--- title: "koog vs career-ops" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jetbrains-koog-vs-santifer-career-ops" tools: ["jetbrains-koog", "santifer-career-ops"] --- # koog vs career-ops *GraphCanon updated Sep 20, 2026* ## Verdict Pick koog if koog offers JVM-centric AI agent development with support for wide-ranging deployment environments from Kotlin; pick career-ops if career-ops is an open-source AI job search tool designed to automate scanning job portals in the tech industry, scoring job listings for suitability, and customizing resumes, all run from a CLI interface. [koog](https://docs.koog.ai) reports 4.6k GitHub stars, 474 forks, and 195 open issues, last pushed Sep 14, 2026. [career-ops](https://career-ops.org) has 72k stars, 14k forks, and 537 open issues, last pushed Sep 19, 2026. Figures are from public GitHub metadata via [koog's repository](https://github.com/JetBrains/koog) and [career-ops's repository](https://github.com/santifer/career-ops). | | [koog](/tools/jetbrains-koog.md) | [career-ops](/tools/santifer-career-ops.md) | | --- | --- | --- | | Tagline | A JVM-based framework for building enterprise-ready AI agents | Open-source AI job search tool that automates the process of scanning job portals, scoring listings, and tailoring CVs for applicants. | | Stars | 4,579 | 72,182 | | Forks | 474 | 13,600 | | Open issues | 195 | 537 | | Language | Kotlin | JavaScript | | Adopt for | Koog offers JVM-centric AI agent development with support for wide-ranging deployment environments from Kotlin. | career-ops is an open-source AI job search tool designed to automate scanning job portals in the tech industry, scoring job listings for suitability, and customizing resumes, all run from a CLI interface. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 License grants permissive use with attribution requirement. | MIT | | Categories | AI Agents, Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [koog](/tools/jetbrains-koog.md) | [career-ops](/tools/santifer-career-ops.md) | | --- | --- | --- | | Days since push | 5d | 0d | | Open issues (now) | 195 | 537 | | Stars delta | +64 (30d) | +8.7k (30d) | | Open issues delta | +20 (30d) | +260 (30d) | | Full report | [trust report](/tools/jetbrains-koog/trust.md) | [trust report](/tools/santifer-career-ops/trust.md) | ## Decision facts: koog - **Adopt for:** Koog offers JVM-centric AI agent development with support for wide-ranging deployment environments from Kotlin. - **License detail:** Apache-2.0 License grants permissive use with attribution requirement. ## Decision facts: career-ops - **Pricing:** freemium - The tool is open source and distributed under the MIT license, free to use. However, premium services or integrations might be available for additional costs. - **Adopt for:** career-ops is an open-source AI job search tool designed to automate scanning job portals in the tech industry, scoring job listings for suitability, and customizing resumes, all run from a CLI interface. ## Choose when ### Choose koog if… - koog is primarily Kotlin; career-ops is JavaScript. - License: koog is Apache-2.0, career-ops is MIT. - Tags unique to koog: agentframework, agentic-ai, agents, ai-agents-framework. - Need JVM-based fault-tolerant AI agents across multiple platforms including Android, iOS, and web browsers ### Choose career-ops if… - career-ops is primarily JavaScript; koog is Kotlin. - License: career-ops is MIT, koog is Apache-2.0. - Pricing: The tool is open source and distributed under the MIT license, free to use. However, premium services or integrations might be available for additional costs.. - Tags unique to career-ops: ai, ai-agent, careerops, job-hunting. - career-ops ships Docker support for self-hosted deployment. - When you are actively searching for tech-related jobs and need tools to streamline resume tailoring and application tracking on your local machine. ## When NOT to use koog - Primarily working outside of JVM environments, such as pure Python or JavaScript projects without JVM support - Looking for an AI agent framework that does not require JDK 17 or Kotlin 2.3.10 or higher ## When NOT to use career-ops - Avoid using this tool if you prefer web-based job search solutions and do not want to manage the application locally on your machine. - Career-ops may not be suitable for users looking for robust automation of resume creation from scratch, as it focuses more on tailoring existing CVs. ## Common questions ### What is the difference between koog and career-ops? koog: A JVM-based framework for building enterprise-ready AI agents. career-ops: Open-source AI job search tool that automates the process of scanning job portals, scoring listings, and tailoring CVs for applicants.. See the comparison table for live GitHub stats and shared categories. ### When should I choose koog over career-ops? Choose koog over career-ops when koog is primarily Kotlin; career-ops is JavaScript; License: koog is Apache-2.0, career-ops is MIT; Tags unique to koog: agentframework, agentic-ai, agents, ai-agents-framework; Need JVM-based fault-tolerant AI agents across multiple platforms including Android, iOS, and web browsers. ### When should I choose career-ops over koog? Choose career-ops over koog when career-ops is primarily JavaScript; koog is Kotlin; License: career-ops is MIT, koog is Apache-2.0; Pricing: The tool is open source and distributed under the MIT license, free to use. However, premium services or integrations might be available for additional costs.; Tags unique to career-ops: ai, ai-agent, careerops, job-hunting; career-ops ships Docker support for self-hosted deployment; When you are actively searching for tech-related jobs and need tools to streamline resume tailoring and application tracking on your local machine. ### When should I avoid koog? Primarily working outside of JVM environments, such as pure Python or JavaScript projects without JVM support Looking for an AI agent framework that does not require JDK 17 or Kotlin 2.3.10 or higher ### When should I avoid career-ops? Avoid using this tool if you prefer web-based job search solutions and do not want to manage the application locally on your machine. Career-ops may not be suitable for users looking for robust automation of resume creation from scratch, as it focuses more on tailoring existing CVs. ### Is koog or career-ops more popular on GitHub? career-ops has more GitHub stars (72,182 vs 4,579). Stars measure visibility, not whether either tool fits your constraints. ### Are koog and career-ops open source? Yes - both are open-source projects on GitHub (koog: Apache-2.0, career-ops: MIT). ### Where can I find alternatives to koog or career-ops? GraphCanon lists graph-backed alternatives at [koog alternatives](/tools/jetbrains-koog/alternatives) and [career-ops alternatives](/tools/santifer-career-ops/alternatives) ([koog markdown twin](/tools/jetbrains-koog/alternatives.md), [career-ops markdown twin](/tools/santifer-career-ops/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/jetbrains-koog-vs-santifer-career-ops.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, koog or career-ops? koog: Very active. career-ops: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for koog and career-ops? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [koog trust report](/tools/jetbrains-koog/trust); [career-ops trust report](/tools/santifer-career-ops/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jetbrains-koog`](/api/graphcanon/graph?tool=jetbrains-koog) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_