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

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'

Analyze Repositories for:

• ML/AI projects (ComfyUI, HuggingFace, PyTorch)

• DevOps tooling (Docker, CI/CD, scripts)

• API/backend experience

• Star counts and activity

Check Pollinations Contributions:

• Merged PRs (high signal)

• Open issues/discussions

• Project submissions

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"