Interview Relevance and Skill Matching
SkillDocs & knowledgeAssess interview notes and job descriptions for skill relevance matching. Score candidate-role fit, highlight skill gaps, evaluate competency alignment, and generate structured hiring recommendations
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What this skill tells your AI
The instructions your AI receives, as published by happy-technologies-llc/happy-platform-skills in skills/hrsd/interview-relevance/SKILL.md and read by ahel’s review.
Overview
This skill assesses interview feedback and job descriptions to evaluate candidate-role fit in ServiceNow HR Service Delivery environments:
- Extracting required skills and competencies from job requisitions and descriptions
- Parsing interview notes to identify demonstrated skills, experience levels, and behavioral indicators
- Scoring candidate-role fit across technical skills, soft skills, and experience criteria
- Highlighting skill gaps between candidate qualifications and role requirements
- Comparing multiple candidates for the same position
- Generating structured hiring recommendations with evidence-based justification
- Tracking interview feedback patterns across hiring panels
When to use: When hiring managers, recruiters, or HR business partners need to evaluate candidate-role alignment, compare candidates objectively, or generate structured assessment summaries from interview feedback.
Prerequisites
- Roles:
sn_hr_core.case_writer,sn_hr_core.manager, oradmin - Plugins:
com.sn_hr_service_delivery(HR Service Delivery),com.snc.assessment(Assessments, optional) - Access: Read/write access to interview feedback tables, job requisition records, and candidate profiles
- Knowledge: Competency framework concepts, structured interview evaluation methods
- Related Skills:
hrsd/resume-skill-extractionfor resume parsing,hrsd/sentiment-analysisfor feedback tone
Procedure
Step 1: Retrieve the Job Requisition and Requirements
Fetch the job description and required competencies for the target role.
MCP Approach:
Tool: SN-Query-Table
Parameters:
table_name: u_job_requisition
query: number=REQ0001234
fields: sys_id,number,u_title,u_department,u_location,u_description,u_required_skills,u_preferred_skills,u_experience_years,u_education,u_salary_range,u_hiring_manager,state
limit: 1
REST Approach:
GET /api/now/table/u_job_requisition
?sysparm_query=number=REQ0001234
&sysparm_fields=sys_id,number,u_title,u_department,u_location,u_description,u_required_skills,u_preferred_skills,u_experience_years,u_education,u_hiring_manager
&sysparm_display_value=true
&sysparm_limit=1
Step 2: Parse and Categorize Role Requirements
Extract structured requirements from the job description text:
Technical Skills (tools, languages, platforms):
- Parse
u_required_skillsfield for explicit skill listings - Extract technology mentions from
u_description(e.g., "Java", "ServiceNow", "AWS") - Categorize as: Required vs Preferred, and by proficiency level expected
Soft Skills (communication, leadership, collaboration):
- Identify behavioral competency requirements from description keywords
- Map to standard competency frameworks if configured
Experience Requirements:
- Minimum years of experience from
u_experience_years - Industry or domain-specific experience from description
- Management or leadership experience indicators
Step 3: Retrieve Interview Feedback Records
Fetch all interview feedback for the candidate on this requisition.
MCP Approach:
Tool: SN-Query-Table
Parameters:
table_name: u_interview_feedback
query: u_candidate=<candidate_sys_id>^u_requisition=<requisition_sys_id>^ORDERBYu_interview_date
fields: sys_id,u_candidate,u_interviewer,u_interview_date,u_interview_type,u_overall_rating,u_technical_rating,u_communication_rating,u_culture_fit_rating,u_notes,u_recommendation,u_strengths,u_concerns
limit: 20
REST Approach:
GET /api/now/table/u_interview_feedback
?sysparm_query=u_candidate=<candidate_sys_id>^u_requisition=<requisition_sys_id>^ORDERBYu_interview_date
&sysparm_fields=sys_id,u_interviewer,u_interview_date,u_interview_type,u_overall_rating,u_technical_rating,u_notes,u_recommendation,u_strengths,u_concerns
&sysparm_display_value=true
&sysparm_limit=20
Step 4: Retrieve Candidate Profile
Get the candidate's background information for context.
