candidate-evaluation

pollinations's avatarfrom pollinations

Evaluate GitHub contributors for MLOps/engineering roles. Use when analyzing candidates, researching GitHub profiles, or updating CONTRIBUTORS.md with hiring assessments.

⭐3.7kstars🔀559forks📁View on GitHub🕐Updated Jan 11, 2026
[Hiring Operations]

When & Why to Use This Skill

This Claude skill automates the technical evaluation of GitHub contributors specifically for MLOps and engineering roles. By leveraging GitHub API data to analyze repository history, code quality, and contribution patterns, it provides a comprehensive fit score and structured hiring recommendations, significantly streamlining the technical screening process for recruiters and engineering managers.

Use Cases

  • Technical Candidate Screening: Automatically assess a candidate's proficiency in Python, DevOps, and ML deployment by analyzing their public GitHub repositories and contribution history.
  • Open Source Talent Research: Deep-dive into GitHub profiles to identify high-quality contributors based on PR quality, documentation habits, and technical stack alignment.
  • Structured Hiring Reports: Generate detailed candidate profiles featuring ASCII-based skills matrices, strengths/weaknesses analysis, and a final hiring verdict for internal review.
  • Contributor Documentation Management: Efficiently update project files like CONTRIBUTORS.md with standardized hiring assessments and fit scores for better talent tracking.
namecandidate-evaluation
descriptionEvaluate GitHub contributors for MLOps/engineering roles. Use when analyzing candidates, researching GitHub profiles, or updating CONTRIBUTORS.md with hiring assessments.
allowed-tools"Read, Write, Edit, Grep, Bash(gh api:*), Bash(git:*)"

Candidate Evaluation Skill

Evaluate GitHub contributors for engineering roles at Pollinations.

When to Use

  • User asks to evaluate a contributor or candidate
  • User wants to research GitHub profiles for hiring
  • User needs to update CONTRIBUTORS.md with candidate analysis
  • User mentions "hiring", "candidate", "MLOps", or "evaluate contributor"

Evaluation Criteria

Must-Have Skills (Weight: High)

  • Python: Primary language proficiency
  • DevOps: Docker, CI/CD, infrastructure
  • GPU/ML Deployment: Model serving, inference optimization

Nice-to-Have Skills (Weight: Medium)

  • Kubernetes, vLLM, TGI
  • Quantization (GGUF, ONNX)
  • CI/CD pipelines (GitHub Actions)

Work Style Indicators (Weight: Medium)

  • PR size preference (small, focused = good)
  • Response time to reviews
  • Documentation quality
  • Test coverage habits

Evaluation Process

  1. Gather Data via GitHub MCP or gh api:

    # Get user repos
gh api users/{username}/repos --jq '.[].name'

# Search PRs in pollinations
gh api search/issues -X GET -f q='repo:pollinations/pollinations author:{username}'

# Search code for MLOps keywords
gh api search/code -X GET -f q='user:{username} docker OR kubernetes OR gpu OR vllm'

  2. Analyze Repositories for:

    • ML/AI projects (ComfyUI, HuggingFace, PyTorch)
    • DevOps tooling (Docker, CI/CD, scripts)
    • API/backend experience
    • Star counts and activity

  3. Check Pollinations Contributions:

    • Merged PRs (high signal)
    • Open issues/discussions
    • Project submissions

  4. Generate Profile with:

    • Fit score (1-10)
    • Strengths (bullet points)
    • Weaknesses (bullet points)
    • Key repositories table
    • Hiring recommendation

Output Format

Use ASCII box art for visual appeal:

┌─────────────────────────────────────────────────────────────────────────────┐
│  FIT: X.X/10  │  GitHub: username  │  Repos: N  │  Focus: Area             │
└─────────────────────────────────────────────────────────────────────────────┘

✅ STRENGTHS

  • Point 1
  • Point 2

❌ WEAKNESSES

  • Point 1
  • Point 2

📦 KEY REPOS

Repo Tech What It Does

🎯 VERDICT: Recommendation

Skills Matrix Format

╔═══════════════════╦════════╦════════╦════════╦═══════════════╗
║     CANDIDATE     ║ Python ║ GPU/ML ║ Docker ║   FIT SCORE   ║
╠═══════════════════╬════════╬════════╬════════╬═══════════════╣
║ username          ║ █████  ║ ███    ║ ████   ║     X.X/10    ║
╚═══════════════════╩════════╩════════╩════════╩═══════════════╝

Legend: █ = Skill Level (1-5)

Reference Files

  • AGENTS.md - Project guidelines and contributor attribution

Example Queries

  • "Evaluate @username for MLOps role"
  • "Research GitHub profile for {username}"
  • "Add {username} to CONTRIBUTORS.md"
  • "Compare candidates X and Y"