Job Posting Analysis Skill

Purpose

Extract technology stack information from job postings and career pages, which often reveal internal tech stack details.

Operations

1. find_careers_page

Locate company's career/jobs page.

Search Strategies:

1. Common paths: /careers, /jobs, /work-with-us, /join-us
2. Subdomains: careers.{domain}, jobs.{domain}
3. Web search: site:{domain} careers OR jobs
4. Footer links on main site

Common Career Page URLs:

https://{domain}/careers
https://{domain}/jobs
https://careers.{domain}
https://jobs.{domain}
https://{domain}/about/careers
https://{domain}/company/careers

2. detect_ats_platform

Identify Applicant Tracking System in use.

ATS Detection Patterns:

{
  "Greenhouse": {
    "url_pattern": "boards.greenhouse.io",
    "indicates": ["Tech-forward startup", "Modern hiring"],
    "confidence": 95
  },
  "Lever": {
    "url_pattern": "jobs.lever.co",
    "indicates": ["Tech-forward startup", "Growth stage"],
    "confidence": 95
  },
  "Workday": {
    "url_pattern": ".wd5.myworkdayjobs.com|.wd3.myworkdayjobs.com",
    "indicates": ["Enterprise company", "Large org"],
    "confidence": 95
  },
  "Ashby": {
    "url_pattern": "jobs.ashbyhq.com",
    "indicates": ["Modern startup", "Tech-forward"],
    "confidence": 95
  },
  "iCIMS": {
    "url_pattern": "careers-.*\\.icims\\.com|icims.com",
    "indicates": ["Enterprise hiring"],
    "confidence": 95
  },
  "Taleo": {
    "url_pattern": "taleo.net",
    "indicates": ["Enterprise (Oracle)", "Large org"],
    "confidence": 95
  },
  "SmartRecruiters": {
    "url_pattern": "jobs.smartrecruiters.com",
    "indicates": ["Mid-market to Enterprise"],
    "confidence": 95
  },
  "BambooHR": {
    "url_pattern": ".bamboohr.com/jobs",
    "indicates": ["SMB company"],
    "confidence": 95
  },
  "Jobvite": {
    "url_pattern": "jobs.jobvite.com",
    "indicates": ["Mid-market hiring"],
    "confidence": 95
  },
  "Breezy HR": {
    "url_pattern": ".breezy.hr",
    "indicates": ["SMB startup"],
    "confidence": 95
  }
}

3. extract_tech_requirements

Parse job descriptions for technology mentions.

Extraction Patterns:

Experience with ([\w\s,/]+)
Proficiency in ([\w\s,/]+)
Knowledge of ([\w\s,/]+)
Tech stack:? ([\w\s,/]+)
Working knowledge of ([\w\s,/]+)
Familiar with ([\w\s,/]+)
Strong background in ([\w\s,/]+)
Required:?\s*([\w\s,/]+)
Nice to have:?\s*([\w\s,/]+)
Technologies:?\s*([\w\s,/]+)
Tools:?\s*([\w\s,/]+)

Technology Keyword Categories:

Languages:

JavaScript, TypeScript, Python, Java, Go, Rust, Ruby, PHP,
C#, C++, Kotlin, Swift, Scala, Elixir, Clojure

Frontend Frameworks:

React, Vue, Angular, Svelte, Next.js, Nuxt, Gatsby,
Redux, MobX, Zustand, React Query, Tailwind, Bootstrap

Backend Frameworks:

Node.js, Express, NestJS, Django, Flask, FastAPI,
Rails, Spring, .NET, Laravel, Phoenix

Databases:

PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch,
DynamoDB, Cassandra, Neo4j, Snowflake, BigQuery

Cloud/Infrastructure:

AWS, GCP, Azure, Kubernetes, Docker, Terraform,
Ansible, CloudFormation, Pulumi

Tools:

Git, GitHub, GitLab, Jenkins, CircleCI, GitHub Actions,
Datadog, New Relic, Grafana, Prometheus, Sentry

4. calculate_tech_frequency

Weight technologies by mention frequency across postings.

