Developer jiito has published interview-prep-skills, a three-skill package for technical interview preparation that installs into Cursor, Claude Code, and compatible platforms via npx skills add jiito/interview-prep-skills. It's a modest project, but it functions as a concrete test of what Anthropic's Agent Skills open standard can actually support at the community level.
The three skills divide the interview process into discrete phases. requirements-prioritization-drill runs focused chat exercises targeting the opening of a system design session — specifically, compressing an ambiguous problem statement into prioritized functional and non-functional requirements before any architecture discussion begins. system-design-interview supports full generate/practice/review cycles with Excalidraw diagram integration and a configured interviewer mode that withholds solutions during practice rounds. The third, interview-generation, produces structured four-part Python coding prompts with runnable skeletons and optional test scaffolding, while scanning the repository to avoid regenerating questions already covered.
One correction worth making before going further: the skills CLI used to install this package — npx skills — was built by Vercel Labs, which has contributed significantly to the ecosystem's tooling. But Anthropic released Agent Skills as an open standard in December 2025, and the specification is governed through agentskills.io, not by Vercel. The distinction matters when evaluating cross-platform portability claims: documented adopters include Cursor, Claude Code, GitHub Copilot, OpenAI Codex, Gemini CLI, and OpenCode, but which platforms implement which parts of the spec varies, and compatibility should be tested rather than assumed.
It's also worth being clear about what the skills in this package actually are: natural-language instruction sets wrapped in SKILL.md files, not trained capabilities or evaluated prompting strategies. Their effectiveness depends on whether a given agent reliably holds conversational state across a session — staying in an interviewer role, not surfacing solutions prematurely, tracking which questions have been generated. These constraints are easy to specify and hard to verify, and the repository includes no automated tests or evaluation framework to catch when an agent goes off-script. Engineers who use it seriously should treat it as a starting point, not a reliable coaching system.
What the project does demonstrate is that the Skills format is accessible enough for individuals to publish workflow-specific packages without organizational backing. The more open question is whether those packages behave consistently across different adopters. 'Compatible with Cursor and Claude Code' is a meaningful claim; 'produces equivalent results on both' is a harder one to make, and the ecosystem hasn't yet developed reliable ways to test it.