# wxlvip/Interviewer

Repository: https://github.com/wxlvip/Interviewer
Canonical: https://ross.abutalabs.com/products/interviewer
License Family: other
Last push: 2021-12-05T10:14:12+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1785, "days_push": 1732, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1137, forks 253 (observed 2026-08-28T04:03:43.885715+00:00)

## What it is
A curated collection of frontend interview questions and study materials covering HTML, CSS, and JavaScript, organized around job-level models (e.g., P7 requirements). It emphasizes understanding underlying principles rather than rote memorization of answers.

## Use cases
- prepare for a frontend developer interview
- study javascript fundamentals for interviews
- understand css and html concepts behind common interview questions
- self-assess skills against a job level model like P7
- find a structured learning path for frontend career growth
- review computer networking and design patterns for web interviews

## When to choose
- you are preparing for frontend web developer interviews and want principle-focused study material
- you want to map your skills to a company job level model
- you prefer curated question lists with explanations over random question banks

## When to avoid
- you need hands-on coding practice or runnable projects
- you need interview prep for backend, mobile, or non-web roles
- you need an actively updated resource with recent content

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: web-development, frontend, tutorials
- platform: -
- tags: interview-preparation, frontend-interview, job-model, study-guide, chinese-language, web-server

## Member repositories
- wxlvip/Interviewer (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:43.885715+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:36:22.861164+00:00, confidence not recorded.
  - readme: https://github.com/wxlvip/Interviewer (fetched 2026-08-28T04:03:43.885715+00:00, sha 894ba7d096d2)
- Data as of 2026-08-30T08:39:29.467469+00:00.