No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by vaibhavarora14 · Claude Skill · ★ 145
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is job-application-agent safe to install? View the security audit →
💼 Job Application Agent A privacy-first Codex skill for a more disciplined job search Discover better roles · Apply with verified facts · Keep private data local · Learn from outcomes Quick start · How it works · Safety · Privacy · Analytics · Security Job Application Agent helps Codex discover, qualify, complete, and track your own job applications—without inventing credentials or hiding consequential decisions. It combines browser-assisted form filling with a verified résumé, candidate-defined targeting, secure local profile storage, duplicate detection, and an application ledger. Install — for humans and agents Run this one canonical command in a terminal: bash npx job-application-agent
| Stars | 145 |
| Forks | 25 |
| Language | JavaScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 69.7522426628497/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-02 |
| Created | 2026-08-12 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~15k |
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job-application-agent is Privacy-first Codex skill for discovering, validating, completing, and tracking job applications. It is categorized as a Claude Skill with 145 GitHub stars.
job-application-agent is primarily written in JavaScript. It covers topics such as agent-skills, ai-agent, automation.
You can find installation instructions and usage details in the job-application-agent GitHub repository at github.com/vaibhavarora14/job-application-agent. The project has 145 stars and 25 forks, indicating an active community.
job-application-agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to job-application-agent on Agent Skills Hub include awesome-ai-agent-skills, semanticscholar-skill, Overture. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: