Assess non-functional requirements across 6 quality categories (Security, Performance, Reliability, Maintainability, Scalability, Usability) with measurable criteria, evidence-based evaluation, and automated checks. Scores each category, identifies gaps with severity ratings, and provides remediation guidance. Use during quality review to evaluate production readiness and NFR compliance.
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SKILL.md
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name
nfr-assess
description
Assess non-functional requirements across 6 quality categories (Security, Performance, Reliability, Maintainability, Scalability, Usability) with measurable criteria, evidence-based evaluation, and automated checks. Scores each category, identifies gaps with severity ratings, and provides remediation guidance. Use during quality review to evaluate production readiness and NFR compliance.
version
2
category
Quality
acceptance
{"all_categories_assessed":"All 6 NFR categories (Security, Performance, Reliability, Maintainability, Scalability, Usability) scored with evidence","gaps_identified":"NFR gaps documented with severity ratings (CRITICAL/HIGH/MEDIUM) and remediation guidance","automated_checks_executed":"Automated checks run where available (security scans, linting, test coverage, performance tests)","report_generated":"Complete NFR assessment report generated with overall score, category scores, gap summary, and recommendations"}
inputs
{"task_id":{"required":true,"description":"Task identifier to assess (e.g., 'task-007')"},"task_file":{"required":true,"description":"Path to task specification file"},"config_file":{"required":false,"description":"Path to project configuration (defaults to .claude/config.yaml)"},"nfr_thresholds":{"required":false,"description":"Custom NFR thresholds (security, performance, maintainability)"}}
outputs
{"overall_nfr_score":{"description":"Weighted overall NFR score (0-100)"},"category_scores":{"description":"Individual scores for each of 6 NFR categories"},"overall_status":{"description":"Overall NFR status (PASS/CONCERNS/FAIL)"},"critical_gaps_count":{"description":"Number of critical NFR gaps (P0)"},"high_gaps_count":{"description":"Number of high-severity NFR gaps (P1)"},"report_path":{"description":"Path to generated NFR assessment report"},"quality_gate_impact":{"description":"Predicted impact on quality gate (PASS/CONCERNS/FAIL)"}}
The nfr-assess skill performs comprehensive evaluation of non-functional requirements (NFRs) to ensure the implementation meets quality attributes beyond functional correctness. NFRs are cross-cutting concerns that determine system quality, reliability, and long-term viability. This skill assesses 6 critical quality categories with measurable criteria, evidence-based evaluation, and automated checks where possible.
Unlike functional requirements that define what the system does, non-functional requirements define how well the system performs. This skill provides objective assessment across Security (authentication, encryption, vulnerabilities), Performance (response times, throughput, resource usage), Reliability (error handling, monitoring, fault tolerance), Maintainability (code quality, documentation, testability), Scalability (horizontal scaling, database design, async processing), and Usability (API design, error messages, documentation).
The assessment produces a weighted overall NFR score, individual category scores, identifies gaps with severity ratings, and provides actionable recommendations. Results feed directly into the quality-gate skill to inform merge/release decisions. Automated checks (security scans, linting, test coverage, performance tests) are integrated where available to provide objective, reproducible metrics.
When to Use This Skill
This skill should be used when:
Non-functional quality attributes need validation during implementation review
System-wide quality concerns (security, performance, reliability) need assessment
Gaps in quality attributes need identification with severity ratings
Evidence-based NFR reports are required for audit/compliance
NFR metrics need to feed into quality gate decision-making
Production readiness needs validation from quality perspective
This skill is particularly valuable:
Before quality gate review (identifies issues early)
After functional testing completes (assess non-functional aspects)
During architectural review (validate design patterns for NFRs)
When preparing for production deployment (ensure production readiness)
For compliance validation (OWASP, WCAG, performance budgets)
This skill should NOT be used when:
Functional requirements haven't been implemented yet (assess functionality first)
Task is purely planning/design (no implementation to assess)
You only need to test functional behavior (use run-tests instead)
Prerequisites
Before running nfr-assess, ensure you have:
Task specification file with implementation record
Project configuration (.claude/config.yaml) with quality settings
Implementation files accessible for code review
Automated tools available (optional but recommended):
Security: npm audit, semgrep, or equivalent
Code quality: linter (eslint, pylint, etc.)
Test coverage: coverage tools (jest --coverage, pytest-cov, etc.)
Optional: test-design (provides performance/load test specifications)
Sequential NFR Assessment Process
This skill executes through 9 sequential steps. Each step must complete successfully before proceeding. The process is designed to systematically evaluate all 6 NFR categories with evidence collection, automated checks, and gap identification.
Step 0: Load Configuration and Context
Purpose: Load project configuration, task specification, and all relevant context needed for NFR assessment. Identify implementation files, prepare automated checks, and determine which NFR categories are most relevant based on task type.
Actions:
Load project configuration from .claude/config.yaml (quality settings, NFR thresholds)
See:references/templates.md#step-1-security-assessment-output for complete format, nfr-categories.md for criteria, nfr-examples.md for evidence examples
Step 2: Performance Assessment
Purpose: Evaluate performance characteristics including response times, throughput, resource usage, caching, and optimization. Run performance tests if available, analyze database queries for N+1 problems, and check algorithm complexity in hot paths.
