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candidate-evaluation

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

mattnigh/skills_collection0installs24starsDevOps & CI/CD

SKILL.md

Full skill instructions

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

RepoTechWhat 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

  • pollinator-agent/​CONTRIBUTORS.md - Current contributor analysis
  • 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"