MCP Approach:
Tool: SN-Query-Table
Parameters:
table_name: u_candidate
query: sys_id=<candidate_sys_id>
fields: sys_id,u_name,u_email,u_current_title,u_current_company,u_experience_years,u_education,u_skills,u_resume_text,u_source,u_status
limit: 1
Step 5: Extract Skills from Interview Notes
Parse interview notes to identify demonstrated skills and experience:
Analysis framework for each interview feedback record:
- Technical skill mentions: Identify specific technologies, tools, or methodologies mentioned
- Experience depth indicators: Look for keywords like "led", "designed", "implemented", "managed"
- Quantified achievements: Extract metrics (e.g., "reduced downtime by 40%", "managed team of 12")
- Behavioral examples: Identify STAR-format responses (Situation, Task, Action, Result)
- Red flags: Note concerns, gaps, or inconsistencies mentioned by interviewers
Step 6: Score Candidate-Role Fit
Build a structured scoring matrix:
=== SKILL RELEVANCE SCORING ===
Required Technical Skills:
| Skill | Required Level | Candidate Level | Score | Evidence |
|--------------------|---------------|-----------------|-------|----------|
| ServiceNow Dev | Expert | Advanced | 4/5 | "5 years SN development, built 3 scoped apps" |
| JavaScript | Advanced | Advanced | 5/5 | "Strong JS skills demonstrated in coding exercise" |
| ITIL Framework | Intermediate | Basic | 2/5 | "Familiar with ITIL concepts but no certification" |
| REST API Design | Advanced | Advanced | 4/5 | "Designed RESTful integrations at previous role" |
Preferred Technical Skills:
| Skill | Desired Level | Candidate Level | Score | Evidence |
|--------------------|---------------|-----------------|-------|----------|
| Flow Designer | Intermediate | Basic | 2/5 | "Limited exposure, willing to learn" |
| ATF Testing | Basic | None | 0/5 | "No automated testing experience mentioned" |
Soft Skills:
| Competency | Weight | Score | Evidence |
|--------------------|--------|-------|----------|
| Communication | High | 4/5 | "Articulate, clear technical explanations" |
| Problem Solving | High | 5/5 | "Excellent analytical approach in case study" |
| Team Collaboration | Medium | 3/5 | "Works well independently, limited team examples" |
| Leadership | Low | 3/5 | "Mentored 2 junior developers" |
Overall Fit Score: 78/100
Step 7: Identify Skill Gaps and Development Needs
Highlight areas where the candidate falls short of requirements:
=== SKILL GAP ANALYSIS ===
Critical Gaps (Required skills below threshold):
1. ITIL Framework - Candidate: Basic, Required: Intermediate
- Risk: May struggle with ITSM process alignment
- Mitigation: ITIL Foundation certification (2-week course)
2. ATF Testing - Candidate: None, Required: Basic (preferred)
- Risk: Low immediate impact (preferred, not required)
- Mitigation: On-the-job training, pair with senior developer
No Critical Gaps in Required Technical Skills: PASS
Soft Skill Gaps: None identified
Experience Gap: None (5 years vs 3 years minimum)
Step 8: Compare Multiple Candidates (Optional)
If evaluating multiple candidates for the same role:
MCP Approach:
Tool: SN-Query-Table
Parameters:
table_name: u_interview_feedback
query: u_requisition=<requisition_sys_id>^u_recommendation=hire^ORDERBYDESCu_overall_rating
fields: u_candidate,u_overall_rating,u_technical_rating,u_communication_rating,u_recommendation
limit: 50
Generate a comparison matrix:
=== CANDIDATE COMPARISON ===
Position: Senior ServiceNow Developer (REQ0001234)
| Criterion | Candidate A | Candidate B | Candidate C |
|--------------------|-------------|-------------|-------------|
| Technical Score | 78/100 | 85/100 | 72/100 |
| Soft Skills Score | 82/100 | 70/100 | 88/100 |
| Experience Match | 90% | 95% | 75% |
| Skill Gaps | 1 minor | 0 | 2 moderate |
| Panel Consensus | 3/4 Hire | 4/4 Hire | 2/4 Hire |
| Overall Rank | #2 | #1 | #3 |
Step 9: Generate Hiring Recommendation
Compile findings into an actionable recommendation:
=== HIRING RECOMMENDATION ===
Candidate: Alex Chen
Position: Senior ServiceNow Developer (REQ0001234)
RECOMMENDATION: STRONG HIRE
Justification:
- Exceeds technical requirements in 4 of 5 required skill areas
- Demonstrates strong problem-solving through case study performance
- 5 years of relevant experience exceeds 3-year minimum
- Minor gap in ITIL knowledge can be addressed through certification
Panel Summary:
- Phone Screen (Sarah Lee): Hire - "Strong technical foundation"
- Technical Interview (Mike Chen): Strong Hire - "Best coding exercise in this cycle"
- Behavioral Interview (Lisa Park): Hire - "Good cultural fit, collaborative"
- Hiring Manager (Bob Johnson): Hire - "Strong candidate, minor ITIL gap acceptable"
Onboarding Recommendations:
1. Enroll in ITIL Foundation certification within first 30 days
2. Pair with senior developer for ATF testing mentorship
3. Assign initial project in familiar technology stack (JavaScript/REST APIs)
Compensation Recommendation:
- Based on skill assessment: Mid-to-upper range of band ($X - $Y)
- Justification: Above-average technical skills, below-average ITIL knowledge
Step 10: Record the Assessment
Store the structured assessment in ServiceNow.
MCP Approach:
Tool: SN-Update-Record
Parameters:
table_name: u_candidate
sys_id: <candidate_sys_id>
data:
u_status: "Recommended"
u_assessment_summary: "<compiled assessment>"
u_skill_score: 78
u_recommendation: "hire"
Tool Usage
| Tool | Purpose | When to Use |
|---|---|---|
| SN-Query-Table | Fetch requisitions, feedback, candidates | Primary data retrieval |
| SN-Get-Record | Retrieve specific requisition or candidate | Detailed record inspection |
| SN-Create-Record | Create assessment records or feedback entries | Recording new evaluations |
| SN-Update-Record | Update candidate status and scores | Saving assessment results |
| SN-Natural-Language-Search | Search for similar roles or past hires | Pattern matching for benchmarks |
Best Practices
- Use consistent scoring rubrics -- define what each score level means before evaluation
- Require evidence for scores -- every rating should reference specific interview observations
- Separate required vs preferred skills -- do not penalize candidates for missing preferred skills
- Weight skills by role priority -- not all skills are equally important for the position
- Consider growth potential -- a candidate with strong fundamentals may outgrow a gap quickly
- Avoid bias in language analysis -- focus on demonstrated skills, not communication style preferences
- Include development plan -- every gap should have a mitigation strategy
- Cross-reference interviewer calibration -- some interviewers consistently rate higher or lower
- Maintain confidentiality -- restrict assessment access to hiring team members only
- Document objectively -- use behavioral evidence rather than subjective impressions
Troubleshooting
| Issue | Cause | Resolution |
|---|---|---|
| No feedback records found | Custom table name differs | Check actual table name for interview feedback in your instance |
| Skills not parsing from description | Unstructured job description format | Use NL-Search to extract keywords, or request structured input |
| Scores inconsistent across interviewers | No calibration standard | Implement scoring rubric and calibration sessions |
| Candidate profile incomplete | Resume not imported or parsed | Use hrsd/resume-skill-extraction skill to populate profile |
| Comparison not meaningful | Different interview panels | Normalize scores based on interviewer calibration data |
| Assessment not saving | Table permissions restricted | Verify write access to candidate and assessment tables |
Examples
Example 1: Single Candidate Technical Assessment
Input: "Assess interview feedback for candidate Alex Chen against the Senior ServiceNow Developer requisition REQ0001234"
Steps: Retrieve requisition requirements, fetch all interview feedback for the candidate, extract skills from notes, build scoring matrix, identify gaps, generate recommendation with evidence.
Example 2: Panel Consensus Report
Input: "Generate a consensus report for all interviewers who assessed candidate ID CAND0005678"
Steps: Retrieve all feedback records for the candidate, aggregate scores across interviewers, identify areas of agreement and disagreement, flag any split decisions, generate a unified panel recommendation.
Example 3: Multi-Candidate Ranking
Input: "Compare the top 3 candidates for requisition REQ0001234 and rank them"
Steps: Retrieve all candidates with "hire" or "strong hire" recommendations, build comparison matrix across all scoring dimensions, calculate weighted overall scores, generate ranked list with differentiation analysis.
Related Skills
hrsd/resume-skill-extraction- Extract skills from resumes and CVshrsd/sentiment-analysis- Analyze tone and sentiment in feedbackhrsd/case-summarization- General HR case summarizationhrsd/persona-assistant- Persona-based HR assistanceknowledge/gap-analysis- Knowledge gap identification patterns
Signals
- GitHub stars
- 37
- Forks
- 13
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
interview-relevance- Source
- github.com/happy-technologies-llc/happy-platform-skills