Hiring Scorecard Skill
Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions.
About this skill
The Hiring Scorecard Skill empowers AI agents to objectively evaluate and compare job candidates based on weighted criteria. It enables users to define specific roles, customize scoring dimensions (like technical skills, experience, or culture fit), and then score candidates on a 1-5 scale across these factors. The agent then calculates weighted totals, provides a ranked comparison, and offers a hire/no-hire recommendation. This skill is invaluable for recruiters, hiring managers, and interview teams aiming to standardize their candidate assessment process. By using predefined commands to score individual candidates or compare multiple applicants, it ensures a consistent and transparent evaluation. It eliminates subjective biases, providing a data-driven approach to identify the best fit for any role. Users benefit from a structured scorecard template that includes strengths, concerns, and a clear recommendation, making post-interview debriefs more efficient and informed. The ability to adjust criterion weights allows for tailored evaluations, ensuring that the most critical aspects of a role are emphasized, ultimately leading to more confident and effective hiring decisions.
Best use case
The primary use case for this skill is to bring objectivity and structure to the job candidate evaluation process. Recruiters, hiring managers, and interviewers can leverage it to score individual candidates or compare multiple applicants side-by-side, ensuring consistent assessment against predefined criteria. This helps in making data-driven hiring decisions and reducing subjective bias.
Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions.
Users can expect a structured candidate scorecard with weighted scores, a ranked comparison of applicants, and clear hire/no-hire recommendations, facilitating objective hiring decisions.
Practical example
Example input
Compare candidates Alice, Bob, and Carol for the Marketing Manager role. Alice: Tech Skills 4, Exp 5, Culture 4, Comm 5, Prob Solv 4, Growth 4. Bob: Tech Skills 3, Exp 4, Culture 3, Comm 3, Prob Solv 3, Growth 3. Carol: Tech Skills 5, Exp 5, Culture 5, Comm 5, Prob Solv 5, Growth 5.
Example output
Here is a comparison of candidates for the Marketing Manager role: 1. Carol: Total Score 4.8/5.0 (Strong Hire Recommendation) 2. Alice: Total Score 4.2/5.0 (Hire Recommendation) 3. Bob: Total Score 3.2/5.0 (No Hire Recommendation) Carol is recommended due to exceptional performance across all criteria, especially Communication and Culture Fit. Alice is a strong candidate, scoring well in experience. Bob has notable gaps in multiple areas.
When to use this skill
- When evaluating job candidates immediately after interviews.
- To compare multiple applicants for a specific role side-by-side.
- To standardize candidate assessment across an interviewing team.
- When seeking to document objective feedback for hiring decisions.
When not to use this skill
- For initial resume screening or pre-interview qualification.
- When quick, informal feedback without structured scoring is sufficient.
- If the hiring process requires purely qualitative, unstructured feedback.
- If you lack sufficient interview or assessment data to score candidates meaningfully.
Installation
Claude Code / Cursor / Codex
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 | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
Score and compare job candidates objectively using weighted criteria. Eliminates gut-feel hiring decisions.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
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.
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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.
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