/test-design-techniques
Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage.
$ npx -y skills add proffesor-for-testing/agentic-qe --skill test-design-techniques --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/test-design-techniques
Context preview
The summary Claude sees to decide when to auto-load this skill.
Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage.
SKILL.md
test-design-techniques.SKILL.mdname: test-design-techniques
description: "Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage."
category: specialized-testing
priority: high
tokenEstimate: 900
agents: [qe-test-generator, qe-coverage-analyzer, qe-quality-analyzer]
implementation_status: optimized
optimization_version: 1.0
last_optimized: 2025-12-02
dependencies: []
quick_reference_card: true
tags: [test-design, bva, equivalence-partitioning, decision-tables, pairwise, state-transition]
trust_tier: 3
validation:
schema_path: schemas/output.json
validator_path: scripts/validate-config.json
eval_path: evals/test-design-techniques.yaml
Test Design Techniques
<default_to_action> When designing test cases, select technique by input type:
- Numeric ranges → BVA + EP
- Multiple conditions → Decision Tables
- Workflows → State Transition
- Many parameter combinations → Pairwise Testing
</default_to_action>
Quick Reference Card
When to Use
- Designing new test suites
- Optimizing existing tests
- Complex business rules
- Reducing test redundancy
---
Agent-Driven Test Design
// Auto-generate BVA tests
await Task("Generate BVA Tests", {
field: 'age',
dataType: 'integer',
constraints: { min: 18, max: 120 }
}, "qe-test-generator");
// Returns: 6 boundary test cases
// Auto-generate pairwise tests
await Task("Generate Pairwise Tests", {
parameters: {
browser: ['Chrome', 'Firefox', 'Safari'],
os: ['Windows', 'Mac', 'Linux'],
screen: ['Desktop', 'Tablet', 'Mobile']
}
}, "qe-test-generator");
// Returns: 9-12 tests (vs 27 full combination)---
Agent Coordination Hints
Memory Namespace
aqe/test-design/
├── bva-analysis/* - Boundary value tests
├── partitions/* - Equivalence partitions
├── decision-tables/* - Decision table tests
└── pairwise/* - Combinatorial reduction
Fleet Coordination
const designFleet = await FleetManager.coordinate({
strategy: 'systematic-test-design',
agents: [
'qe-test-generator', // Apply design techniques
'qe-coverage-analyzer', // Analyze coverage
'qe-quality-analyzer' // Assess test quality
],
topology: 'sequential'
});---
Related Skills
- [agentic-quality-engineering](../agentic-quality-engineering/) - Agent-driven testing
- [risk-based-testing](../risk-based-testing/) - Prioritize by risk
- [mutation-testing](../mutation-testing/) - Validate test effectiveness
---
Remember
**With Agents:** `qe-test-generator` applies these techniques automatically, generating optimal test suites with maximum coverage and minimum redundancy. Agents identify boundaries, partitions, and combinations from code analysis.
Read more
name: test-design-techniques description: "Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage." category: specialized-testing priority: high tokenEstimate: 900 agents: [qe-test-generator, qe-coverage-analyzer, qe-quality-analyzer] implementation_status: optimized optimization_version: 1.0 last_optimized: 2025-12-02 dependencies: [] quick_reference_card: true tags: [test-design, bva, equivalence-partitioning, decision-tables, pairwise, state-transition] trust_tier: 3 validation: schema_path: schemas/output.json validator_path: scripts/validate-config.json eval_path: evals/test-design-techniques.yaml
Test Design Techniques
<default_to_action> When designing test cases, select technique by input type:
- Numeric ranges → BVA + EP
- Multiple conditions → Decision Tables
- Workflows → State Transition
- Many parameter combinations → Pairwise Testing
</default_to_action>
Quick Reference Card
When to Use
- Designing new test suites
- Optimizing existing tests
- Complex business rules
- Reducing test redundancy
---
Agent-Driven Test Design
// Auto-generate BVA tests
await Task("Generate BVA Tests", {
field: 'age',
dataType: 'integer',
constraints: { min: 18, max: 120 }
}, "qe-test-generator");
// Returns: 6 boundary test cases
// Auto-generate pairwise tests
await Task("Generate Pairwise Tests", {
parameters: {
browser: ['Chrome', 'Firefox', 'Safari'],
os: ['Windows', 'Mac', 'Linux'],
screen: ['Desktop', 'Tablet', 'Mobile']
}
}, "qe-test-generator");
// Returns: 9-12 tests (vs 27 full combination)---
Agent Coordination Hints
Memory Namespace
aqe/test-design/ ├── bva-analysis/* - Boundary value tests ├── partitions/* - Equivalence partitions ├── decision-tables/* - Decision table tests └── pairwise/* - Combinatorial reduction
Fleet Coordination
const designFleet = await FleetManager.coordinate({
strategy: 'systematic-test-design',
agents: [
'qe-test-generator', // Apply design techniques
'qe-coverage-analyzer', // Analyze coverage
'qe-quality-analyzer' // Assess test quality
],
topology: 'sequential'
});---
Related Skills
- [agentic-quality-engineering](../agentic-quality-engineering/) - Agent-driven testing
- [risk-based-testing](../risk-based-testing/) - Prioritize by risk
- [mutation-testing](../mutation-testing/) - Validate test effectiveness
---
Remember
**With Agents:** `qe-test-generator` applies these techniques automatically, generating optimal test suites with maximum coverage and minimum redundancy. Agents identify boundaries, partitions, and combinations from code analysis.
AI-powered quality engineering agents that generate tests, find coverage gaps, detect flaky tests, and learn your codebase patterns — across 11 coding agent platforms.
Repo: proffesor-for-testing/agentic-qe
Other skills on agentic-qe.
- /a11y-ally
Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
Open skill - /accessibility-testing
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
Open skill - /agentdb-advanced
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Open skill - /agentdb-learning
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
Open skill - /agentdb-memory-patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Open skill - /agentdb-optimization
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
Open skill

