AI Skill Report Card
Evaluating Resumes
YAML--- name: evaluating-resumes description: Evaluates resumes using the MATCH format methodology and LinkedIn profile analysis. Use when screening candidates or assessing job fit. ---
Quick Start
MATCH Evaluation Framework:
M - Motivation: Why do they want this role/company?
A - Ability: Do they have required skills/experience?
T - Tenure: How long do they stay at jobs?
C - Culture: Will they fit the team/company culture?
H - Hire-ability: Overall recommendation and reasoning
Recommendation▾
Add a concrete template or scorecard format for consistent evaluation documentation
Workflow
Resume + LinkedIn Review Process:
Progress:
- Initial scan (30 seconds): Role relevance, experience level, red flags
- MATCH deep dive (5 minutes): Systematic evaluation
- LinkedIn cross-reference (2 minutes): Verify details, culture indicators
- Decision + notes (1 minute): Hire/pass with reasoning
Detailed Steps:
-
Quick Scan
- Job titles progression
- Employment gaps >6 months
- Required skills present
- Location/relocation needs
-
MATCH Analysis
- M: Cover letter enthusiasm, career moves logic
- A: Skills match (must-have vs nice-to-have), quantified achievements
- T: Average tenure, reasons for leaving pattern
- C: Company types, team size preferences, work style indicators
- H: Overall score 1-5, specific next steps
-
LinkedIn Cross-Check
- Verify employment dates/titles
- Recommendations quality
- Activity/posts for culture fit
- Network connections in industry
Recommendation▾
Include specific examples of red flags and what questions to ask about them in interviews
Examples
Example 1: Input: Software Engineer resume, 5 years experience, seeking senior role
MATCH Score: 4/5
M: Strong - mentions specific interest in our tech stack
A: High - React/Node.js + relevant projects, 20% performance improvements shown
T: Good - 2-3 year tenures, logical progressions
C: Fit - contributes to open source, mentoring experience
H: ADVANCE - Schedule technical interview
Red flags: None
LinkedIn: Confirms details, active in tech communities
Example 2: Input: Marketing Manager, frequent job changes
MATCH Score: 2/5
M: Unclear - generic cover letter
A: Partial - relevant experience but no metrics/results shown
T: Concerning - 6 jobs in 4 years, no clear pattern
C: Unknown - limited culture indicators
H: PASS - Tenure concerns outweigh experience
Red flags: Job hopping without growth trajectory
LinkedIn: Sparse profile, few recommendations
Recommendation▾
Provide guidance on how to weight different MATCH components based on role seniority or type
Best Practices
- Speed matters: Aim for 8-minute total evaluation per candidate
- Document red flags immediately: Gaps, inconsistencies, culture mismatches
- Use LinkedIn activity for culture fit: Posts, comments, groups show values
- Weight recent experience heaviest: Last 2-3 roles most predictive
- Look for growth trajectory: Increasing responsibility, not just job changes
- Check mutual connections: Internal referrals carry weight
Common Pitfalls
- Don't just keyword match: Skills without context/results are weak signals
- Don't ignore soft red flags: "Seeking new challenges" every 12 months
- Don't skip LinkedIn: Resume dates often don't match LinkedIn
- Don't over-index on education: Experience trumps degrees for most roles
- Don't assume remote preferences: Verify location/travel expectations
- Don't rush the culture assessment: Bad culture fits are expensive mistakes