interview-relevance

name	interview-relevance
version	1.0.0
description	Assess interview notes and job descriptions for skill relevance matching. Score candidate-role fit, highlight skill gaps, evaluate competency alignment, and generate structured hiring recommendations
author	Happy Technologies LLC
tags	["hrsd","interview","hiring","talent","skill-matching","candidate-assessment","recruitment","competency"]
platforms	["claude-code","claude-desktop","chatgpt","cursor","any"]
tools	{"mcp":["SN-Query-Table","SN-Get-Record","SN-Create-Record","SN-Update-Record","SN-NL-Search"],"rest":["/api/now/table/sn_hr_core_case","/api/now/table/sn_hr_core_profile","/api/now/table/sys_user","/api/now/table/cmn_department","/api/now/table/u_job_requisition","/api/now/table/u_interview_feedback","/api/now/table/u_candidate","/api/now/table/assessment_instance","/api/now/table/assessment_instance_question"],"native":["Bash"]}
complexity	advanced
estimated_time	15-30 minutes

Interview Relevance and Skill Matching

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, or admin
• 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-extraction for resume parsing, hrsd/sentiment-analysis for 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_skills field 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:

1. Technical skill mentions: Identify specific technologies, tools, or methodologies mentioned
2. Experience depth indicators: Look for keywords like "led", "designed", "implemented", "managed"
3. Quantified achievements: Extract metrics (e.g., "reduced downtime by 40%", "managed team of 12")
4. Behavioral examples: Identify STAR-format responses (Situation, Task, Action, Result)
5. 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-NL-Search	Search for similar roles or past hires	Pattern matching for benchmarks

Best Practices

1. Use consistent scoring rubrics -- define what each score level means before evaluation
2. Require evidence for scores -- every rating should reference specific interview observations
3. Separate required vs preferred skills -- do not penalize candidates for missing preferred skills
4. Weight skills by role priority -- not all skills are equally important for the position
5. Consider growth potential -- a candidate with strong fundamentals may outgrow a gap quickly
6. Avoid bias in language analysis -- focus on demonstrated skills, not communication style preferences
7. Include development plan -- every gap should have a mitigation strategy
8. Cross-reference interviewer calibration -- some interviewers consistently rate higher or lower
9. Maintain confidentiality -- restrict assessment access to hiring team members only
10. 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 CVs
• hrsd/sentiment-analysis - Analyze tone and sentiment in feedback
• hrsd/case-summarization - General HR case summarization
• hrsd/persona-assistant - Persona-based HR assistance
• knowledge/gap-analysis - Knowledge gap identification patterns