Output: Overall performance score, response time metrics (p50/p95/p99), throughput, load test results, performance gaps
See:references/templates.md#step-2-performance-assessment-output for complete format with benchmark tables
Step 3: Reliability Assessment
Purpose: Evaluate system reliability including error handling, fault tolerance, recovery, monitoring, and logging. Check for comprehensive error handling, graceful degradation when dependencies fail, and proper observability (logging, monitoring, health checks).
Identify reliability gaps (e.g., no monitoring, no log aggregation, missing health checks)
Output: Overall reliability score, error handling status, logging status (structured/aggregation), monitoring status (health checks/metrics), reliability gaps
See:references/templates.md#step-3-reliability-assessment-output for complete format
Step 4: Maintainability Assessment
Purpose: Evaluate code maintainability including code quality, documentation, testability, modularity, and technical debt. Leverage automated tools (linting, test coverage, complexity analysis) and manual review for documentation, naming, and code organization.
Actions:
Define maintainability criteria (10 criteria: code quality, test coverage, documentation, modularity, naming, complexity, duplication, type safety, dependencies, technical debt)
Run automated maintainability checks:
Linting (npm run lint or equivalent)
Test coverage (npm run test:coverage)
Complexity analysis (cyclomatic complexity ≤10?)
Duplication detection (jscpd, etc.)
Type checking (TypeScript strict mode)
Manual code review for maintainability:
Check code structure and organization
Check naming conventions (clear, descriptive?)
Check function/class sizes (≤50 lines?)
Check documentation completeness (README, API docs, JSDoc)
See:references/templates.md#step-4-maintainability-assessment-output for complete format with metrics breakdown
Step 5: Scalability Assessment
Purpose: Evaluate system scalability including horizontal/vertical scaling capability, load handling, database design, and caching strategy. Check for stateless design, proper database indexing, async processing for expensive operations, and readiness for load balancing.
See:references/templates.md#step-5-scalability-assessment-output for complete format with DB analysis
Step 6: Usability Assessment
Purpose: Evaluate system usability including API design, error messages, documentation, and accessibility (if UI). For APIs, check RESTful conventions, error message clarity, and API documentation. For UIs, check WCAG compliance, responsive design, and user experience.
Actions:
Define usability criteria:
For APIs (10 criteria): API design, error messages, documentation, versioning, pagination, filtering, HTTP status codes, response format, HATEOAS, developer experience
For UIs (10 criteria): accessibility (WCAG 2.1 AA), responsive design, loading states, error handling, keyboard navigation, color contrast, screen reader support, form validation, intuitive navigation, performance
See:references/templates.md#step-6-usability-assessment-output for API and UI formats
Step 7: Generate NFR Assessment Report
Purpose: Create comprehensive NFR assessment report using template with all category assessments, overall score calculation, gap summary, and recommendations.
Actions:
Load NFR assessment template
Compute overall NFR score using weighted formula (Security 25%, Performance 20%, Reliability 20%, Maintainability 15%, Scalability 10%, Usability 10%)
See:references/templates.md#step-7-overall-nfr-scoring-formula for complete formula and examples, nfr-scoring.md for methodology, nfr-gaps.md for gap categorization
Step 8: Present Summary to User
Purpose: Provide concise summary with key metrics, critical gaps, quality gate impact, and recommended next steps.
Actions:
Display formatted summary: Task metadata, overall NFR score/status, category scores (6), critical gaps (P0), high gaps (P1), quality gate impact + reasoning, actionable recommendations with time estimates, report path
Suggest next steps: Review report, prioritize P0 gaps, create tickets for P1 gaps, re-run after fixes, proceed to quality-gate when ≥75%
Emit telemetry
Output: Complete formatted summary with scores, gaps, quality gate prediction, recommendations, next steps
See:references/templates.md#step-8-complete-user-summary-format for full formatted output, nfr-examples.md for examples
Integration with Other Skills
Integration with risk-profile: Security/performance/reliability risks from risk profile inform NFR assessment priorities and amplify gap severity (e.g., HIGH gap + HIGH risk = CRITICAL P0)
Integration with trace-requirements: Implementation evidence validates NFR implementation; NFR gaps feed back as coverage gaps in traceability matrix
Integration with test-design: Performance/load/security test specifications inform corresponding NFR category assessments
Integration with quality-gate: Overall NFR score + category scores + critical gaps feed into quality gate decision (≥90%: PASS-excellent, 75-89%: PASS-good, 60-74%: CONCERNS, <60%: FAIL; Security/Reliability <50%: production blocker)
See:references/templates.md#integration-examples for detailed integration workflows and decision logic
Best Practices
Run NFR assessment before quality gate | Integrate automated checks (security, linting, coverage) | Document evidence thoroughly (file paths, line numbers, snippets) | Prioritize Security and Reliability (production blockers) | Set measurable thresholds in config | Re-run after fixes to validate | Customize category weights per project | Review with stakeholders (cross-functional decisions)