Scoring:

def calculate_frequency_score(tech, postings):
    mentions = sum(1 for p in postings if tech in p.requirements)
    total_postings = len(postings)

    frequency = mentions / total_postings

    # Classify importance
    if frequency >= 0.5:
        importance = "Core Stack"  # 50%+ of postings
    elif frequency >= 0.25:
        importance = "Common"      # 25-50%
    else:
        importance = "Occasional"  # < 25%

    return {
        "mentions": mentions,
        "frequency": frequency,
        "importance": importance
    }

5. analyze_role_patterns

Identify tech stack from role types.

Role Type Signals:

{
  "Frontend Engineer": {
    "implies": ["React/Vue/Angular", "JavaScript/TypeScript", "CSS frameworks"],
    "confidence": 70
  },
  "Backend Engineer": {
    "implies": ["Server-side language", "Database", "API development"],
    "confidence": 70
  },
  "Full Stack Engineer": {
    "implies": ["Frontend framework", "Backend framework", "Database"],
    "confidence": 65
  },
  "DevOps Engineer": {
    "implies": ["Cloud platform", "CI/CD", "Kubernetes/Docker", "IaC"],
    "confidence": 75
  },
  "Data Engineer": {
    "implies": ["Python/Scala", "Spark/Airflow", "Data warehouse"],
    "confidence": 75
  },
  "ML Engineer": {
    "implies": ["Python", "TensorFlow/PyTorch", "Cloud ML services"],
    "confidence": 75
  },
  "iOS Developer": {
    "implies": ["Swift", "Xcode", "iOS SDK"],
    "confidence": 85
  },
  "Android Developer": {
    "implies": ["Kotlin/Java", "Android SDK"],
    "confidence": 85
  }
}

Output

{
  "skill": "job_posting_analysis",
  "domain": "string",
  "results": {
    "careers_page": {
      "url": "string",
      "ats_platform": "Greenhouse",
      "ats_confidence": 95
    },
    "postings_analyzed": "number",
    "technologies_extracted": [
      {
        "name": "React",
        "category": "Frontend Framework",
        "mentions": 15,
        "total_postings": 20,
        "frequency": 0.75,
        "importance": "Core Stack",
        "contexts": [
          "Experience with React and TypeScript",
          "Build UIs using React"
        ],
        "confidence": 80
      }
    ],
    "role_distribution": {
      "Frontend": 5,
      "Backend": 8,
      "Full Stack": 4,
      "DevOps": 2,
      "Data": 1
    },
    "tech_stack_inference": {
      "frontend": ["React", "TypeScript", "Tailwind"],
      "backend": ["Node.js", "PostgreSQL", "Redis"],
      "infrastructure": ["AWS", "Kubernetes"],
      "confidence": "Medium"
    },
    "company_signals": {
      "engineering_size": "Large (20+ open roles)",
      "growth_stage": "Scaling",
      "tech_culture": "Modern (tech-forward ATS, current stack)"
    }
  },
  "evidence": [
    {
      "type": "job_posting",
      "title": "Senior Frontend Engineer",
      "url": "string",
      "technologies_mentioned": ["React", "TypeScript", "GraphQL"],
      "timestamp": "ISO-8601"
    }
  ]
}

Rate Limiting

Careers page fetch: 10/minute
Job posting pages: 20/minute
ATS APIs: Varies by platform

Error Handling

404: No careers page found
Access denied: ATS may require authentication
Continue with partial data
Fall back to search engine results

Security Considerations

Only access public job postings
Do not apply to jobs or create accounts
Respect robots.txt
Do not scrape PII (recruiter names, emails)
Log all fetches for audit

Confidence Notes

Job posting data provides indirect signals:

Technologies mentioned in job posts may not be currently deployed
"Nice to have" vs "Required" distinction matters
Combine with direct technical evidence for validation
Base confidence: 60-80% (lower than direct signals)

job-posting-analysis