{"adoption": {"forks": 3240, "observed_at": "2026-08-28T04:11:38.942513+00:00", "stars": 26260}, "canonical_url": "https://ross.abutalabs.com/products/fe-interview", "card": {"archived": false, "artifact_type": "learning-resource", "description": "前端面试每日 3+1，以面试题来驱动学习，提倡每日学习与思考，每天进步一点！每天早上5点纯手工发布面试题（死磕自己，愉悦大家），6000+道前端面试题全面覆盖，HTML/CSS/JavaScript/Vue/React/Nodejs/TypeScript/ECMAScritpt/Webpack/Jquery/小程序/软技能……", "domain": ["frontend", "tutorials", "web-development", "education"], "enriched": true, "function": ["documentation"], "health_score": 49, "homepage": "http://www.h-camel.com", "language": "JavaScript", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["haizlin/fe-interview"], "name": "haizlin/fe-interview", "platform": ["cross-platform"], "pushed_at": "2025-10-26T20:49:10+00:00", "repo": "haizlin/fe-interview", "stars": 26260, "tags": ["interview-questions", "frontend-interview", "question-bank", "daily-learning", "html", "css", "javascript", "vue", "react", "nodejs", "typescript", "soft-skills", "chinese", "web-server"], "topics": ["frontend", "interview", "frontend-interview", "fe-interview", "front-end", "javascript", "css", "html", "resume", "interview-questions", "vue", "react", "js", "nodejs", "node"], "urls": [], "use_cases": ["prepare for a frontend developer interview", "practice daily javascript and css interview questions", "find vue and react interview questions with answers", "review frontend fundamentals before a job interview", "study frontend topics a little every day", "browse a large categorized list of html css js questions"], "what_it_is": "A free open-source collection of 6000+ frontend interview questions published daily (3+1 per day) covering HTML, CSS, JavaScript, Vue, React, Node.js, TypeScript, and soft skills. It drives daily learning and interview preparation through a question-a-day format maintained since 2019.", "when_to_avoid": ["you need an interactive quiz app or automated grading - this is a curated question list", "you need backend, algorithms, or non-frontend interview prep", "you need content in a language other than Chinese (English README exists but questions are Chinese)"], "when_to_choose": ["you are preparing for frontend job interviews and want a large, categorized question bank", "you want a daily habit of answering frontend questions", "you need coverage across HTML, CSS, JS, frameworks, and soft skills in one place"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/fe-interview", "repo": "haizlin/fe-interview", "role": "main", "score": 45}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:11:38.942513+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T16:55:54.362601+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "b817f200bc4fde04614bbbf1abe7e416aa5b14ef6012f62fd8b7c073cc35b5ba", "fetched_at": "2026-08-28T04:11:38.942513+00:00", "kind": "readme", "missing": false, "url": "https://github.com/haizlin/fe-interview"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 49, "longevity": 100, "rhythm": 8}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": [], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2695, "days_push": 311, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 45, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}