qui-job-auto-apply（qui 工作自动申请）

Job Auto-Apply Skill

Automate job searching and application submission across multiple job platforms using Clawdbot. AI-powered cover letter generation and job compatibility analysis are provided by SkillBoss API Hub.

Overview

This skill enables automated job search and application workflows. It searches for jobs matching user criteria, analyzes compatibility using SkillBoss API Hub's AI capabilities, 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 Environment

export SKILLBOSS_API_KEY=your_skillboss_api_key

2. 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

3. 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 via SkillBoss API Hub (AI-powered)
5. Generate tailored cover letters via SkillBoss API Hub
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 (powered by SkillBoss API Hub)

• Analyzes job descriptions for requirement matching using AI via SkillBoss API Hub
• Calculates compatibility scores
• Filters jobs based on minimum match threshold

3. Application Customization (powered by SkillBoss API Hub)

• Generates tailored cover letters per job using SkillBoss API Hub's AI
• 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 SkillBoss API Hub 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 (AI features via SkillBoss API Hub)

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