No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by tao943 · Codex Skill · ★ 196
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is build-resume-portfolio-site safe to install? View the security audit →
build-resume-portfolio-site 一个自包含的简历作品集网站 Skill：将简历材料和可选岗位 JD 转化为经过事实核验、用户批准的内容，并生成可运行的 React + Vite 个人作品集网站。 能力 提取简历事实与证据，区分事实、推断、待确认内容和最终文案。 通过对话逐项澄清日期、职责、项目范围、成果、指标和公开信息。 对岗位 JD 进行匹配分析，保留硬性要求、核心能力和加分项，并标记匹配、部分匹配、可迁移能力或未匹配。 对每段经历和项目文案执行写作、STAR、ATS、事实证据与 JD 相关性质量门；只有证据充分时才提供加强版本。 在生成网站前分别确认整体结构、字体排版、配色、媒体处理、主动效和副动效。 每个启用的设计类别都可在用户明确同意后打开独立的浏览器视觉预览；预览只用于展示，不代替对话批准。 在明确需求后生成 TODO 计划，等待批准，再生成并验证完整网站。 自动执行 React + Vite 构建、响应式检查、视觉审计和有限范围修复。 网站完成后支持“满意完成”“加强动效”或“提出修改”三种验收路径。 工作流程 Skill 会保留事实与证据边界：未匹配的 JD 要求不会被自动写入简历或网站，缺少证据的指标、职责、日期和技术不会被虚构。 使用 将 安装为本地 Skill 后，在对话中调用： 然后提供简历文件、文本材料、岗位 JD、作品集素材或已有网站信息。Skill 会在内容未就绪时先完成内容准备，在设计选择前询问是否需要浏览器视觉展示，并在最终生成前等待明确的计划批准。 浏览器视觉预览 内置 Visual Companion 使用 Node.js 内置模块启动本地只读展示页，不依赖浏览器插件或 npm 包。浏览器只负责呈现候选风格；选择、批准和流程推进始终以对话中的明确回复为准。 如果宿主无法启动本地服务，Skill 会提供静态 HTML 回退。用户也可以拒绝某一类别的浏览器预览，继续使用文本方式完成选择。 目录 本 Skill 不要求外部内容 Skill、远程
| Stars | 196 |
| Forks | 1 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 55.5885228670121/100 |
| Open Issues | 2 |
| Last Updated | 2026-09-30 |
| Created | 2026-07-24 |
| Platforms | codex, python |
| Est. Tokens | ~13k |
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build-resume-portfolio-site is Codex skill for building staged React + Vite resume and portfolio sites. It is categorized as a Codex Skill with 196 GitHub stars.
build-resume-portfolio-site is primarily written in Python.
You can find installation instructions and usage details in the build-resume-portfolio-site GitHub repository at github.com/tao943/build-resume-portfolio-site. The project has 196 stars and 1 forks, indicating an active community.
The top alternatives to build-resume-portfolio-site on Agent Skills Hub include ai-maestro, upskill, skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: