---
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 years B2B, HubSpot certified
```

**Output:**
```
## Batch Screening Summary: Marketing Manager

### Quick Rank

| Rank | Candidate | Score | Recommendation |
|------|-----------|-------|----------------|
| 1 | David | 95% | Priority Interview |
| 2 | Alice | 85% | Priority Interview |
| 3 | Eve | 75% | Standard Review |
| 4 | Carol | 55% | Conditional Hold |
| 5 | Bob | 40% | Not Qualified |

---

### Individual Summaries

#### 1. David (95%) - PRIORITY INTERVIEW

| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ 6 years | 4/4 |
| B2B experience | ✅ Full tenure | 4/4 |
| Analytics skills | ✅ Tool owner | 4/4 |

**Standout:** Exceptional analytics depth - owns a marketing analytics tool
**Interview:** Immediately

---

#### 2. Alice (85%) - PRIORITY INTERVIEW

| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ 5 years | 4/4 |
| B2B experience | ✅ Full tenure | 4/4 |
| Analytics skills | ✅ GA certified | 3/4 |

**Standout:** Solid all-around, Google Analytics certification
**Interview:** This week

---

#### 3. Eve (75%) - STANDARD REVIEW

| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ Exactly 3 | 3/4 |
| B2B experience | ✅ Full tenure | 4/4 |
| Analytics skills | ⚠️ HubSpot only | 2/4 |

**Concern:** HubSpot is automation, not analytics
**Interview:** Probe analytics skills deeper

---

#### 4. Carol (55%) - CONDITIONAL HOLD

| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ 4 years | 3/4 |
| B2B experience | ⚠️ Mixed | 2/4 |
| Analytics skills | ❌ Basic Excel | 1/4 |

**Concern:** Weak analytics foundation
**Hold:** Consider if top candidates decline

---

#### 5. Bob (40%) - NOT QUALIFIED

| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ❌ 2 years | 1/4 |
| B2B experience | ❌ B2C only | 1/4 |
| Analytics skills | ✅ Strong | 3/4 |

**Disqualified:** Does not meet experience or B2B requirements
**Action:** Reject with positive note on analytics skills

---

### Screening Actions

| Action | Candidates |
|--------|------------|
| Schedule interviews | David, Alice |
| Standard queue | Eve |
| Hold file | Carol |
| Rejection email | Bob |
```

## Skill Boundaries

### What This Skill Does Well
- Structuring evaluation criteria
- Consistent scoring application
- Identifying relevant flags
- Documenting decisions

### What This Skill Cannot Do
- Assess culture fit
- Verify claims accuracy
- Conduct background checks
- Replace human judgment

### Important Compliance Notes
- Focus only on job-related criteria
- Avoid protected class considerations
- Document all decisions
- Apply criteria consistently

## Iteration Guide

**Follow-up Prompts:**
- "Create interview questions based on this screening"
- "What should I probe further with [candidate]?"
- "Compare these top 3 candidates side by side"
- "Draft rejection email for [candidate]"

## References

- SHRM Structured Interviewing Guidelines
- EEOC Uniform Guidelines on Employee Selection
- Google re:Work Hiring Practices
- Lever Recruiting Best Practices

## Related Skills

- `interview-scheduler` - Coordinate interviews
- `onboarding-guide` - Post-hire integration
- `job-description-writer` - Create requirements

## Skill Metadata

- **Domain**: HR Operations
- **Complexity**: Intermediate
- **Mode**: centaur
- **Time to Value**: 10-15 min per resume
- **Prerequisites**: Job requirements, resumes


---
Source attribution: guia-matthieu
Original project: https://github.com/guia-matthieu/clawfu-skills/blob/4108f5c010ccaa8b5707fa05ca1d888ae167e548/skills/hr-ops/resume-screener/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Guia

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: guia-matthieu
Original project: https://github.com/guia-matthieu/clawfu-skills/blob/4108f5c010ccaa8b5707fa05ca1d888ae167e548/skills/hr-ops/resume-screener/SKILL.md
Attribution basis: Source repository record

Fields of work: Human Resources, Operations
Roles: Business Process Analyst, HR Generalist, Recruiter
Specialties: Specialty not specified
Tools: Tool not specified
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: b950a32ec355db572f3b5c1e304e8397329fdf48efd0027cfde491496be29dde