/resume-screener

name: resume-screener
description: Screen resumes efficiently against job requirements with structured scoring, red flag identification, and interview recommendations
license: MIT
metadata:
  author: ClawFu
  version: 1.0.0
  mcp-server: "@clawfu/mcp-skills"

Resume Screener

> Systematically evaluate resumes against job requirements to identify qualified candidates, flag concerns, and prioritize for interviews.

When to Use This Skill

• High-volume application screening
• Creating screening criteria
• Building evaluation rubrics
• Training hiring managers
• Audit of screening consistency

Methodology Foundation

Based on **structured interviewing research** and **EEOC guidelines**, combining:

• Job-related criteria only
• Objective scoring rubrics
• Bias-aware evaluation
• Documentation requirements

What Claude Does vs What You Decide

| Claude Does | You Decide | |-------------|------------| | Creates screening rubrics | Hiring decisions | | Scores against criteria | Culture fit assessment | | Identifies red/green flags | Interview invitation | | Summarizes qualifications | Final selection | | Flags potential concerns | Exception handling |

Instructions

Step 1: Define Job Criteria

**Required vs. Preferred:** | Category | Must Have | Nice to Have | |----------|-----------|--------------| | Education | Minimum degree | Advanced degree | | Experience | X years in Y | Specific industry | | Skills | Core technical | Adjacent skills | | Certifications | Required licenses | Preferred certs |

**Scoring Weight:** | Criterion | Weight | Rationale | |-----------|--------|-----------| | Required experience | 40% | Core capability | | Required skills | 30% | Day-one impact | | Education | 15% | Foundation | | Preferred qualifications | 15% | Growth potential |

Step 2: Create Screening Rubric

**Scoring Scale:** | Score | Definition | |-------|------------| | 4 | Exceeds requirement significantly | | 3 | Meets requirement fully | | 2 | Partially meets requirement | | 1 | Does not meet requirement | | 0 | Cannot assess from resume |

Step 3: Evaluate Resume

**Assessment Framework:** 1. Check must-have requirements (binary pass/fail) 2. Score each criterion (1-4 scale) 3. Calculate weighted total 4. Identify flags (red and green) 5. Make recommendation

Step 4: Document Findings

**For Each Resume:**

• Overall score
• Must-have checklist
• Criterion-by-criterion scores
• Flags and concerns
• Recommendation with rationale

Step 5: Prioritize Candidates

**Priority Matrix:** | Score Range | Action | |-------------|--------| | 80-100% | Priority interview | | 60-79% | Standard review | | 40-59% | Conditional hold | | <40% | Not qualified |

Examples

Example 1: Full Resume Screening

**Input:**

Job: Senior Product Manager

Requirements:
- 5+ years product management experience
- B2B SaaS background required
- Technical degree or equivalent experience
- Experience with Agile methodologies
- Preferred: MBA or similar

Resume:
Jane Smith
Product Manager at TechCorp (3 years)
- Led product roadmap for B2B analytics platform
- Managed team of 4 designers and engineers
- Increased user retention by 35%

Associate PM at StartupXYZ (2 years)
- B2C mobile app
- Launched 3 major features

Education: BS Computer Science, Stanford
Certifications: CSPO, SAFe Agilist

**Output:**

## Resume Screening: Jane Smith

### Quick Summary
**Position:** Senior Product Manager
**Candidate:** Jane Smith
**Score:** 78/100 - STANDARD REVIEW

---

### Must-Have Requirements

| Requirement | Status | Evidence |
|-------------|--------|----------|
| 5+ years PM experience | ✅ PASS | 3 + 2 = 5 years total |
| B2B SaaS background | ✅ PASS | TechCorp B2B analytics |
| Technical degree/equivalent | ✅ PASS | BS CS Stanford |
| Agile experience | ✅ PASS | CSPO, SAFe certifications |

**Must-Have Result:** PASS (4/4)

---

### Detailed Scoring

| Criterion | Weight | Score | Weighted | Notes |
|-----------|--------|-------|----------|-------|
| Years of Experience | 40% | 3/4 | 30/40 | Meets minimum exactly |
| B2B SaaS | 30% | 3/4 | 22.5/30 | 3 years, not full tenure |
| Technical Background | 15% | 4/4 | 15/15 | Stanford CS |
| Preferred (MBA) | 15% | 2/4 | 7.5/15 | Has certs, no MBA |

**Total Score: 75/100**

---

### Green Flags

| Flag | Evidence | Significance |
|------|----------|--------------|
| Quantified impact | "35% retention increase" | Results-oriented |
| Management experience | "Team of 4" | Leadership ready |
| Relevant certifications | CSPO, SAFe | Agile commitment |
| Top-tier education | Stanford CS | Technical foundation |

---

### Yellow Flags

| Flag | Concern | Mitigation |
|------|---------|------------|
| Experience exactly at minimum | Just hits 5 years | Probe depth in interview |
| Mixed B2B/B2C | 2 years in B2C | Understand B2B transition |
| No MBA | Preferred qualification | Certs may compensate |

---

### Red Flags

None identified.

---

### Interview Recommendation

**Decision:** RECOMMEND FOR INTERVIEW

**Rationale:**
- Meets all must-have requirements
- Strong B2B SaaS experience at TechCorp
- Technical background exceeds expectations
- Quantified achievements show impact

**Interview Focus Areas:**
1. Depth of B2B product strategy experience
2. Transition from B2C to B2B context
3. Scale of products managed (ARR, users)
4. Examples of cross-functional leadership

---

### Comparison Notes

Candidate is solid but not exceptional. Meets requirements without
significantly exceeding them. Consider alongside stronger candidates
if available.

Example 2: Batch Screening Summary

**Input:**

Screen these 5 candidates for Marketing Manager:
Requirements: 3+ years marketing, B2B experience, analytics skills

1. Alice: 5 years B2B marketing, Google Analytics certified
2. Bob: 2 years marketing, B2C only, strong analytics
3. Carol: 4 years, mixed B2B/B2C, basic Excel
4. David: 6 years B2B, owns marketing analytics tool
5. Eve: 3 yea