career-ops is a retrieval and knowledge workflows repository at santifer/career-ops; GitHub metadata summarizes it as: AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing. Its recorded primary language is JavaScript. License metadata lists MIT. GitHub metadata shows about 48,428 stars. The project homepage is https://career-ops.org.
License
MIT
Stars
58,436
Homepage
https://career-ops.org/Features
- Maintainer description for career-ops: AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.
- career-ops uses JavaScript as its recorded primary language, which helps with stack-fit review.
- career-ops supports investigation of retrieval, embedding, or knowledge-grounded application flows.
- career-ops can inform repeatable automation, scheduled execution, or operations workflow design.
- career-ops fits engineering teams assessing code, CLI, SDK, runtime, or developer-tooling workflows.
- career-ops lists MIT license metadata; review obligations before redistribution or hosted use.
Use Cases
- Supports AI engineering build-and-iterate workflows for dev teams
- Used for cross-system process automation and operations efficiency
- Build internal AI workflow prototypes with career-ops
- Validate career-ops in production-like engineering scenarios
- Building AI development workflows
- Automating agent-based processes
FAQ
Start from the repository summary (AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.), then verify maintenance status, integration boundaries, and whether its retrieval and knowledge workflows, workflow automation, developer engineering workflows focus matches the intended workflow. Repository: https://github.com/santifer/career-ops. Stars: about 48,428. License: MIT. Language: JavaScript.
career-ops is best treated as a repository-level component or reference implementation for retrieval and knowledge workflows, workflow automation, developer engineering workflows. Good evaluation scenarios include: Use career-ops when the need is retrieval and knowledge workflows and the repo summary matches: AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF ge... Compare the JavaScript implementation in career-ops before choosing a similar internal architecture. Use career-ops to prototype retrieval-backed knowledge features using the repository direction.