AI Agents
- Rank
- No. 166Tools index
- Pricing
- Open Source
- Type
- TOOL
- Builder
- santifer
- GitHub
- 70.6k stars
- Latest release
- web-v0.10.0
- Date
About
AI-powered job search system that evaluates job postings with structured A-F scoring, generates tailored ATS-optimized CVs, and automates application tracking. Built on Claude Code with 14 skill modes and batch processing capabilities.
What it does
Career-Ops turns a local project folder into a guided job-search workspace. An AI coding assistant reads your profile and CV, scans public job boards, compares roles against your goals, prepares application documents, and maintains a searchable pipeline. You inspect every result and submit applications yourself.
Why it's ranked here
The tool covers unusually deep ground after discovery: fit analysis, company research, interview stories, negotiation prep, follow-ups, and outcome patterns share one workflow. Its local-first design and explicit approval gates are credible strengths. The cost is substantial setup, personal context feeding, and dependence on an AI coding environment.
What's good
Public ATS scans consume no model tokens, while broader analysis remains optional. Integrity tools normalize statuses, detect duplicates, verify report links, and resume interrupted batches. Application assistance stops before submission. Plugin consent requires both explicit enablement and credentials, with host restrictions, pinned community revisions, and tamper detection.
Tradeoffs
Early evaluations can be weak until you supply detailed career history, proof points, preferences, and constraints. Browser-backed PDF and form workflows require Chromium and can encounter captchas or changing page structures. Data does not sync across devices. Batch work can hit provider limits, and some interfaces need manual intervention.
How to use it well
It suits terminal-comfortable candidates running a selective, research-heavy search across many postings. Start with onboarding, configure target roles and portals, scan cheaply, then reserve full evaluation and document tailoring for plausible matches. Use the tracker through interviews and offers. It does not replace human judgment, cloud synchronization, legal advice, or final application submission.
Technical notes+
package.json defines a private Node.js package requiring Node 18 or newer, with Playwright, YAML, dotenv, and Google Generative AI dependencies; its postinstall fetches Chromium. docs/SETUP.md documents the scoped npx initializer, manual clone installation, Codex prompts, and an optional Go terminal dashboard. docs/ARCHITECTURE.md describes agent-authored reports, HTML-to-PDF rendering, parallel headless workers, and a canonical Markdown tracker. docs/SCRIPTS.md details validation, normalization, deduplication, merging, scanner, updater, and upgrade-regression surfaces. docs/PLUGINS.md specifies opt-in ESM plugins, allowed-host enforcement, pinned registry commits, capability hooks, and no submission hook. docs/APPLY_AUTOFILL.md keeps final submission manual and documents ATS-specific browser constraints.
Observed
- License
- MIT
- Primary runtime
- Node.js 18 or newer using JavaScript ESM modules
- Installation
- Scoped npx initializer or manual Git clone followed by npm install
- Interfaces
- Interactive AI coding CLI prompts, one-shot CLI workers, npm scripts, and an optional Go terminal dashboard
- Platform support
- Setup and automation guidance covers macOS, Linux, Windows, Docker, Codex, and Claude Cowork
- Data model
- Local files form the source of truth; no cloud sync component is provided
Read from README.md, package.json, docs/FAQ.md, docs/CODEX.md, docs/SETUP.md, docs/COWORK.md, docs/PLUGINS.md, docs/SCRIPTS.md, docs/FREE_TIER.md, docs/REVIEWING.md, docs/AUTOMATION.md, docs/ARCHITECTURE.md, docs/CUSTOMIZATION.md, docs/PLUGIN_REVIEW.md, docs/APPLY_AUTOFILL.md.
What it can do
Evaluate job postings with structured scoring
Job posting text or URL → A-F grade score with structured evaluation criteria
Generate tailored ATS-optimized CVs
Job posting requirements and user profile data → Customized PDF resume optimized for applicant tracking systems
Process multiple job applications in batches
Multiple job posting URLs or descriptions → Batch-processed evaluations and tailored application materials
Scan job portals for relevant opportunities
Search criteria and portal parameters → List of matching job opportunities with basic details
Track job application status and progress
Application submission data and status updates → Application tracking dashboard with current status
Perform integrity checks on application data
Submitted application materials and job requirements → Validation report identifying discrepancies or issues
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Editorially curated, with community endorsements as a secondary signal. Corrections welcome.