作业

SKILLAI 工具
AI 工具 未标注权限 许可证不明确
安装这个技能

求职申请自动化,代你提交申请(需授权谨慎)。This skill fits its job-application automation purpose,

一句话选型结论

按资料字段整理

作业是AI 工具类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类AI 工具 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install zcwl/job-auto-apply
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

AI 工具
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方zcwl仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 enterprise
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791719225
正文体量6.5 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
组合多个 AI 能力

把写作、检索、总结串成一条流程。

搭工作流

把固定流程做成可重复调用的步骤。

做提示词与评测

整理提示词并对比输出效果。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在AI 工具场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
作业当前 未标注权限 未标注 未标注 未标注 有
执行计划 只读 GitHub 仓库 151.5 万 Codex、Claude、Cursor 有
Playwright MCP 测试 浏览器控制 ClawHub 市场 136.5 万 OpenClaw 有
完成前的验证 未标注权限 GitHub 仓库 131.9 万 Codex、Claude、Cursor 有
子 Agent 驱动开发 只读 GitHub 仓库 131.2 万 Codex、Claude、Cursor 有
前端设计 执行命令 GitHub 仓库 125.6 万 Codex、Claude、Cursor 有

SKILL.md 全文

6.5 KB
模型实际读到的说明书原文,来自技能仓库

Job Auto-Apply Skill

Automate job searching and application submission across multiple job platforms using Clawdbot.

Overview

This skill enables automated job search and application workflows. It searches for jobs matching user criteria, analyzes compatibility, generates tailored cover letters, and submits applications automatically or with user confirmation.

Supported Platforms:
- LinkedIn (including Easy Apply)
- Indeed
- Glassdoor
- ZipRecruiter
- Wellfound (AngelList)

Quick Start

1. Set Up User Profile

First, create a user profile using the template:

# Copy the profile template
cp profile_template.json ~/job_profile.json

# Edit with user's information
# Fill in: name, email, phone, resume path, skills, preferences

2. Run Job Search and Apply

# Basic usage - search and apply (dry run)
python job_search_apply.py \
  --title "Software Engineer" \
  --location "San Francisco, CA" \
  --remote \
  --max-applications 10 \
  --dry-run

# With profile file
python job_search_apply.py \
  --profile ~/job_profile.json \
  --title "Backend Engineer" \
  --platforms linkedin,indeed \
  --auto-apply

# Production mode (actual applications)
python job_search_apply.py \
  --profile ~/job_profile.json \
  --title "Senior Developer" \
  --no-dry-run \
  --require-confirmation

Workflow Steps

Step 1: Profile Configuration

Load the user's profile from the template or create programmatically:

from job_search_apply import ApplicantProfile

profile = ApplicantProfile(
    full_name="Jane Doe",
    email="jane@example.com",
    phone="+1234567890",
    resume_path="~/Documents/resume.pdf",
    linkedin_url="https://linkedin.com/in/janedoe",
    years_experience=5,
    authorized_to_work=True,
    requires_sponsorship=False
)

Step 2: Define Search Parameters

from job_search_apply import JobSearchParams, JobPlatform

search_params = JobSearchParams(
    title="Software Engineer",
    location="Remote",
    remote=True,
    experience_level="mid",
    job_type="full-time",
    salary_min=100000,
    platforms=[JobPlatform.LINKEDIN, JobPlatform.INDEED]
)

Step 3: Run Automated Application

from job_search_apply import auto_apply_workflow

results = auto_apply_workflow(
    search_params=search_params,
    profile=profile,
    max_applications=10,
    min_match_score=0.75,
    dry_run=False,
    require_confirmation=True
)

Integration with Clawdbot

Using as a Clawdbot Tool

When installed as a Clawdbot skill, invoke via natural language:

Example prompts:
- "Find and apply to Python developer jobs in San Francisco"
- "Search for remote backend engineer positions and apply to the top 5 matches"
- "Auto-apply to senior software engineer roles with 100k+ salary"
- "Apply to jobs at tech startups on Wellfound"

The skill will:
1. Parse the user's intent and extract search parameters
2. Load the user's profile from saved configuration
3. Search across specified platforms
4. Analyze job compatibility
5. Generate tailored cover letters
6. Submit applications (with confirmation if enabled)
7. Report results and track applications

Configuration in Clawdbot

Add to your Clawdbot configuration:

{
  "skills": {
    "job-auto-apply": {
      "enabled": true,
      "profile_path": "~/job_profile.json",
      "default_platforms": ["linkedin", "indeed"],
      "max_daily_applications": 10,
      "require_confirmation": true,
      "dry_run": false
    }
  }
}

Features

1. Multi-Platform Search

  • Searches across all major job platforms
  • Uses official APIs when available
  • Falls back to web scraping for platforms without APIs

2. Smart Matching

  • Analyzes job descriptions for requirement matching
  • Calculates compatibility scores
  • Filters jobs based on minimum match threshold

3. Application Customization

  • Generates tailored cover letters per job
  • Customizes resume emphasis based on job requirements
  • Handles platform-specific application forms

4. Safety Features

  • Dry Run Mode: Test without submitting applications
  • Manual Confirmation: Review each application before submission
  • Rate Limiting: Prevents overwhelming platforms
  • Application Logging: Tracks all submissions for reference

5. Form Automation

Automatically fills common application fields:
- Personal information
- Work authorization status
- Education and experience
- Skills and certifications
- Screening questions (using AI when needed)

Advanced Usage

Custom Cover Letter Templates

Create a template with placeholders:

Dear Hiring Manager at {company},

I am excited to apply for the {position} role. With {years} years of 
experience in {skills}, I believe I would be an excellent fit.

{custom_paragraph}

I look forward to discussing how I can contribute to {company}'s success.

Best regards,
{name}

Application Tracking

Results are automatically saved in JSON format with details on each application submitted, including timestamps, match scores, and status.

Bundled Resources

Scripts

  • job_search_apply.py - Main automation script with search, matching, and application logic

References

  • platform_integration.md - Technical documentation for API integration, web scraping, form automation, and platform-specific details

Assets

  • profile_template.json - Comprehensive profile template with all required and optional fields

Safety and Ethics

Important Guidelines

  1. Truthfulness: Never misrepresent qualifications or experience
  2. Genuine Interest: Only apply to jobs you're actually interested in
  3. Rate Limiting: Respect platform limits and terms of service
  4. Manual Review: Consider enabling confirmation mode for quality control
  5. Privacy: Secure storage of personal information and credentials

Best Practices

  • Start with dry-run mode to verify behavior
  • Set reasonable limits (5-10 applications per day)
  • Use high match score thresholds (0.75+)
  • Enable confirmation for important applications
  • Track results to optimize strategy

常见问题

5 问
答案由本站依据条目字段整理
作业怎么安装?

在支持 Skills 的客户端里执行:skillhub install zcwl/job-auto-apply。安装方式为未标注。装完刷新技能列表或重开客户端。

作业支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

作业权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

作业收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

作业用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。