AI Skill Report Card

Testing and Validation Skill

B+88·Jan 10, 2026

This skill enables AI to systematically test, validate, and verify functionality, processes, or outputs to ensure quality, reliability, and correctness. It encompasses creating test cases, executing validation procedures, and identifying potential issues before deployment or implementation.

Step 1: Define Testing Scope

  • Identify what needs to be tested (functionality, performance, edge cases)
  • Establish success criteria and acceptance thresholds
  • Document assumptions and constraints

Step 2: Design Test Strategy

  • Create comprehensive test plan covering all scenarios
  • Prioritize test cases by risk and impact
  • Select appropriate testing methods (unit, integration, system, user acceptance)

Step 3: Prepare Test Environment

  • Set up controlled testing conditions
  • Gather necessary test data and resources
  • Establish baseline measurements

Step 4: Execute Tests

  • Run tests systematically following documented procedures
  • Record results, observations, and anomalies
  • Maintain detailed logs of all test activities

Step 5: Analyze Results

  • Compare actual outcomes against expected results
  • Identify patterns in failures or successes
  • Assess severity and priority of any issues found

Step 6: Report and Recommend

  • Document findings clearly and comprehensively
  • Provide actionable recommendations for improvements
  • Suggest retesting procedures for fixes
  • Start with simple, basic tests before complex scenarios
  • Test both positive and negative cases
  • Use realistic data that mirrors production conditions
  • Automate repetitive tests when possible
  • Maintain traceability between requirements and test cases
  • Test early and often throughout development cycles
  • Document everything for reproducibility

Test Case Template

Test Case ID: TC-XXX
Title: [Brief description]
Preconditions: [Setup requirements]
Test Steps: 
1. [Action]
2. [Action]
Expected Result: [What should happen]
Actual Result: [What actually happened]
Status: [Pass/Fail/Blocked]
Notes: [Additional observations]

Test Report Template

Test Summary Report
- Total Tests: X
- Passed: X (X%)
- Failed: X (X%)
- Blocked: X (X%)

Critical Issues: [High priority failures]
Recommendations: [Next steps]
Risk Assessment: [Impact analysis]

Good Testing Approach

  • Comprehensive: Tests cover normal use, edge cases, and error conditions
  • Systematic: Follows documented procedures with clear steps
  • Objective: Uses measurable criteria for pass/fail decisions
  • Documented: Maintains detailed records of all activities and results

Poor Testing Approach

  • Ad-hoc: Random testing without systematic approach
  • Incomplete: Missing critical scenarios or edge cases
  • Subjective: Relies on opinions rather than measurable criteria
  • Undocumented: No record of what was tested or results
Recommendation
Add specific examples of testing tools, frameworks, or metrics (e.g., code coverage percentages, response time thresholds, specific automation tools like Selenium or Jest)
  • Don't test only the "happy path" - include error conditions
  • Don't assume previous tests are still valid after changes
  • Don't skip documentation because "it's just a quick test"
  • Don't test in production environments without proper safeguards
  • Don't ignore seemingly minor issues without proper assessment
  • Don't proceed without clear pass/fail criteria
  • Don't test with insufficient or unrealistic data
  • Don't rely solely on manual testing for repetitive tasks
0
Grade B+AI Skill Framework
Scorecard
Criteria Breakdown
Quick Start
11/15
Workflow
11/15
Examples
15/20
Completeness
15/20
Format
11/15
Conciseness
11/15