multiAI Summary Pending
Hiring Scorecard Skill
Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions.
3,556 stars
byopenclaw
Installation
Claude Code / Cursor / Codex
$curl -o ~/.claude/skills/afrexai-hiring-scorecard/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1kalin/afrexai-hiring-scorecard/SKILL.md"
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/afrexai-hiring-scorecard/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Hiring Scorecard Skill Compares
| Feature / Agent | Hiring Scorecard Skill | Standard Approach |
|---|---|---|
| Platform Support | multi | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions.
Which AI agents support this skill?
This skill is compatible with multi.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Hiring Scorecard Skill Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions. ## Usage Tell your agent: "Score this candidate for [role]" or "Compare these 3 candidates for the backend engineer role." ## How It Works 1. **Define the role** — provide job title and key requirements 2. **Set criteria** — the agent uses 6 default dimensions (or you customize): - Technical skills (weight: 25%) - Relevant experience (weight: 20%) - Culture fit (weight: 15%) - Communication (weight: 15%) - Problem solving (weight: 15%) - Growth potential (weight: 10%) 3. **Score candidates** — 1-5 scale per criterion after interview/review 4. **Get weighted totals** — ranked comparison with hire/no-hire recommendation ## Commands - `score candidate [name] for [role]` — start a new scorecard - `add criterion [name] weight [%]` — customize scoring dimensions - `compare candidates` — side-by-side ranked comparison - `hiring summary` — executive summary with recommendation ## Scorecard Template ```markdown # Candidate Scorecard: [Name] **Role:** [Title] **Date:** [Date] **Interviewer:** [Name] | Criterion | Weight | Score (1-5) | Weighted | |-----------|--------|-------------|----------| | Technical Skills | 25% | _ | _ | | Relevant Experience | 20% | _ | _ | | Culture Fit | 15% | _ | _ | | Communication | 15% | _ | _ | | Problem Solving | 15% | _ | _ | | Growth Potential | 10% | _ | _ | | **TOTAL** | **100%** | | **_/5.0** | ### Notes - Strengths: - Concerns: - Recommendation: HIRE / NO HIRE / MAYBE ### Scoring Guide 5 = Exceptional — top 5% of candidates seen 4 = Strong — clearly above average 3 = Meets bar — would do the job well 2 = Below bar — notable gaps 1 = Not a fit — significant concerns ``` ## Tips - Score immediately after each interview while impressions are fresh - Have multiple interviewers score independently, then compare - Adjust weights per role (e.g., bump Technical to 40% for senior eng) - Track scores over time to calibrate your hiring bar ## More Business Tools Get industry-specific AI agent context packs at [AfrexAI](https://afrexai-cto.github.io/context-packs/) — pre-built configurations for recruitment, sales, operations, and more. Drop-in and go.