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ai-interview艾访谈

Agent Skill

ai-interview 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

13,430

周安装

571

GitHub Stars

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下载量

4,705
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ai-interview(艾访谈)
来源仓库:https://github.com/zhangdong/ai-interview
安装命令:
openclaw skills install ai-interview
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ai-interview

简介

基于 Fuku.ai 免费服务提供 AI 驱动的模拟面试体验。

  • 适合求职者练习技术面或行为面试问题并获得反馈。
  • 支持自定义岗位方向与难度级别调整题目风格。ai-interview 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 当前依赖第三方公共接口,可能存在服务变动风险。
  • 建议结合真实面试经验综合评估自身准备情况。

SKILL.md

name
ai-interview
description
Run AI-powered mock interviews using Fuku.ai's free public service.

AI Interview Skill

Turn a folder full of resumes into structured AI interview sessions. This skill uses Fuku.ai's free public API to generate AI interview reports.

🎯 Purpose

This is a Fuku.ai-specific skill that leverages their free, anonymous interview service. No user account, API key, or login required.

🔑 Authentication

This skill uses shared anonymous credentials provided by Fuku.ai for public access:

ItemValue
Upload Endpointhttps://hapi.fuku.ai/hr/rc/anon/file/upload
Job APIhttps://hapi.fuku.ai/hr/rc/anon/job/invite/ai_interview
X-NUMBER Headerjob-Z4nV8cQ1LmT7XpR2bH9sJdK6WyEaF0
uid Query Param1873977344885133312

These are fixed, shared credentials for Fuku.ai's free tier. All users of this skill use the same endpoints and identifiers. This is intentional—the service is designed for anonymous, no-login usage.

Design Notes

  • No user credentials required: The service is free and public
  • No environment variables: Endpoints and credentials are hardcoded by design
  • Not self-hostable: This skill only works with Fuku.ai's hosted service
  • Privacy consideration: Resume files are sent to Fuku.ai's servers. Review their privacy policy before uploading sensitive documents.

✅ What It Does

  1. Collects three mandatory inputs: job title, company name, report email.
  2. Scans a resume folder for PDF/DOC/DOCX files (up to 100).
  3. Uploads each resume to Fuku.ai's public endpoint and captures the returned file URLs.
  4. Creates an AI interview job via Fuku.ai's API using the shared anonymous credentials.
  5. Logs minimal job metadata locally and confirms the report email destination.

🧭 Workflow

  1. Install & Prepare

- cd skills/ai-interview && npm install (installs axios + form-data). - Subsequent runs only need node run.js ....

  1. Gather Inputs

- Ask the user for: job title, company, email for reports (validate email format). - Ask for the resume folder path inside the workspace. Confirm contents before proceeding.

  1. Scan Folder

- Accept only .pdf, .doc, .docx files. - Abort if folder is empty or missing.

  1. Upload Resumes

- From skills/ai-interview/, run node run.js --folder <dir> --jobTitle <title> --company <company> --email <email>. - The script auto-detects .pdf/.doc/.docx files (up to 100), uploads each to Fuku.ai's upload endpoint, and captures the returned file URLs. - On any failed upload, the script aborts and reports the .desc field from the API.

  1. Trigger Interview Job

- The same script immediately calls the interview creation endpoint with payload { jobTitle, company, email, fileUrls }. - Authentication uses hardcoded credentials (see "Hardcoded Configuration" table above). - Expect response { "code": 0, "data": { "id", "company", "title", ... } }. - If code is not 0, the script surfaces the error and stops.

  1. Report Back

- Confirm job creation, list resumes included, and restate the email destination. - Persist only the minimal identifiers (id, company, title) into ai-interview/jobs/<timestamp>.json—no need to keep full payloads. - Remind the user that AI interview reports are delivered directly to the email they provided. - A typical success response looks like:

     {
       "code": 0,
       "data": {
         "id": "5b16b2d2f5e947f78244246a9f24e2cb",
         "company": "FUKU",
         "title": "cfoe",
         ... (truncated)
       },
       "desc": "successful"
     }

🔒 Validation & Safety

  • Email: Must match /^[^@\s]+@[^@\s]+\.[^@\s]+$/.
  • File count: Maximum 100 resumes per batch.
  • Upload errors: The Fuku API must return code: 0; otherwise surface the .desc field and ask whether to retry or skip that file.
  • PII handling: Do not log resume contents—only file names are logged (not full remote URLs).
  • HTTPS: Both endpoints use HTTPS.
  • Data destination: Resume files are sent to Fuku.ai's third-party service. Review their privacy policy before uploading sensitive documents.

📁 Local Storage

Minimal audit trail stored under ai-interview/jobs/:

ai-interview/
  jobs/
    2026-02-27T08-30-00Z.json  # job identifiers only

Each file contains only the essential identifiers (no resume data or full API responses):

{
  "timestamp": "2026-02-27T08:30:00Z",
  "jobId": "5b16b2d2f5e947f78244246a9f24e2cb",
  "company": "FUKU",
  "title": "cfoe"
}

🧪 Testing Tips

  • Use dummy resumes and a test email address for initial runs.
  • Validate that the email receives the AI interview report before marking the job done.
  • Note: This skill only works with Fuku.ai's production endpoints—there is no staging/mock mode.

🆘 Troubleshooting

IssueCauseFix
Upload returns 413File too largeCompress resume or raise server limit
fileUrls emptyUpload failed silentlyCheck upload response for success flag
API 400Missing fieldsEnsure jobTitle/company/email/fileUrls filled

📣 User Prompt Template

"Great! Need the job title, company name, a mailbox for the interview report, and the folder path containing the resumes (PDF/DOC/DOCX)."

🚀 Next Steps

  • Automate email notifications to confirm when the interview report is delivered (future enhancement).
  • Add optional metadata per candidate (experience, notes) by extending the payload.

Happy interviewing! 🎙️

适合场景

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02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

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按下载量换算4,543

安全审计

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可疑

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通过

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权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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